Rewiring the classroom: How the COVID-19 pandemic transformed K-12 education
Subscribe to the brown center on education policy newsletter, brian a. jacob and brian a. jacob walter h. annenberg professor of education policy; professor of economics, and professor of education - university of michigan, former brookings expert cristina stanojevich cs cristina stanojevich doctoral student - michigan state university.
August 26, 2024
- The pandemic changed K-12 classrooms through new technologies, instructional practices, and parent-teacher communications, along with an emphasis on social-emotional learning.
- Less tangibly, COVID-19 might have shifted perceptions of the value and purposes of K-12 schooling.
- The durability and effects of these changes remain unclear and will depend on how educational leaders and policymakers manage them.
In March 2020, virtually all public school districts in the U.S. shut their doors. For the next 18 months, schooling looked like it never had before. Homes became makeshift classrooms; parents became de facto teachers. But by fall 2022, many aspects of K-12 education had returned to “normal.” Schools resumed in-person classes, extracurricular activities flourished, and mask mandates faded.
But did schools really return to what they were before the COVID-19 pandemic? Our research suggests not. We interviewed teachers, school leaders, and district administrators across 12 districts in two states, and then we surveyed a nationally representative set of veteran educators in May 2023. We found that the COVID-19 pandemic transformed K-12 education in fundamental ways.
Below, we describe how the pandemic reshaped the educational landscape in these ways and we consider the opportunities and challenges these changes present for students, educators, and policymakers.
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Accelerated adoption of technology
One of the most immediate and visible changes brought about by the pandemic was the rapid integration of technology into the classroom. Before COVID-19, many schools were easing into the digital age. The switch to remote learning in March 2020 forced schools to fully embrace Learning Management Systems (LMS), Zoom, and educational software almost overnight.
When students returned to in-person classrooms, the reliance on these digital tools persisted. Over 70% of teachers in our survey report that students are now assigned their own personal device (over 80% for secondary schools). LMS platforms like Google Classroom and Schoology remain essential in many schools. An assistant superintendent of a middle-income district remarked, “Google Classroom has become a mainstay for many teachers, especially middle school [and] high school.”
The platforms serve as hubs for posting assignments, accessing educational content, and enabling communication between teachers, students, and parents. They have become popular among parents as well. One teacher, who has school-age children herself, noted :
“Whereas pre-COVID…you’re hoping and praying your kids bring home information…[now] I can go on Google classroom and be like, ‘Oh, it says you worked on Mesopotamia today. What was that lesson about?’”
Transformed instructional practices
The pandemic’s impact on student learning was profound. Reading and math scores dropped precipitously, and the gap widened between more and less advantaged students. Many schools responded by adjusting their schedules or adopting new programs. Several mentioned adopting “What I need” (WIN) or “Power” blocks to accommodate diverse learning needs. During these blocks, teachers provide individualized support to students while others work on independent practice or extension activities.
Teachers report placing greater emphasis on small-group instruction and personalized learning. They spend less time on whole-class lecture and rely more on educational software (e.g., Lexia for reading and Zearn for math) to tailor instruction to individual student needs. A third-grade teacher in a low-income district explained:
“The kids are in so many different places, Lexia is very prescriptive and diagnostic, so it will give the kids specifically what level and what skills they need. [I] have a student who’s working on Greek and Latin roots, and then I have another kid who’s working on short vowel sounds. [It’s] much easier for them to get it through Lexia than me trying to get, you know, 18 different reading lessons.”
Teachers aren’t just using technology to personalize instruction. Having spent months gaining expertise with educational software, more teachers find it natural to integrate those programs into their classrooms today. Those teachers who used ed tech before report doing so even more now. They describe using software like Flowcabulary and Prodigy to make learning more engaging, and games such as Kahoot to give students practice with various skills. Products like Nearpod let them create presentations that integrate instruction with formative assessment. Other products, like Edpuzzle, help teachers monitor student progress.
Some teachers discovered how to use digital tools to save time and improve their communications to students. One elementary teacher, for example, explains even when her students complete an assignment by hand, she has them take a picture of it and upload it to her LMS:
“I can sort them, and I can comment on them really fast. So it’s made feedback better. [I have] essentially a portfolio of all their math, rather than like a hard copy that they could lose…We can give verbal feedback. I could just hit the mic and say, ‘Hey, double check number 6, your fraction is in fifths, it needs to be in tenths.’”
Increased emphasis on social-emotional learning
The pandemic also revealed and exacerbated the social-emotional challenges that students face. In our survey, nearly 40% of teachers report many more students struggling with depression and anxiety than before the COVID-19 pandemic; over 80% report having at least a few more students struggling.
These student challenges have changed teachers’ work. When comparing how they spend class time now versus before the pandemic, most teachers report spending more time on activities relating to students’ social-emotional well-being (73%), more time addressing behavioral issues (70%), and more time getting students caught up and reviewing routines and procedures (60%).
In response, schools have invested in social-emotional learning (SEL) programs and hired additional counselors and social workers. Some districts turned to online platforms such as Class Catalyst and CloseGap that allow students to anonymously report their emotional state on a daily basis, which helps school staff track students’ mental health.
Teachers also have been adapting their expectations of students. Many report assigning less homework and providing students more flexibility to turn in assignments late and retake exams.
Facilitated virtual communication between parents and teachers
The pandemic also radically reshaped parent-teacher communications. Mirroring trends across society, videoconferencing has become a go-to option. Schools use videoconferencing for regular parent-teacher conferences, along with meetings to discuss special education placements and disciplinary incidents. In our national survey, roughly one-half of teachers indicate that they conduct a substantial fraction of parent-teacher conferences online; nearly a quarter of teachers report that most of their interactions with parents are virtual.
In our interviews, teachers and parents gushed about the convenience afforded by videoconferencing, and some administrators believe it has increased overall parent participation. (One administrator observed, “Our attendance rates [at parent-teacher conferences] and interaction with parents went through the roof.”)
An administrator from a low-income district shared the benefits of virtual Individualized Education Plan (IEP) meetings:
“It’s rare that we have a face-to-face meeting…everything is Docusigned now. Parents love it because I can have a parent that’s working—a single mom that’s working full time—that can step out during her lunch break…[and] still interact with everybody.”
During the pandemic, many districts purchased a technology called Remind that allows teachers to use their personal smartphones to text with parents while blocking their actual phone number. We heard that teachers continue to text with parents, citing the benefits for quick check-ins or questions. Remind and many LMS also have translation capabilities that makes it easier for teachers and parents to overcome language barriers.
Moving forward
The changes described above have the potential to improve student learning and increase educational equity. They also carry risks. On the one hand, the growing use of digital tools to differentiate instruction may close achievement gaps, and the ubiquity of video conferencing could allow working parents to better engage with school staff. On the other hand, the overreliance on digital tools could harm students’ fine motor skills (one teacher remarked, “[T]heir handwriting sucks compared to how it used to be”) and undermine student engagement. Some new research suggests that relying on digital platforms might impede learning relative to the old-fashioned “paper and pencil” approach. And regarding virtual conferences, the superintendent of a small, rural district told us, “There’s a disconnect when we do that…No, I want the parents back in our buildings, I want people back. We’re [the school] a community center.”
Of course, some of the changes we observed may not persist. For example, fewer teachers may rely on digital tools to tailor instruction once the “COVID cohorts” have aged out of the system. As the emotional scars of the pandemic fade, schools may choose to devote fewer resources to SEL programming. It’s important to note, too, that many of the changes we found come from the adoption of new technology, and the technology available to educators will continue to evolve (e.g., with the integration of new AI technologies into personalized tutoring systems). That being said, now that educators have access to more instructional technology and—perhaps more importantly—greater familiarity with using such tools, they might continue to rely on them.
The changes brought about by the COVID-19 pandemic provide a unique opportunity to rethink and improve the structure of K-12 education. While the integration of technology and the focus on social-emotional learning offer promising avenues for enhancing student outcomes, they also require continuous evaluation. Indeed, these changes raise some questions beyond simple cost-benefit calculations. For example, the heightened role of ed tech raises questions about the proper role of the private sector in public education. As teachers increasingly “outsource” the job of instruction to software products, what might be lost?
Educational leaders and policymakers must ensure that these pandemic-inspired changes positively impact learning and address the evolving needs of students and teachers. As we navigate this new educational landscape, the lessons learned from this unprecedented time can serve as a guide for building a more resilient, equitable, and effective educational system for the future.
Beyond technological changes, COVID-19 shifted perspectives about K-12 schooling. A middle-school principal described a new mentality among teachers in her district, “I think we have all become more readily able to adapt…we’ve all learned to assess what we have in front of us and make the adjustments we need to ensure that students are successful.” And a district administrator emphasized how the pandemic highlighted the vital role played by schools:
“…we saw that when students were not in school. From a micro and macro level, the environment that a school creates to support you growing up…we realized how needed this network is…both academically and socially, in growing our citizens up to be productive in the world. And we are happy to have everyone back.”
At the end of the day, this realization may be one of the pandemic’s most enduring legacies.
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Guidance on distance learning
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School closures were mandated as part of public health efforts to contain the spread of COVID-19 from February 2020 in most countries. Education systems around the world are facing an unprecedented challenge. Governmental agencies are working with international organizations, private sector partners and civil society to deliver education remotely through a mix of technologies in order to ensure continuity of curriculum-based study and learning for all.
Supporting distance learning during COVID-19
UNESCO has been working to mitigate the impact of education disruption and school closures. In response to the pandemic, UNESCO has produced various distance learning resources to support teachers and policy-makers. The following resources offer best practices, innovative ideas and practical information.
UNESCO is supporting the organization of several workshops based on the publication Ensuring effective distance learning during COVID-19 disruption: guidance for teachers following a call for proposals that attracted almost 200 entries. The first workshop was held online on 20-21 October 2021, sponsored by the Faculty of Specific Education at Alexandria University in Egypt. Organized by Prof. Mona Sharaf Abdelgalil, the session was attended by 211 teachers from different educational departments, including 80% female teachers. The second set of workshops (six in-person, and one hybrid) took place in Zimbabwe from 5 to 24 November 2021, organized by Learning Factory and Mr Addi Mavengere. These workshops reached a total of 95 participants, including 67% female teachers, 64% from rural communities, and 1% with physical impairment. Six other pilot workshops were held in-person in Ethiopia by Mr Inku Fasil, targeting 120 teachers in Bahirdar, Addis Ababa and Adama from 13 November to 2 December 2021.
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Case studies
10 recommendations to plan distance learning solutions.
Decide on the use high-technology and low-technology solutions based on the reliability of local power supplies, internet connectivity, and digital skills of teachers and students. This could range through integrated digital learning platforms, video lessons, MOOCs, to broadcasting through radios and TVs.
Implement measures to ensure that students including those with disabilities or from low-income backgrounds have access to distance learning programmes, if only a limited number of them have access to digital devices. Consider temporarily decentralizing such devices from computer labs to families and support them with internet connectivity.
Assess data security when uploading data or educational resources to web spaces, as well as when sharing them with other organizations or individuals. Ensure that the use of applications and platforms does not violate students’ data privacy.
Mobilize available tools to connect schools, parents, teachers and students with each other. Create communities to ensure regular human interactions, enable social caring measures, and address possible psychosocial challenges that students may face when they are isolated.
Organize discussions with stakeholders to examine the possible duration of school closures and decide whether the distance learning programme should focus on teaching new knowledge or enhance students’ knowledge of prior lessons. Plan the schedule depending on the situation of the affected zones, level of studies, needs of students needs, and availability of parents. Choose the appropriate learning methodologies based on the status of school closures and home-based quarantines. Avoid learning methodologies that require face-to-face communication.
Organize brief training or orientation sessions for teachers and parents as well, if monitoring and facilitation are needed. Help teachers to prepare the basic settings such as solutions to the use of internet data if they are required to provide live streaming of lessons.
Blend tools or media that are available for most students, both for synchronous communication and lessons, and for asynchronous learning. Avoid overloading students and parents by asking them to download and test too many applications or platforms.
Define the rules with parents and students on distance learning. Design formative questions, tests, or exercises to monitor closely students’ learning process. Try to use tools to support submission of students’ feedback and avoid overloading parents by requesting them to scan and send students’ feedback.
Keep a coherent timing according to the level of the students’ self-regulation and metacognitive abilities especially for livestreaming classes. Preferably, the unit for primary school students should not be more than 20 minutes, and no longer than 40 minutes for secondary school students.
Create communities of teachers, parents and school managers to address sense of loneliness or helplessness, facilitate sharing of experience and discussion on coping strategies when facing learning difficulties.
National distance learning platforms and tools
A collection of national learning platforms and tools from Member States to facilitate the search for resources in one place.
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Remote Learning During COVID-19: Lessons from Today, Principles for Tomorrow
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"Remote Learning During the Global School Lockdown: Multi-Country Lessons” and “Remote Learning During COVID-19: Lessons from Today, Principles for Tomorrow"
WHY A TWIN REPORT ON THE IMPACT OF COVID IN EDUCATION?
The COVID-19 pandemic has disrupted education in over 150 countries and affected 1.6 billion students. In response, many countries implemented some form of remote learning. The education response during the early phase of COVID-19 focused on implementing remote learning modalities as an emergency response. These were intended to reach all students but were not always successful. As the pandemic has evolved, so too have education responses. Schools are now partially or fully open in many jurisdictions.
A complete understanding of the short-, medium- and long-term implications of this crisis is still forming. The twin reports analyze how this crisis has amplified inequalities and also document a unique opportunity to reimagine the traditional model of school-based learning.
The reports were developed at different times during the pandemic and are complementary:
The first one follows a qualitative research approach to document the opinions of education experts regarding the effectiveness of remote and remedial learning programs implemented across 17 countries. DOWNLOAD THE FULL REPORT
WHAT ARE THE LESSONS LEARNED OF THE TWIN REPORTS?
- Availability of technology is a necessary but not sufficient condition for effective remote learning: EdTech has been key to keep learning despite the school lockdown, opening new opportunities for delivering education at a scale. However, the impact of technology on education remains a challenge.
- Teachers are more critical than ever: Regardless of the learning modality and available technology, teachers play a critical role. Regular and effective pre-service and on-going teacher professional development is key. Support to develop digital and pedagogical tools to teach effectively both in remote and in-person settings.
- Education is an intense human interaction endeavor: For remote learning to be successful it needs to allow for meaningful two-way interaction between students and their teachers; such interactions can be enabled by using the most appropriate technology for the local context.
- Parents as key partners of teachers: Parent’s involvement has played an equalizing role mitigating some of the limitations of remote learning. As countries transition to a more consistently blended learning model, it is necessary to prioritize strategies that provide guidance to parents and equip them with the tools required to help them support students.
- Leverage on a dynamic ecosystem of collaboration: Ministries of Education need to work in close coordination with other entities working in education (multi-lateral, public, private, academic) to effectively orchestrate different players and to secure the quality of the overall learning experience.
- FULL REPORT
- Interactive document
- Understanding the Effectiveness of Remote and Remedial Learning Programs: Two New Reports
- Understanding the Perceived Effectiveness of Remote Learning Solutions: Lessons from 18 Countries
- Five lessons from remote learning during COVID-19
- Launch of the Twin Reports on Remote Learning during COVID-19: Lessons for today, principles for tomorrow
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MINI REVIEW article
Distance learning in higher education during covid-19.
- 1 Department of Pedagogy of Higher Education, Kazan (Volga Region) Federal University, Kazan, Russia
- 2 Department of Jurisprudence, Bauman Moscow State Technical University, Moscow, Russia
- 3 Department of English for Professional Communication, Financial University under the Government of the Russian Federation, Moscow, Russia
- 4 Department of Foreign Languages, RUDN University, Moscow, Russia
- 5 Department of Medical and Social Assessment, Emergency, and Ambulatory Therapy, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
COVID-19’s pandemic has hastened the expansion of online learning across all levels of education. Countries have pushed to expand their use of distant education and make it mandatory in view of the danger of being unable to resume face-to-face education. The most frequently reported disadvantages are technological challenges and the resulting inability to open the system. Prior to the pandemic, interest in distance learning was burgeoning, as it was a unique style of instruction. The mini-review aims to ascertain students’ attitudes about distant learning during COVID-19. To accomplish the objective, articles were retrieved from the ERIC database. We utilize the search phrases “Distance learning” AND “University” AND “COVID.” We compiled a list of 139 articles. We chose papers with “full text” and “peer reviewed only” sections. Following the exclusion, 58 articles persisted. Then, using content analysis, publications relating to students’ perspectives on distance learning were identified. There were 27 articles in the final list. Students’ perspectives on distant education are classified into four categories: perception and attitudes, advantages of distance learning, disadvantages of distance learning, and challenges for distance learning. In all studies, due of pandemic constraints, online data gathering methods were selected. Surveys and questionnaires were utilized as data collection tools. When students are asked to compare face-to-face and online learning techniques, they assert that online learning has the potential to compensate for any limitations caused by pandemic conditions. Students’ perspectives and degrees of satisfaction range widely, from good to negative. Distance learning is advantageous since it allows for learning at any time and from any location. Distance education benefits both accomplishment and learning. Staying at home is safer and less stressful for students during pandemics. Distance education contributes to a variety of physical and psychological health concerns, including fear, anxiety, stress, and attention problems. Many schools lack enough infrastructure as a result of the pandemic’s rapid transition to online schooling. Future researchers can study what kind of online education methods could be used to eliminate student concerns.
Introduction
The pandemic of COVID-19 has accelerated the spread of online learning at all stages of education, from kindergarten to higher education. Prior to the epidemic, several colleges offered online education. However, as a result of the epidemic, several governments discontinued face-to-face schooling in favor of compulsory distance education.
The COVID-19 problem had a detrimental effect on the world’s educational system. As a result, educational institutions around the world developed a new technique for delivering instructional programs ( Graham et al., 2020 ; Akhmadieva et al., 2021 ; Gaba et al., 2021 ; Insorio and Macandog, 2022 ; Tal et al., 2022 ). Distance education has been the sole choice in the majority of countries throughout this period, and these countries have sought to increase their use of distance education and make it mandatory in light of the risk of not being able to restart face-to-face schooling ( Falode et al., 2020 ; Gonçalves et al., 2020 ; Tugun et al., 2020 ; Altun et al., 2021 ; Valeeva and Kalimullin, 2021 ; Zagkos et al., 2022 ).
What Is Distance Learning
Britannica defines distance learning as “form of education in which the main elements include physical separation of teachers and students during instruction and the use of various technologies to facilitate student-teacher and student-student communication” ( Simonson and Berg, 2016 ). The subject of distant learning has been studied extensively in the fields of pedagogics and psychology for quite some time ( Palatovska et al., 2021 ).
The primary distinction is that early in the history of distant education, the majority of interactions between professors and students were asynchronous. With the advent of the Internet, synchronous work prospects expanded to include anything from chat rooms to videoconferencing services. Additionally, asynchronous material exchange was substantially relocated to digital settings and communication channels ( Virtič et al., 2021 ).
Distance learning is a fundamentally different way to communication as well as a different learning framework. An instructor may not meet with pupils in live broadcasts at all in distance learning, but merely follow them in a chat if required ( Bozkurt and Sharma, 2020 ). Audio podcasts, films, numerous simulators, and online quizzes are just a few of the technological tools available for distance learning. The major aspect of distance learning, on the other hand, is the detailed tracking of a student’s performance, which helps to develop his or her own trajectory. While online learning attempts to replicate classroom learning methods, distant learning employs a computer game format, with new levels available only after the previous ones have been completed ( Bakhov et al., 2021 ).
In recent years, increased attention has been placed on eLearning in educational institutions because to the numerous benefits that have been discovered via study. These advantages include the absence of physical and temporal limits, the ease of accessing material and scheduling flexibility, as well as the cost-effectiveness of the solution. A number of other studies have demonstrated that eLearning is beneficial to both student gains and student performance. However, in order to achieve the optimum results from eLearning, students must be actively participating in the learning process — a notion that is commonly referred to as active learning — throughout the whole process ( Aldossary, 2021 ; Altun et al., 2021 ).
The most commonly mentioned negatives include technological difficulties and the inability to open the system as a result, low teaching quality, inability to teach applicable disciplines, and a lack of courses, contact, communication, and internet ( Altun et al., 2021 ). Also, misuse of technology, adaptation of successful technology-based training to effective teaching methods, and bad practices in managing the assessment and evaluation process of learning are all downsides of distance learning ( Debeş, 2021 ).
Distance Learning in a Pandemic Context
The epidemic forced schools, colleges, and institutions throughout the world to close their doors so that students might practice social isolation ( Toquero, 2020 ). Prior to the pandemic, demand for distance learning was nascent, as it was a novel mode of education, the benefits and quality of which were difficult to judge due to a dearth of statistics. But, in 2020, humanity faced a coronavirus pandemic, which accelerated the shift to distant learning to the point that it became the only viable mode of education and communication ( Viktoria and Aida, 2020 ). Due to the advancements in digital technology, educators and lecturers have been obliged to use E-learning platforms ( Benadla and Hadji, 2021 ).
In remote education settings for higher education, activities are often divided into synchronous course sessions and asynchronous activities and tasks. In synchronous courses, learners participate in interactive and targeted experiences that help them develop a fundamental grasp of technology-enhanced education, course design, and successful online instruction. Asynchronous activities and tasks, on the other hand, include tests, group work assignments, group discussion, feedback, and projects. Additionally, asynchronous activities and tasks are carried out via interactive video-based activities, facilitator meetings, live webinars, and keynote speakers ( Debeş, 2021 ).
According to Lamanauskas and Makarskaitė-Petkevičienė (2021) , ICT should be attractive for learners. Additionally, student satisfaction with ODL has a statistically significant effect on their future choices for online learning ( Virtič et al., 2021 ). According to Avsheniuk et al. (2021) , the majority of research is undertaken to categorize students’ views and attitudes about online learning, and studies examining students’ perspectives of online learning during the COVID-19 epidemic are uncommon and few. There is presently a dearth of research on the impact on students when schools are forced to close abruptly and indefinitely and transition to online learning communities ( Unger and Meiran, 2020 ). So that, the mini-review is aimed to examining the students’ views on using distance learning during COVID-19.
In order to perform the aim, the articles were searched through ERIC database. We use “Distance learning” AND “University” AND “COVID” as search terms. We obtained 139 articles. We selected “full text” and “Peer reviewed only” articles. After the exclusion, 58 articles endured. Then content analyses were used to determine articles related to students’ voices about distance learning. In the final list, there were 27 articles ( Table 1 ).
![distance education during covid 19 www.frontiersin.org](https://www.frontiersin.org/files/Articles/822958/feduc-07-822958-HTML/image_m/feduc-07-822958-t001.jpg)
Table 1. Countries and data collection tools.
In the study, a qualitative approach and content analyses were preferred. Firstly, the findings related to students’ attitudes and opinions on distance learning were determined. The research team read selected sections independently. Researchers have come to a consensus on the themes of perception and attitudes, advantages of distance learning, disadvantages of distance learning, and challenges for distance learning. It was decided which study would be included in which theme/s. Finally, the findings were synthesized under themes.
Only 3 studies ( Lassoued et al., 2020 ; Viktoria and Aida, 2020 ; Todri et al., 2021 ) were conducted to cover more than one country. Other studies include only one country. Surveys and questionnaires were mostly used as measurement tools in the study. Due to pandemic restrictions, online data collection approaches were preferred in the data collection process.
Students’ views on distance learning are grouped under four themes. These themes are perception and attitudes, advantages of distance learning, disadvantages of distance learning, and challenges for distance learning.
Perception and Attitudes Toward Distance Learning
Students’ attitudes toward distance learning differ according to the studies. In some studies ( Mathew and Chung, 2020 ; Avsheniuk et al., 2021 ), it is stated that especially the students’ attitudes are positive, while in some studies ( Bozavlı, 2021 ; Yurdal et al., 2021 ) it is clearly stated that their attitudes are negative. In addition, there are also studies ( Akcil and Bastas, 2021 ) that indicate that students’ attitudes are at a moderate level. The transition to distance learning has been a source of anxiety for some students ( Unger and Meiran, 2020 ).
When the students’ satisfaction levels are analyzed, it is obvious from the research ( Gonçalves et al., 2020 ; Avsheniuk et al., 2021 ; Bakhov et al., 2021 ; Glebov et al., 2021 ; Todri et al., 2021 ) that the students’ satisfaction levels are high. In some studies, it is pronounced that the general satisfaction level of the participants is moderate ( Viktoria and Aida, 2020 ; Aldossary, 2021 ; Didenko et al., 2021 ) and low ( Taşkaya, 2021 ).
When students compare face-to-face and online learning methods, they state that online learning has opportunities to compensate for their deficiencies due to the pandemic conditions ( Abrosimova, 2020 ) and but they prefer face-to-face learning ( Gonçalves et al., 2020 ; Kaisar and Chowdhury, 2020 ; Bakhov et al., 2021 ). Distance learning is not sufficiently motivating ( Altun et al., 2021 ; Bozavlı, 2021 ), effective ( Beltekin and Kuyulu, 2020 ; Bozavlı, 2021 ), and does not have a contribution to students’ knowledge ( Taşkaya, 2021 ). Distance education cannot be used in place of face-to-face instruction ( Aldossary, 2021 ; Altun et al., 2021 ).
Advantages of Distance Learning
It is mostly cited advantages that distance learning has a positive effect on achievement and learning ( Gonçalves et al., 2020 ; Lin and Gao, 2020 ; Aldossary, 2021 ; Altun et al., 2021 ; Şahin, 2021 ). In addition, in distance learning, students can have more resources and reuse resources such as re-watching video ( Önöral and Kurtulmus-Yilmaz, 2020 ; Lamanauskas and Makarskaitė-Petkevičienė, 2021 ; Martha et al., 2021 ).
Distance learning for the reason any time and everywhere learning ( Adnan and Anwar, 2020 ; Lamanauskas and Makarskaitė-Petkevičienė, 2021 ; Todri et al., 2021 ). There is no need to spend money on transportation to and from the institution ( Lamanauskas and Makarskaitė-Petkevičienė, 2021 ; Nenakhova, 2021 ). Also, staying at home is safe during pandemics and less stressful for students ( Lamanauskas and Makarskaitė-Petkevičienė, 2021 ).
Challenges and Disadvantages of Distance Learning
Distance learning cannot guarantee effective learning, the persistence of learning, or success ( Altun et al., 2021 ; Benadla and Hadji, 2021 ). Students state that they have more works, tasks, and study loads in the distance learning process ( Mathew and Chung, 2020 ; Bakhov et al., 2021 ; Didenko et al., 2021 ; Nenakhova, 2021 ). Group working and socialization difficulties are experienced in distance learning ( Adnan and Anwar, 2020 ; Bozavlı, 2021 ; Lamanauskas and Makarskaitė-Petkevičienė, 2021 ). The absence of communication and face-to-face interaction is seen a disadvantage ( Didenko et al., 2021 ; Nenakhova, 2021 ).
It is difficult to keep attention on the computer screen for a long time, so distance-learning negatively affects concentration ( Bakhov et al., 2021 ; Lamanauskas and Makarskaitė-Petkevičienė, 2021 ). In addition, distance education prompts some physical and psychological health problems ( Kaisar and Chowdhury, 2020 ; Taşkaya, 2021 ).
Devices and internet connection, technical problems are mainly stated as challenges for distance learning ( Abrosimova, 2020 ; Adnan and Anwar, 2020 ; Mathew and Chung, 2020 ; Bakhov et al., 2021 ; Benadla and Hadji, 2021 ; Didenko et al., 2021 ; Lamanauskas and Makarskaitė-Petkevičienė, 2021 ; Nenakhova, 2021 ; Taşkaya, 2021 ; Şahin, 2021 ). In addition, some students have difficulties in finding a quiet and suitable environment where they can follow distance education courses ( Taşkaya, 2021 ). It is a disadvantage that students have not the knowledge and skills to use the technological tools used in distance education ( Lassoued et al., 2020 ; Bakhov et al., 2021 ; Didenko et al., 2021 ).
The purpose of this study is to ascertain university students’ perceptions about distant education during COVID-19. The study’s findings are intended to give context for developers of distant curriculum and higher education institutions.
According to Toquero (2020) , academic institutions have an increased need to enhance their curricula, and the incorporation of innovative teaching methods and tactics should be a priority. COVID-19’s lockout has shown the reality of higher education’s current state: Progressive universities operating in the twenty-first century did not appear to be prepared to implement digital teaching and learning tools; existing online learning platforms were not universal solutions; teaching staff were not prepared to teach remotely; their understanding of online teaching was sometimes limited to sending handbooks, slides, sample tasks, and assignments to students via email and setting deadlines for submission of completed tasks ( Didenko et al., 2021 ).
It is a key factor that student satisfaction to identify the influencers that emerged in online higher education settings ( Parahoo et al., 2016 ). Also, there was a significant positive relationship between online learning, social presence and satisfaction with online courses ( Stankovska et al., 2021 ). According to the findings, the attitudes and satisfaction levels of the students differ according to the studies and vary in a wide range from positive to negative attitudes.
According to the study’s findings, students responded that while online learning is beneficial for compensating for deficiencies during the pandemic, they would prefer face-to-face education in the future. This is a significant outcome for institutions. It is not desirable for all students to take their courses entirely online. According to Samat et al. (2020) , the one-size-fits-all approach to ODL implementation is inapplicable since it not only impedes the flow of information delivery inside the virtual classroom, but it also has an impact on psychological well-being because users are prone to become disturbed.
In distance learning, students can have more resources and reuse resources such as re-watching videos. So, distance learning has a positive effect on achievement and learning. Alghamdi (2021) stated that over the last two decades, research on the influence of technology on students’ academic success has revealed a range of good and negative impacts and relationships, as well as zero effects and relationship.
The result also shows that distance education prompts some physical and psychological health problems. Due to the difficulty of maintaining focus on a computer screen for an extended period of time, remote education has a detrimental effect on concentration. There is some evidence that students are fearful of online learning in compared to more traditional, or in-person, in-class learning environments, as well as media representations of emergencies ( Müller-Seitz and Macpherson, 2014 ).
Unsatisfactory equipment and internet connection, technical difficulties, and a lack of expertise about remote learning technology are frequently cited as distance learning issues. Due to the pandemic’s quick move to online education, many schools have an insufficient infrastructure. Infrastructure deficiency is more evident in fields that require laboratory work such as engineering ( Andrzej, 2020 ) and medicine ( Yurdal et al., 2021 ).
Conclusion and Recommendation
To sum up, students’ opinions and levels of satisfaction vary significantly, ranging from positive to negative. Distance learning for the reason any time and everywhere learning. Distance learning has a positive effect on achievement and learning. Staying at home is safe during pandemics and less stressful for students. Distance education prompts some physical and psychological health problems such as fear, anxiety, stress, and losing concentration. Due to the pandemic’s quick move to online education, many schools have an insufficient infrastructure. Future researchers can investigate what distance education models can be that will eliminate the complaints of students. Students’ positive attitudes and levels of satisfaction with their distant education programs have an impact on their ability to profit from the program. Consequently, schools wishing to implement distant education should begin by developing a structure, content, and pedagogical approach that would improve the satisfaction of their students. According to the findings of the study, there is no universally applicable magic formula since student satisfaction differs depending on the country, course content, and external factors.
Author Contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.
This manuscript has been supported by the Kazan Federal University Strategic Academic Leadership Program.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Keywords : ICT, distance learning, COVID-19, higher education, online learning
Citation: Masalimova AR, Khvatova MA, Chikileva LS, Zvyagintseva EP, Stepanova VV and Melnik MV (2022) Distance Learning in Higher Education During Covid-19. Front. Educ. 7:822958. doi: 10.3389/feduc.2022.822958
Received: 26 November 2021; Accepted: 14 February 2022; Published: 03 March 2022.
Reviewed by:
Copyright © 2022 Masalimova, Khvatova, Chikileva, Zvyagintseva, Stepanova and Melnik. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alfiya R. Masalimova, [email protected]
† ORCID: Alfiya R. Masalimova, orcid.org/0000-0003-3711-2527 ; Maria A. Khvatova, orcid.org/0000-0002-2156-8805 ; Lyudmila S. Chikileva, orcid.org/0000-0002-4737-9041 ; Elena P. Zvyagintseva, orcid.org/0000-0001-7078-0805 ; Valentina V. Stepanova, orcid.org/0000-0003-0495-0962 ; Mariya V. Melnik, orcid.org/0000-0001-8800-4628
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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Student's perspective on distance learning during COVID-19 pandemic: A case study of Western Michigan University, United States
Wassnaa al-mawee.
a Department of Computer Science, Western Michigan University, 1903 W. Michigan Ave., Kalamazoo, MI 49008-5466, USA
Keneth Morgan Kwayu
b Department of Civil and Transportation Engineering, Western Michigan University, 1903 W. Michigan Ave., Kalamazoo, MI 49008-5466, USA
Tasnim Gharaibeh
As the distance learning process has become more prevalent in the USA due to the COVID-19 pandemic, it is important to understand students’ experiences, perspectives, and preferences. Our study's purpose is to reveal students’ perspectives and preferences on distance learning due to the dramatic change that happened in the education process. Western Michigan University is used as the case study to achieve that purpose. Participants completed an online survey that investigated two measures: distance learning and instructional methods with a set of scales associated with each. Students reported negative experiences of distance learning such as lack of social interaction and positive experiences such as time and location flexibility. These findings may help WMU and higher educational institutions to improve distance learning education.
1. Introduction
The benefits and challenges of distance learning have been a subject of continuous discussion in the past. Of recent, the topic of distance learning has become more relevant and imminent due to the COVID-19 pandemic. The COVID-19 has compelled most of the higher education institutions to shift to either distance learning and/or some form of hybrid teaching model ( Smalley, 2020 ). This has disrupted the natural ecosystem of conventional learning environments where students live and study in close proximity. Challenges that have been raised in the previous studies about distance learning include variation in the quality of educational instructions, students’ unequal access to the essential technologies for distance learning, and technology readiness of students ( Ratliff, 2009 ). For example, one study found that 20% of students reported having issues in accessing essential technology for distance learning such as laptops and high-speed internet ( Gonzales, Calarco, & Lynch, 2018 ). Also, it has been found that students who were already suffering academically in face-to-face instruction are more likely to obtain lower grade points in distance learning ( Xu & Jaggars, 2014 ). Despite the challenges, this sudden and unexpected change in the learning environment offers opportunities for academic institutions to reimage innovative modes of learning that take advantage of the current technologies. Therefore, the challenges and opportunities of shifting from in-person instruction mode to remote/distance instruction mode need a thorough assessment. This study intends to explore the benefits and challenges of distance learning based on student's perspectives. The case study selected 5000 students randomly from all undergraduate and graduate students at Western Michigan University to participate in the survey and we got 420 responses.
2. Related work
Distance education, or remote learning, refers to technology-based teaching in which students during the entire course of learning are physically removed from teachers at a place. It is learning from outside the normal classroom and involves online education ( Lei & Gupta, 2010 ) A distance learning program can be completely distance learning, or a combination of distance learning and traditional classroom instruction (called hybrid) ( Tabor, 2007 ). This form of teaching helps teachers to access a considerably broader audience and facilitates greater versatility in the curriculum for students. Online education is a term under the distance education umbrella. It is education that takes place over the Internet. It is often referred to as “e-learning” in other terms. However, it is just one type of “distance learning”.
Many works and research were made to study the students’ perceptions of distance learning. In one of them, especially related to students’ perceived impacts of the COVID-19 pandemic, Aristovnik, Keržič, Ravšelj, Tomaževič, and Umek (2020) introduced a comprehensive and large-scale study of students’ perceived impacts of the COVID-19 pandemic on different aspects of their lives on a global level. Their study sample contains 30,383 students enrolled in higher education institutions, who were at least 18 years old from 62 countries, where a multi-lingual web-based comprehensive questionnaire composed of 39 predominantly closed-ended questions was used to collect the data. The questionnaire addressed socio-demographic, geographic, and other characteristics, in addition to the various features and elements of higher education student life, such as online academic work and life, emotional life, social life, personal situations, changing habits, responsibilities, as well as personal thoughts on COVID-19.
Under the online academic, as part of the distance learning, work, and life element, an ordinal logistic regression analysis was used to indicate which factors influence the students’ satisfaction with the role of the university. This logistic regression model implemented in Python programming language using libraries Pandas and Numpy which is the same language that they used to prepare, clean, and aggregate their data. The results emphasize that satisfaction with asynchronous online teaching methods such as recorded videos (p<0.001), information on exams oqr the procedure of examination in times of crisis (p<0.001), teaching staff (lecturers), and websites, social media information have a positive effect on students’ satisfaction with the role of the university during the COVID-19 pandemic. The result also showed that the students’ workload was larger or significantly larger in online teaching, in addition to some difficulty in using online teaching platforms ( Aristovnik et al., 2020 ).
On the other hand, to answer the question of how students experience distance learning, Blackmon and Major (2012) introduced an investigation using qualitative research synthesis to collect the data. They ended with 10 studies focusing on online learning. To analyze the data, they summarized the articles and extracted findings. The findings were grouped into student factors that influenced experience and instructor factors that influenced student experience. Students must combine work and families, handle time and devote themselves individually. In the absence of physical copresence, teachers can strive to develop academic relationships with students and to create a sense of community. The balance between student and teacher considerations affects the classroom and student interactions. According to their theoretical framework suggestion, the students are more abstract and understandingly observing their academic experiences. In some situations, students appeared to miss the physical markers and signals that make social interactions easier to discuss. In other situations, some students seemed to succeed in the new environment. Although the student must be responsible, the teacher also has a significant role to do to generate creative online environments that facilitate the delivery and use of new intellectual skills.
Another survey of professors, staff, and students was commissioned by Illinois Community Colleges Online in 2005 to determine the pressing concerns affecting quality, retention, and capacity building related to online learning. About one thousand people from seventeen Illinois community colleges presented data relating to these three problems over six months ( Hutti, 2007 ). Three separate methods were used in the data collection method: an electronic survey of faculty, employees, and students; a focus group including faculty, employees, and students; and interviews with select faculty, employees, and students. The findings of the review of the collected data showed that the consistency benchmarks that were most important and least important for distance learning, especially online learning, were decided by faculty, staff, and students. Using a four-point Likert Scale (Strongly Agree = 4, Agree = 3, Disagree = 2, and Strongly Disagree = 1), all three groups of respondents were asked to rate the importance of each quality benchmark. The top 5 quality benchmarks rated most important based on highest means where technical assistance in course development is available to faculty, a college-wide system (such as Blackboard or WebCT) supports and facilitates the online courses, faculty are encouraged to use technical assistance in course development, faculty give constructive feedback on student assignments and to their questions, and faculty are assisted in the transition from classroom teaching to online instruction ( Hutti, 2007 ).
To focus on a specific level college, Fedynich, Bradley and Bradley (2015) studied the graduate students’ perceptions regarding distance learning using the analysis of an online survey. Their findings indicate that the role of the teacher, the contact between students and with the teacher, and feedback and assessment were identified as being essential to the satisfaction of the students. Other difficulties found included technical support for learners connected to campus services, and the need for differing educational design and implementation to promote the ability of students to study. Students, on the other hand, were highly pleased with the consistency and organization of teaching using the right tools.
In order to find ways to improve and support distance learning, faculty members in the Distance Education Center at the University of West Georgia came together to form the “Online Refresh Faculty Learning Community” (FLC) ( Rath, Olmstead, Zhang, & Beach, 2019 ). They introduced a study conducted at a public comprehensive university located in the northeastern United States. The participants were invited to answer an online survey through Qualtrics that collected quantitative and qualitative data. Coding sheets in Excel and SPSS were used for analyzing quantitative data where qualitative data were analyzed using grounded theory procedures. In the quantitative data, the result under the factor of comfort level using technology showed 55% of participants were extremely comfortable using technology and only 2% were uncomfortable. Under the preferred course modality factor, students preferred the in-person courses followed by the online courses, and at last, the hybrid/blind courses. Four factors were addressed in the qualitative data results, set-up of the course; learner characteristics and sense of course learning; social interactions; and technology issues. Regarding how the course set up by the instructor influenced the perceptions of students about the quality and efficacy of distance learning environments, successful contact was considered as a key to an online course's progress. Next, the clear due dates and understandable instructions on assignments came as important components of the course organization. Under learner characteristics, distance learning works best for the students who demonstrate strong self-regulatory behaviors and managing their time. Also, many students in their study surveyed reported frustration with learning online applications and with the lack of reliability of the internet. On the other hand, their result showed clearly, the social aspect of face-to-face classes is very important and valuable to most students.
Students stated some advantages for distance learning such as saving time, fitting in better with schedules, enabling students to take more courses, self-paced study, time and space flexibility, distance learning course often costs less ( O'Malley & McCraw, 1999 ). The disadvantages of distance learning that were mentioned include the need for consistent access to technology, the absence of face-to-face contact ( Young & Norgard, 2006 ), the feeling of isolation, the challenge to remain focused, and the difficulty of obtaining immediate feedback ( Lei & Gupta, 2010 ; Paepe, Zhu, & Depryck, 2017 ; Venter, 2010 ; Zuhairi, Zuhairi, Wahyono, & Suratinah, 2006 ).
Many recommendations arising from the previous studies include the following suggestions; continue to offer the courses in many formats (in-person and online) to provide a choice for students, continue to offer professional development and training for instructors ( Burns, 2013 ), providing the learners with social support and sufficient motivation, instead of providing only synchronous or only asynchronous practices, using these environments together ( Allen, 2017 ; Cankaya & Yunkul, 2018 ) consider the students who have complex and special needs with special education support, try to open communication channels among administrators, educators, and students and improve mental wellness programs and provide proactive psychosocial help to students ( Allen, 2017 ).
The purpose of the present study was to share information and experiences that can positively impact distance learning in WMU, besides revealing the factors that affect the students’ experience and investigating the impact of student and college characteristics on perceptions of online learning. The study examined two key college characteristics – namely, college-level and college type to reveal the students’ preferences and experiences of distance learning at WMU. The study pursued to address the following explicit research questions:
- 1 What are the WMU students' general perceptions about distance learning?
- 2 What are the significant differences in perceptions of distance learning when comparing different college types?
- 3 How are perceptions of graduate-level students differ from the perceptions of undergraduate-level students of distance learning?
- 4 What are the students’ preferences regarding instructional methods of distance learning?
4.1. Data collection procedure
The survey was administered online through Western Michigan University's official website, Qualtrics. Qualtrics platform is a powerful platform for survey design, and it was available on the WMU official website to all WMU students, faculty, and staff. Informed consent and a link to the survey were distributed to students through the university e-mail. Students were asked to state their perspectives and preferences by choosing one choice in a Likert scale survey. An option is also provided for the subject to input additional comments. Students were able to complete the survey in approximately 10-15 minutes at their own convenience within two weeks. No identifiable private information was obtained from the participants.
4.2. Participants
The participants in this study were 420 undergraduate and graduate students enrolled in different distance learning - education courses during the 2019-2020 academic year at Western Michigan University, the U.S. Of the participants, 251 were female (59.76%), 160 were male (38.10%), and 9 (2.14%) were identified as other, with an age range of 18-55 years and above. In terms of college-level, 72 (17.14%) of participants were freshmen, 57 (13.57%) were sophomores, 74 (17.62%) were juniors, 105 (25.00%) were seniors, 107 (25.48%) were graduate students, and 5 (1.19%) were identified as other. The study considered all 11 colleges at WMU. Most of the participants, 107 (25.48%) from the College of Arts and Sciences (CAS), 22 (5.24%) from College of Aviation (CA), 51 (12.14%) from Haworth College of Business (HCB), 61 (14.52%) from College of Education and Human Development (CEHD), 81 (19.29%) from College of Engineering and Applied Sciences (CEAS), 29 (6.90%) from College of Fine Arts (CFA), 48 (11.43%) College of Health and Human Services (CHHS), 3 (0.71%) from Lee Honors College (LHC), 14 (3.33%) from Graduate College (GC), 0 (0.00%) from Thomas M. Cooley Law School (TMCLS) and Homer Stryker M.D. School of Medicine, respectively. Tables 1 and and2 depict 2 depict the participants’ gender and age by college level and college type, respectively.
Participants’ gender and age by college level,
72 | 57 | 74 | 105 | 107 | 5 | |
Female | 45 | 31 | 38 | 59 | 75 | 3 |
Male | 25 | 24 | 35 | 44 | 30 | 2 |
Other | 2 | 2 | 1 | 2 | 2 | 0 |
< 24 years old | 70 | 48 | 55 | 80 | 34 | 2 |
25-34 years old | 0 | 4 | 14 | 18 | 43 | 1 |
> 35 years old | 2 | 5 | 5 | 7 | 30 | 2 |
Participants’ gender and age by college type,
Total | 107 | 22 | 51 | 61 | 81 | 29 | 48 | 3 | 14 | 4 |
---|---|---|---|---|---|---|---|---|---|---|
Gender | ||||||||||
Female | 73 | 5 | 29 | 46 | 25 | 18 | 43 | 2 | 6 | 4 |
Male | 29 | 17 | 22 | 14 | 56 | 8 | 5 | 1 | 8 | 0 |
Other | 5 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 0 | 0 |
Age range | ||||||||||
< 24 years old | 74 | 19 | 41 | 28 | 63 | 26 | 27 | 3 | 6 | 2 |
25-34 years old | 20 | 2 | 6 | 19 | 14 | 2 | 12 | 0 | 5 | 0 |
> 35 years old | 13 | 1 | 4 | 14 | 4 | 1 | 9 | 0 | 3 | 2 |
To assess the sample representativeness, the survey sample size was compared with the total number of students in WMU by college level and age. Out of 22,562 students at WMU, 4802 (21.28%) were graduate students and 17,760 (78.72%) were undergraduate students. The total percentage by college-level aligned well with the survey sample size, whereby out of 420 participants, 107 (25.48%) were graduate students and 313 (74.52%) were graduate students. In terms of age group, most of the WMU students were below 24 years old (75%), followed by 24-34 years (17%) and greater than 34 years (8%). The same pattern was observed in the survey sample size with students below 24 years constituting 69% followed by 24-34 years (19%) and greater than 34 years (12%).
4.3. Measures
The survey incorporated demographic questions, Likert scale questions, and open-end questions. Participants answered five demographic questions regarding gender, age, college level, college type, and department types. Also, they were asked to rate the items using a five-point scale (“Strongly Agree”, “Agree”, “Neutral”, “Disagree”, “Strongly Disagree”). In addition, the participants were asked to input additional comments as open-end questions. The Likert scale and text-based measurements are reconstructed into scales and items as shown in Table 3 and Table 4 , respectively.
Measures for distance learning,
Distance learning flexibility | Distance learning is effective due to location flexibility (Item 1), Distance learning is effective due to class-time flexibility (Item 2), Distance learning saves your time and effort to reach the campus (Item 3), Distance learning causes spending more time doing your classwork (Item 8), You are keeping up with your schoolwork in distance learning as much as you were in personal learning (Item 10) |
Distance learning improvement | Distance learning has improved on-campus classes (in-class learning) (Item 4), Distance learning has better instruction (Item 5), With distance learning, you have learned as much as you were before the COVID-19 crisis (Item 9), Distance learning improves your grades vs. personal learning (Item 11) |
Students interaction and collaboration | Distance learning provides more interaction with the instructor (Item 6), Distance learning provides more interaction with classmates (Item 7) |
Computer and internet usage | Distance learning is manageable because you have internet access at home (Item 12), You have access to a computer or device (other than a computer) that you can use for distance learning (Item 13) |
1. Are you satisfied with the distance learning education provided to you? | |
2. Do you prefer to continue distance learning? |
Measures for instructional methods,
Instructors | Your instructor has provided you clear instructions for how to access the online instructional materials for your classes (Item 1), Your instructors are available online to you when you need help (Item 2), Your instructors have provided you with different ways to demonstrate your learning online (Item 3), Online contact with your instructor is better than face-to-face (Item 4) |
Distance learning tools | It is easy to use distance learning tools that WMU/ instructor provides (Item 5), Meeting and learning through WebEx, Zoom, and Microsoft365) are effective (Item 6) |
Distance learning methods’ preferences | You prefer in-person or hybrid classes over online classes (Item 7), Online classes are a preferable choice due to COVID-19 crises (Item 8), You prefer asynchronous online teaching method (Require no in-person or synchronous online meetings) (Item 9), You prefer synchronous online teaching method (Classes meet exclusively through distance education technologies) (Item 10) |
1. What is the best thing about the online teaching? | |
2. What is the worst thing about the online teaching? |
5. Statistical Methods
The distributions of student's responses to distance learning were analyzed using cross-tabulations and statistical tests. The Chi-square test of independence was used to test if there was a significant association between students’ response to the distance learning experience by college level and college type. The Chi-Square test is a non-parametric test, and it is suitable for categorical data analysis to assess the probability of association or independence of facts ( McHugh, 2012 ). It does not impose prior conditions to the data such as equality of variance or residual homoscedasticity ( Pandis, 2016 ). The test measures how much difference exists between the observed counts and the counts that would be expected if there were no relationship at all in the population. In this study, the null hypothesis (H o ) stated that there is no difference in student rating of a given question related to distance learning across college level or college type. The alternative hypothesis (H 1 ) is the inverse of the null hypothesis stating that there is a difference in student ratings by college type or college level. The null hypothesis was rejected if the p -value was less than 0.05. The Chi-square statistics can be computed using Eq. (1 );
whereby, O i j is the observed frequency and E i j is the expected frequency. The computed χ 2 is compared with the critical value obtained from the Chi-square distribution. The degrees of freedom ( df ) for the critical value can be computed as (c-1) (r-1) , where c is the number of columns and r is the number of rows in the contingency table.
The Cramer's V is also used in conjunction with Chi-Squared statistics. It is used to indicate the strength of association between two variables ( Allen, 2017 ). The Cramer's V values range from 0 which corresponds to no association to 1 which corresponds to complete association. It can be computed by taking the square root of the chi-square statics divided by the sample size and normalized by the minimum of rows or columns in the contingency table as shown in Eq. (2 )
whereby χ 2 is the Chi-squared statistics, n is the sample size involved in the test, c is the number of columns and r is the number of rows.
The result section is subdivided into two subsections namely students’ perceptions of distance learning and students’ perception of instructional methods. For each subsection, the students’ rating results are discussed based on college level and college type. Data were analyzed by calculating Chi-square values, , and p-values as discussed in the statistical methods section.
6.1. Students’ perceptions of distance learning
In this study, WMU students were asked to share their experience of distance learning as the WMU campuses were compelled to move from in-person class to distance learning class during the COVID-19 pandemic. The questions for this section were designed to capture four main aspects of distance learning which were collaboration and interactions, improvement associated with distance learning, flexible options associated with distance learning, and availability of required resources such as personal laptops and the internet for distance learning. Fig. 1 provides an overall of students’ ratings ranging from strongly agree (5 points) to strongly disagree(0 points) on the four main aspects of distance learning that were explored in this study. Distance learning flexibility had the highest ratings while student interaction and collaboration had the least ratings.
![Click on image to zoom Fig. 1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr1_lrg.jpg)
Overall student's perception of distance learning during the COVID-19 pandemic,
Figs. 2 and and3 present 3 present the results of students’ view of distance learning by college level and college type, respectively. Table 5 provides the Chi-square test results of students’ ratings by college level and college type. Most of the students felt distance learning disrupted and diminished interactions and collaboration with classmates and instructors. The student ratings significantly varied across college level (? 2 =44.517, p=0.001) and college type (? 2 =49.941, p=0.023) as shown in Table 5 . For the college level, about 95% of freshmen disagree with the statement that distance learning provides more interactions with other students. However, the percent of disagreement diminished with a higher college level as shown in Fig. 2 . Only 75% of the graduate student disagree with the statement while 12% felt that distance learning increases interactions with classmates. Only 12% of the graduate students felt that distance learning increases interactions with classmates while 75% of the graduate student disagree with the statement. The same trend was observed when comparing the rate of agreement about the interaction with the instructors. Most of freshmen (87%) felt distance learning has reduced the interaction compared to only 66% of graduate students. Sophomore, Juniors, and Seniors' percentage of disagreement with the students’ interaction ranged from 76% to 82%. From the results, it can be observed that most of the students perceived a lack of interaction among students and the instructor as the result of shifting to distance education during the pandemic, mostly the freshman. The effect was less severe to higher college level especially graduate students. College experience may have contributed to the observed pattern.
![Click on image to zoom Fig. 2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr2_lrg.jpg)
Overall student's perception of distance learning during the COVID-19 pandemic by college level,
![Click on image to zoom Fig. 3](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr3_lrg.jpg)
Overall student's perception of distance learning during the COVID-19 pandemic by college type,
Chi-Squared test of association students rating of instructional methods with college level and college type,
χ (20) | χ | ||||||
---|---|---|---|---|---|---|---|
Distance learning provides more interaction with classmates | 44.517 | 0.175 | 49.941 | 0.186 | |||
Distance learning provides more interaction with the instructor | 30.483 | 0.062 | 0.145 | 27.670 | 0.686 | 0.139 | |
Distance learning has improved on-campus classes (in-class learning) | 32.797 | 0.150 | 29.467 | 0.595 | 0.143 | ||
With distance learning, you have learned as much as you were before the COVID-19 crisis | 61.764 | 0.206 | 34.134 | 0.365 | 0.154 | ||
Distance learning has better instructions | 31.089 | 0.146 | 37.381 | 0.236 | 0.161 | ||
Distance learning has improved on-campus classes (in-class learning) | 32.797 | 0.150 | 29.467 | 0.595 | 0.143 | ||
You are keeping up with your schoolwork in distance learning as much as you were in personal learning | 22.491 | 0.314 | 0.124 | 23.055 | 0.877 | 0.127 | |
Distance learning causes spending more time doing your class work | 18.192 | 0.575 | 0.112 | 45.407 | 0.178 | ||
Distance learning saves your time and effort to reach the campus | 38.215 | 0.162 | 38.349 | 0.204 | 0.163 | ||
Distance learning is effective due to location flexibility | 37.400 | 0.160 | 23.063 | 0.876 | 0.127 | ||
Distance learning is effective due to class-time flexibility | 27.246 | 0.128 | 0.137 | 31.736 | 0.480 | 0.149 | |
You have access to a computer or device (other than a computer) that you can use for distance learning | 14.988 | 0.777 | 0.102 | 38.914 | 0.186 | 0.164 | |
Distance learning is manageable because you have internet access at home | 23.938 | 0.245 | 0.128 | 45.061 | 0.177 |
It was also the aim of this study to assess student's perspectives on how distance learning affected their academic progress and success. Four different questions were asked under the “distance learning improvement” category as shown in Fig. 2 . Most of the students indicated that distance learning did not improve on-campus classes or instructions. Further, the rating indicated that most of the students did not learn as much as they would have learned in in-person classes. On the issues of academic success, most students stated that distance learning did not improve their grades compared to if the classes were done in person. The students' rating of academic progress and success during distance learning significantly vary by college level but not college type as shown in Table 5 . The majority of graduate students (41%) agreed that they have learned as much as they learned before the COVID-19 pandemic during in-person classes compared to 27% of students who disagreed or strongly disagreed with the statement. For the undergraduate level, most of the students felt the academic progress and success were negatively affected by the transition to distance learning.
Among the strength of distance learning is the location and time flexibility in class attendance and doing assignments. Students were asked to rate how distance learning has impacted the time they spent completing their assignments. Further, the students were asked if distance learning is effective due to location and time flexibility. The distribution of the results by college level and college type shows that most of the students agreed that distance education offered time and location flexibility. Their responses were in most cases uniform across college level and college type except for location flexibility (? 2 =34.700, p=0.010). The flexibility option offered by distance learning was much appreciated by graduate students (84%) compared to undergraduates.
For distance learning to be effective, students need to have essential resources such as reliable internet access and personal computer resources. The results indicated some minor concerns on the issues of internet at home. About 93% of students that were surveyed reported having a computer or a device to use for distance learning. Only 4% of the student indicated that they lacked personal computers with 4% being neutral on the subject. This was a good indicator for an effective distance learning experience despite the concerns that were raised in the area of interaction and collaboration and improvement in academic progress and success.
6.2. Students’ perceptions of instructional methods
The study assessed student's perception of distance learning instructional methods that were offered by WMU. Instructional methods are the teaching and learning techniques, used by teachers to create learning environments and to specify the nature of the activity in which the teacher and learner will be involved during the education process. Distance education requires different instructor's efforts, special tools, and teaching methods than those needed in traditional classrooms.
The importance of the instructor in distance learning is growing and should be more intensive to the adaptation of new learning environments. Instructor availability, communication, and feedback are some factors the impact distance learning ( Yengin, Karahoca, Karahoca, & Yücel, 2010 ).
A total of ten questions were asked and grouped into three main groups namely instructors, distance learning tools, and distance learning methods preferences as shown in Fig. 4 . The Chi-square test results of students rating of instruction methods by college level and college type presented in Table 6 .
![Click on image to zoom Fig. 4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr4_lrg.jpg)
Overall student's perception of instructors and instructions methods during the COVID-19 pandemic,
Chi-Squared test of association students rating of instructional methods with college-level and college type,
χ | χ | ||||||
---|---|---|---|---|---|---|---|
Online contact with your instructor is better than face-to-face | 22.857 | 0.296 | 0.126 | 36.103 | 0.283 | 0.159 | |
Your instructors have provided you with different ways to demonstrate your learning online | 41.765 | 0.170 | 41.380 | 0.124 | 0.170 | ||
Your instructors are available online to you when you need help | 33.900 | 0.153 | 51.197 | 0.189 | |||
Your instructor has provided you clear instructions for how to access the online instructional materials for your classes | 37.753 | 0.161 | 38.212 | 0.208 | 0.163 | ||
Meeting and learning through WebEx, Zoom, and Microsoft365) are effective | 31.626 | 0.148 | 40.776 | 0.137 | 0.169 | ||
It is easy to use distance learning tools that WMU/ instructor provides | 29.099 | 0.086 | 0.142 | 31.868 | 0.473 | 0.149 | |
You prefer synchronous online teaching method (Classes meet exclusively through distance education technologies) | 23.473 | 0.266 | 0.127 | 50.764 | 0.188 | ||
Online classes are a preferable choice due to COVID-19 crises | 33.665 | 0.152 | 31.419 | 0.496 | 0.148 | ||
You prefer in-person or hybrid classes over online classes | 37.793 | 0.161 | 41.126 | 0.129 | 0.169 | ||
You prefer asynchronous online teaching method (Require no in-person or synchronous online meetings) | 26.744 | 0.143 | 0.136 | 34.733 | 0.339 | 0.156 |
For the issues of instructors, the study intent was to discern how students rated the availability of instructors in cases where they needed help, and whether the instructors were able to provide clear guidance to students on how they can access the course material online. The distribution of student's ratings showed that the student preferred face-to-face meetings that online meetings with the instructors. The results were consistent across college level and college type as shown in Figs. 5 and and6 respectively 6 respectively under the “distance learning methods’ preference” subsection. From Table 6 , Significant variation of students’ ratings by college-level was observed when students were asked whether they disagree or disagree about the availability of instructors(? 2 =41.765, p=0.003), clear instruction provided by the instructors (? 2 =33.900, p=0.027) and methods of assessing students learning (? 2 =37.753, p=0.009). In both cases, the graduate students had a higher percentage of agreement with above-mentioned statements as shown in Fig. 5 . Significant variation of students’ ratings by college type was observed on the issues of instructors’ availability when students needed help (? 2 =51.197, p=0.017). The availability of instructors was highly rated by graduate college followed by the college of health and human services while poor ratings of instructors’ availability were observed in Haworth college of business. The observed variation by college type and college level on the issue of instructor availability offers WMU a clear spectrum of which colleges and students need special attention to improve the effectiveness of distance learning.
![Click on image to zoom Fig. 5](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr5_lrg.jpg)
Overall student's perception of instructors and instructions methods during the COVID-19 pandemic by college level,
![Click on image to zoom Fig. 6](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr6_lrg.jpg)
Overall student's perception of instructors and instructions methods during the COVID-19 pandemic by college type,
The study also examined the efficacy of distance learning tools such as WebEx, and Microsoft team from the students’ perceptive. Graduate students’ ratings of these tools were slightly higher than undergraduate level with 61% agreeing that distance learning effective and easy to use (68%) as shown in Fig. 5 under the “distance learning tool” subsection. The undergraduate student's rating leaned towards disagreement and neutrality. The distribution of ratings by college type showed a poor rating of the distance learning tools by the college of aviation followed by Haworth college of business.
Another interesting subject with was explored in this study was student's perspective of distance learning methods that were provided by WMU. The methods of learning that were examined include synchronous teaching method, asynchronous teaching method, hybrid method. Each method has its pros and cons. With synchronous learning methods, students learn and interact with instructors and classmates in real-time while asynchronous learning instructors provide all the necessary material, and students can read and complete assignments and exams in their own schedule. Students were asked to rate each of the above-mentioned learning methods. Students especially freshmen strongly preferred in-person or hybrid classes over online classes (? 2 =51.197, p=0.017). Also, there was a consensus among students that online classes were the preferable choice due to the COVID-19 crises. However, there was no apparent preference for the form of distance learning method. About 42% of students prefer asynchronous learning while only 29% of students preferred synchronous learning. The rest of the students either strongly disagree, disagree, or were neutral about the subject.
6.3. Textual exploratory analysis
An open-ended question was asked to students about the best and worse experiences of online learning. The question was specifically designed to discern other important concerns that were not covered in Likert-scale questions. A text mining approach was used to extract information from the students’ opinions. Fig. 7 shows the word network diagram showing the keywords that were used by students to articulate their experience of distance learning. Each word has been reduced to its root form through the process known as stemming. The most frequent pairs of words for the best experience of distance learning are “flexible location”, “flexible schedule”, “social distance”, “park pass”, among others. The most frequent pair of words that were used to describe the worse experience of distance learning include “human interact”, “due date”, “distance learn”, “real-time” and “class synchron”. The main themes that were prevalent in students’ comments about the worse distance learning experience are lack of human interaction, social connections, self-motivation, and concentration. Also, technological glitches such poor internet connections and students’ or instructors’ inexperience using online systems were mentioned by students.
![Click on image to zoom Fig. 7](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531333/bin/gr7_lrg.jpg)
Students’ experience of distance learning: Textual exploratory analysis,
7. Discussion
The results of this study are indicative of less positive perceptions of distance learning across college level and college type. Positive attitudes and a high level of satisfaction among all students are what designers and instructors of distance learning need to achieve. The results could provide a useful understanding of what brings about less positive student perceptions of distance learning. For instance, the less positive perceptions may be related to the type of distance learning methods or tools, or they could be linked to other different factors such as college level, college type, previous distance learning experience, and interaction with instructors and classmates. In this study, we found both the college level and college type significantly impacted students’ perceptions of distance learning on the seven defined scales. These two factors influence students’ perceptions and attitudes toward distance learning. Furthermore, all the participants were actively enrolled in a distance learning class at the time when they reported their perceptions, and that may have influenced their overall negative perception of distance learning.
The findings of the study that relate to the influence of college-level showed that most freshmen perceived a lack of interaction among students and instructors as the result of shifting to distance education during the pandemic. The effect was less severe to higher college level, especially graduate students. In the area of improvement in academic progress and success, most of the undergraduate students reported a more negative view than the graduate students. The undergraduate students’ academic progress and success were negatively affected by the transition to distance learning in terms of the extent to which: distance learning did not improve on-campus classes or instructions, students did not learn as much as they would have learned in in-person classes, distance learning did not improve their grades compared if the classes were done in-person. The impediment to academic progress brought by the pandemic has also been reported elsewhere in high education institutions ( Kummitha, Kolloju, Chittoor, & Madepalli, 2021 ; Pokhrel & Chhetri, 2021 ). Much of it has been attributed to a lack of institutional preparedness to cope with the unprecedented pandemic. Also, due to the lack of best of available information on best practices( Armstrong-Mensah, Ramsey-White, Yankey, & Self-Brown, 2020 ) an almost trial and error process of gauging and supporting students has been reported during the pandemic deterred the overall academic performance and progress.
On the other hand, students across the college level reported positive perceptions about the location and time flexibility of distance learning in class attendance and doing assignments. Specifically, distance learning flexibility was much appreciated by graduate students compared to undergraduates. The benefits of distance learning in terms of location and time flexibility have been widely reported in most of the Covid-19 related papers. The benefits include but are not limited to less commuting time, savings on gas, time management, and more time to spend with family members ( Almaiah, Al-Khasawneh, & Althunibat, 2020 ; Armstrong-Mensah et al., 2020 ). Increased flexibility has also been shown to enable independent learning among students ( Müller, Goh, Lim, & Gao, 2021 ).
In terms of reliable distance learning resources, most of the students reported having internet access and a computer or a device to use for distance learning. Only a small number of the students indicated that they lacked personal computers. Similar results were obtained by Armstrong-Mensah (2020) with the majority of students at Georgia State University reported having internet access and digital devices which support distance learning. However, other studies have reported the disparity in digital tools and internet access among students ( Coello, Salazar, & Taborda, 2020 ) Equitable access to the internet and other supporting tools is of paramount importance to students enrolled in distance learning. Each institution should aim at setting out measures that ensure the pandemic does not widen the digital divide between students
The finding that all the students reported a highly positive perception of the face-to-face meeting with instructors’ subscale is an important one that the instructors of distance learning classes need to consider. Similarly, a positive perception was reported by college levels in terms of the availability of instructors, clear instruction provided by the instructors, and methods of assessing students learning. The study also tested the efficiency of distance learning tools such as WebEx and Microsoft teams from the students’ perceptive. Graduate students reported high positive perception than undergraduate students on using and learning through these tools. The perception and acceptance of distance learning tools can be enhanced by training educators and students on the use of digital technology which has now become an integral part of higher education institutions and universities ( Coello et al., 2020 ; Lazarova, Miteva, & Zenku, 2020 ; Rashid & Yadav, 2020 ).
The findings of students’ perspective of distance learning methods that were provided by WMU showed that most of the students, especially the freshman reported a highly positive perception of preferring in-person or hybrid classes over online classes. The preference for hybrid or blended classes has also been reported elsewhere among educators and students ( Müller et al., 2021 ). It has been shown to provide a better understanding of the courses due to an increase in social interaction among peers and instructors( Kimkong & Koemhong, 2020 ). In the meantime, most of the students, especially the graduate students, reported a positive perception of the preference for online classes due to the COVID-19 crisis. However, there was no apparent preference for the form of distance learning method. Seniors and juniors reported more negative perceptions of the synchronous learning method than other college levels, while freshmen reported a highly negative perception of the asynchronous learning method than other students. Synchronous learning has been reported in previous studies to improve instructor-teacher interaction. A study by Müller et al (2021) reported an increased level of engagement among students in distance learning who were normally quiet during in-person classes. A continuous assessment of student readiness to various forms of online learning is needed based on equipment capability, technology skills, self-directed learning, motivation, and perceived usefulness (Widodo, 2020).
The findings of the study that rely on the influence of college type showed that the interaction with classmates was poorly rated by all colleges. However, the College of Aviation and College of Fine Arts reported a highly negative perspective comparing to other colleges. On the distance learning flexibility scale, most of the colleges, especially Haworth College of Business, positively rated the statement: “distance learning causes spending more time doing your work.” A highly positive rating on having internet access at home was reported by the College of Health and Human Services, followed by the College of Fine Arts. In addition, the availability of instructors was highly rated by Graduate College followed by College of Health and Human Services, while poor ratings of instructors’ availability were observed in Haworth College of Business. The issue of instructor availability offers WMU a clear spectrum of which college and students that need special attention to improve the effectiveness of distance learning. Conclusively, the distance learning tools were negatively rated by the College of Aviation followed by Haworth College of Business. The observed disparity in distance learning rating across college types emphasizes the key challenge of distance learning which is to create a holistic and inclusive learning experience that suffices the diverse student needs. These needs tend to vary mostly by college type or nature of the subjects ( Kimkong & Koemhong, 2020 ; Müller et al., 2021 ).
8. Conclusions
In just a few months, The COVID-19 pandemic, caused by the latest coronavirus, resulted in the sudden closure of the universities globally and moved face-to-face classes to distance or online learning, which changed the lives of masses across the globe, including higher education students. In this respect, we introduce this study to reveal students’ perspectives and understand their preferences and needs on distance learning at Western Michigan University (WMU). All students in all different colleges and departments were invited to participate in this study. The findings have important implications for distance learning educators and may help the top management of the university to assess distance learning and make future decisions to enhance the weakness of this type of learning.
Considering the present study, the findings could be split into instructor factors that influenced the experience and student factors that influenced the experience. The instructors need to implement strategies that are influenced by the college's level and type to address students’ needs for better instructions, a proper teaching method, a suitable grading schema to assess student work and comprehension, face-to-face interaction, small group discussion, collaborative projects, and group presentation. These strategies may help boost students’ achievement and overcome their difficulties with distance learning.
On the student side, the capacity to adjust to school and life, acceptance of personal responsibility, connection with peers, and time management skills are the most factors that influenced the student's experience.
Future studies could examine perceptions of distance learning at the departmental level. Generally, the findings and discussion of this study have important implications for future research. As the survey for this study was done during the pandemic's initial period, the finding is essential and points to the overall higher levels of awareness and comfortability with the distance learning among the students in general. So, studies could be established to determine whether WMU students’ perceptions of distance learning are affected by the impact of previous enrollment in distance learning courses comparing to the current study results. Finally, further research could be examined how students’ perceptions will change over academic years.
Conflict of Interest
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- Published: 25 January 2021
Online education in the post-COVID era
- Barbara B. Lockee 1
Nature Electronics volume 4 , pages 5–6 ( 2021 ) Cite this article
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The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make it work — could permanently change how education is delivered.
The COVID-19 pandemic has forced the world to engage in the ubiquitous use of virtual learning. And while online and distance learning has been used before to maintain continuity in education, such as in the aftermath of earthquakes 1 , the scale of the current crisis is unprecedented. Speculation has now also begun about what the lasting effects of this will be and what education may look like in the post-COVID era. For some, an immediate retreat to the traditions of the physical classroom is required. But for others, the forced shift to online education is a moment of change and a time to reimagine how education could be delivered 2 .
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Looking back
Online education has traditionally been viewed as an alternative pathway, one that is particularly well suited to adult learners seeking higher education opportunities. However, the emergence of the COVID-19 pandemic has required educators and students across all levels of education to adapt quickly to virtual courses. (The term ‘emergency remote teaching’ was coined in the early stages of the pandemic to describe the temporary nature of this transition 3 .) In some cases, instruction shifted online, then returned to the physical classroom, and then shifted back online due to further surges in the rate of infection. In other cases, instruction was offered using a combination of remote delivery and face-to-face: that is, students can attend online or in person (referred to as the HyFlex model 4 ). In either case, instructors just had to figure out how to make it work, considering the affordances and constraints of the specific learning environment to create learning experiences that were feasible and effective.
The use of varied delivery modes does, in fact, have a long history in education. Mechanical (and then later electronic) teaching machines have provided individualized learning programmes since the 1950s and the work of B. F. Skinner 5 , who proposed using technology to walk individual learners through carefully designed sequences of instruction with immediate feedback indicating the accuracy of their response. Skinner’s notions formed the first formalized representations of programmed learning, or ‘designed’ learning experiences. Then, in the 1960s, Fred Keller developed a personalized system of instruction 6 , in which students first read assigned course materials on their own, followed by one-on-one assessment sessions with a tutor, gaining permission to move ahead only after demonstrating mastery of the instructional material. Occasional class meetings were held to discuss concepts, answer questions and provide opportunities for social interaction. A personalized system of instruction was designed on the premise that initial engagement with content could be done independently, then discussed and applied in the social context of a classroom.
These predecessors to contemporary online education leveraged key principles of instructional design — the systematic process of applying psychological principles of human learning to the creation of effective instructional solutions — to consider which methods (and their corresponding learning environments) would effectively engage students to attain the targeted learning outcomes. In other words, they considered what choices about the planning and implementation of the learning experience can lead to student success. Such early educational innovations laid the groundwork for contemporary virtual learning, which itself incorporates a variety of instructional approaches and combinations of delivery modes.
Online learning and the pandemic
Fast forward to 2020, and various further educational innovations have occurred to make the universal adoption of remote learning a possibility. One key challenge is access. Here, extensive problems remain, including the lack of Internet connectivity in some locations, especially rural ones, and the competing needs among family members for the use of home technology. However, creative solutions have emerged to provide students and families with the facilities and resources needed to engage in and successfully complete coursework 7 . For example, school buses have been used to provide mobile hotspots, and class packets have been sent by mail and instructional presentations aired on local public broadcasting stations. The year 2020 has also seen increased availability and adoption of electronic resources and activities that can now be integrated into online learning experiences. Synchronous online conferencing systems, such as Zoom and Google Meet, have allowed experts from anywhere in the world to join online classrooms 8 and have allowed presentations to be recorded for individual learners to watch at a time most convenient for them. Furthermore, the importance of hands-on, experiential learning has led to innovations such as virtual field trips and virtual labs 9 . A capacity to serve learners of all ages has thus now been effectively established, and the next generation of online education can move from an enterprise that largely serves adult learners and higher education to one that increasingly serves younger learners, in primary and secondary education and from ages 5 to 18.
The COVID-19 pandemic is also likely to have a lasting effect on lesson design. The constraints of the pandemic provided an opportunity for educators to consider new strategies to teach targeted concepts. Though rethinking of instructional approaches was forced and hurried, the experience has served as a rare chance to reconsider strategies that best facilitate learning within the affordances and constraints of the online context. In particular, greater variance in teaching and learning activities will continue to question the importance of ‘seat time’ as the standard on which educational credits are based 10 — lengthy Zoom sessions are seldom instructionally necessary and are not aligned with the psychological principles of how humans learn. Interaction is important for learning but forced interactions among students for the sake of interaction is neither motivating nor beneficial.
While the blurring of the lines between traditional and distance education has been noted for several decades 11 , the pandemic has quickly advanced the erasure of these boundaries. Less single mode, more multi-mode (and thus more educator choices) is becoming the norm due to enhanced infrastructure and developed skill sets that allow people to move across different delivery systems 12 . The well-established best practices of hybrid or blended teaching and learning 13 have served as a guide for new combinations of instructional delivery that have developed in response to the shift to virtual learning. The use of multiple delivery modes is likely to remain, and will be a feature employed with learners of all ages 14 , 15 . Future iterations of online education will no longer be bound to the traditions of single teaching modes, as educators can support pedagogical approaches from a menu of instructional delivery options, a mix that has been supported by previous generations of online educators 16 .
Also significant are the changes to how learning outcomes are determined in online settings. Many educators have altered the ways in which student achievement is measured, eliminating assignments and changing assessment strategies altogether 17 . Such alterations include determining learning through strategies that leverage the online delivery mode, such as interactive discussions, student-led teaching and the use of games to increase motivation and attention. Specific changes that are likely to continue include flexible or extended deadlines for assignment completion 18 , more student choice regarding measures of learning, and more authentic experiences that involve the meaningful application of newly learned skills and knowledge 19 , for example, team-based projects that involve multiple creative and social media tools in support of collaborative problem solving.
In response to the COVID-19 pandemic, technological and administrative systems for implementing online learning, and the infrastructure that supports its access and delivery, had to adapt quickly. While access remains a significant issue for many, extensive resources have been allocated and processes developed to connect learners with course activities and materials, to facilitate communication between instructors and students, and to manage the administration of online learning. Paths for greater access and opportunities to online education have now been forged, and there is a clear route for the next generation of adopters of online education.
Before the pandemic, the primary purpose of distance and online education was providing access to instruction for those otherwise unable to participate in a traditional, place-based academic programme. As its purpose has shifted to supporting continuity of instruction, its audience, as well as the wider learning ecosystem, has changed. It will be interesting to see which aspects of emergency remote teaching remain in the next generation of education, when the threat of COVID-19 is no longer a factor. But online education will undoubtedly find new audiences. And the flexibility and learning possibilities that have emerged from necessity are likely to shift the expectations of students and educators, diminishing further the line between classroom-based instruction and virtual learning.
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Distance learning in higher education during COVID-19: The role of basic psychological needs and intrinsic motivation for persistence and procrastination–a multi-country study
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Affiliation Department of Developmental and Educational Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
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Affiliation Department of Mathematics, Faculty of Mathematics, University of Vienna, Vienna, Austria
Roles Conceptualization, Funding acquisition, Methodology, Writing – review & editing
Roles Conceptualization, Funding acquisition, Methodology
Affiliation Department of Psychology, Faculty of Education, Aleksandër Moisiu University, Durrës, Albania
Affiliation Department of Educational Sciences, Faculty of Philology and Education, Bedër University, Tirana, Albania
Affiliation Xiangya School of Nursing, Central South University, Changsha, China
Affiliations Xiangya School of Nursing, Central South University, Changsha, China, Department of Nursing Science, University of Turku, Turku, Finland
Affiliation Study of Nursing, University of Applied Sciences Bjelovar, Bjelovar, Croatia
Affiliation Baltic Film, Media and Arts School, Tallinn University, Tallinn, Estonia
Affiliation Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
Affiliation Department of Psychology, University of Bonn, Bonn, Germany
Affiliation Chair of Educational Psychology, Technische Universität Berlin, Berlin, Germany
Affiliation Department of Educational Studies, University of Potsdam, Potsdam, Germany
Affiliation Faculty of Education, University of Akureyri, Akureyri, Iceland
Affiliation Department of Global Education, Tsuru University, Tsuru, Japan
Affiliation Career Center, Osaka University, Osaka University, Suita, Japan
Affiliation Graduate School of Education, Osaka Kyoiku University, Kashiwara, Japan
Affiliation Department of Psychology, Faculty of Philosophy, University of Prishtina ’Hasan Prishtina’, Pristina, Kosovo
Affiliation Department of Social Work, Faculty of Philosophy, University of Pristina ’Hasan Prishtina’, Pristina, Kosovo
Affiliation Department of Psychology, Faculty of Social Sciences and Humanities, Klaipėda University, Klaipėda, Lithuania
Affiliation Geography Department, Junior College, University of Malta, Msida, Malta
Affiliation Institute of Family Studies, Faculty of Philosophy, Ss. Cyril and Methodius University in Skopje, Skopje, North Macedonia
Affiliation Institute of Psychology, Faculty of Social Science, University of Gdańsk, Gdańsk, Poland
Affiliation Faculty of Historical and Pedagogical Sciences, University of Wrocław, Wrocław, Poland
Affiliation Faculty of Educational Studies, Adam Mickiewicz University, Poznań, Poland
Affiliation CERNESIM Environmental Research Center, Alexandru Ioan Cuza University, Iași, România
Affiliation Social Sciences and Humanities Research Department, Institute for Interdisciplinary Research, Alexandru Ioan Cuza University of Iași, Iași, România
Affiliation Department of Informatics, Örebro University School of Business, Örebro University, Örebro, Sweden
Affiliation Faculty of Social Studies, Penn State University, State College, Pennsylvania, United States of America
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Affiliations Department of Developmental and Educational Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria, Department for Teacher Education, Centre for Teacher Education, University of Vienna, Vienna, Austria
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- Elisabeth R. Pelikan,
- Selma Korlat,
- Julia Reiter,
- Julia Holzer,
- Martin Mayerhofer,
- Barbara Schober,
- Christiane Spiel,
- Oriola Hamzallari,
- Ana Uka,
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Due to the COVID-19 pandemic, higher educational institutions worldwide switched to emergency distance learning in early 2020. The less structured environment of distance learning forced students to regulate their learning and motivation more independently. According to self-determination theory (SDT), satisfaction of the three basic psychological needs for autonomy, competence and social relatedness affects intrinsic motivation, which in turn relates to more active or passive learning behavior. As the social context plays a major role for basic need satisfaction, distance learning may impair basic need satisfaction and thus intrinsic motivation and learning behavior. The aim of this study was to investigate the relationship between basic need satisfaction and procrastination and persistence in the context of emergency distance learning during the COVID-19 pandemic in a cross-sectional study. We also investigated the mediating role of intrinsic motivation in this relationship. Furthermore, to test the universal importance of SDT for intrinsic motivation and learning behavior under these circumstances in different countries, we collected data in Europe, Asia and North America. A total of N = 15,462 participants from Albania, Austria, China, Croatia, Estonia, Finland, Germany, Iceland, Japan, Kosovo, Lithuania, Poland, Malta, North Macedonia, Romania, Sweden, and the US answered questions regarding perceived competence, autonomy, social relatedness, intrinsic motivation, procrastination, persistence, and sociodemographic background. Our results support SDT’s claim of universality regarding the relation between basic psychological need fulfilment, intrinsic motivation, procrastination, and persistence. However, whereas perceived competence had the highest direct effect on procrastination and persistence, social relatedness was mainly influential via intrinsic motivation.
Citation: Pelikan ER, Korlat S, Reiter J, Holzer J, Mayerhofer M, Schober B, et al. (2021) Distance learning in higher education during COVID-19: The role of basic psychological needs and intrinsic motivation for persistence and procrastination–a multi-country study. PLoS ONE 16(10): e0257346. https://doi.org/10.1371/journal.pone.0257346
Editor: Shah Md Atiqul Haq, Shahjalal University of Science and Technology, BANGLADESH
Received: March 30, 2021; Accepted: August 29, 2021; Published: October 6, 2021
Copyright: © 2021 Pelikan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Data is now publicly available: Pelikan ER, Korlat S, Reiter J, Lüftenegger M. Distance Learning in Higher Education During COVID-19: Basic Psychological Needs and Intrinsic Motivation 2021. doi: 10.17605/OSF.IO/8CZX3 .
Funding: This work was funded by the Vienna Science and Technology Fund (WWTF) [ https://www.wwtf.at/ ] and the MEGA Bildungsstiftung [ https://www.megabildung.at/ ] through project COV20-025, as well as the Academy of Finland [ https://www.aka.fi ] through project 308351, 336138, and 345117. BS is the grant recipient of COV20-025. KSA is the grant recipient of 308351, 336138, and 345117. Open access funding was provided by University of Vienna. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
In early 2020, countries across the world faced rising COVID-19 infection rates, and various physical and social distancing measures to contain the spread of the virus were adopted, including curfews and closures of businesses, schools, and universities. By the end of April 2020, roughly 1.3 billion learners were affected by the closure of educational institutions [ 1 ]. At universities, instruction was urgently switched to distance learning, bearing challenges for all actors involved, particularly for students [ 2 ]. Moreover, since distance teaching requires ample preparation time and situation-specific didactic adaptation to be successful, previously established concepts for and research findings on distance learning cannot be applied undifferentiated to the emergency distance learning situation at hand [ 3 ].
Generally, it has been shown that the less structured learning environment in distance learning requires students to regulate their learning and motivation more independently [ 4 ]. In distance learning in particular, high intrinsic motivation has proven to be decisive for learning success, whereas low intrinsic motivation may lead to maladaptive behavior like procrastination (delaying an intended course of action despite negative consequences) [ 5 , 6 ]. According to self-determination theory (SDT), satisfaction of the three basic psychological needs for autonomy, competence and social relatedness leads to higher intrinsic motivation [ 7 ], which in turn promotes adaptive patterns of learning behavior. On the other hand, dissatisfaction of these basic psychological needs can detrimentally affect intrinsic motivation. According to SDT, satisfaction of the basic psychological needs occurs in interaction with the social environment. The context in which learning takes place as well as the support of social interactions it encompasses play a major role for basic need satisfaction [ 7 , 8 ]. Distance learning, particularly when it occurs simultaneously with other physical and social distancing measures, may impair basic need satisfaction and, in consequence, intrinsic motivation and learning behavior.
The aim of this study was to investigate the relationship between basic need satisfaction and two important learning behaviors—procrastination (as a consequence of low or absent intrinsic motivation) and persistence (as the volitional implementation of motivation)—in the context of emergency distance learning during the COVID-19 pandemic. In line with SDT [ 7 ] and previous studies (e.g., [ 9 ]), we also investigated the mediating role of intrinsic motivation in this relationship. Furthermore, to test the universal importance of SDT for intrinsic motivation and learning behavior under these specific circumstances, we collected data in 17 countries in Europe, Asia, and North America.
The fundamental role of basic psychological needs for intrinsic motivation and learning behavior
SDT [ 7 ] provides a broad framework for understanding human motivation, proposing that the three basic psychological needs for autonomy, competence, and social relatedness must be satisfied for optimal functioning and intrinsic motivation. The need for autonomy refers to an internal perceived locus of control and a sense of agency. In an academic context, students who learn autonomously feel that they have an active choice in shaping their learning process. The need for competence refers to the feeling of being effective in one’s actions. In addition, students who perceive themselves as competent feel that they can successfully meet challenges and accomplish the tasks they are given. Finally, the need for social relatedness refers to feeling connected to and accepted by others. SDT proposes that the satisfaction of each of these three basic needs uniquely contributes to intrinsic motivation, a claim that has been proved in numerous studies and in various learning contexts. For example, Martinek and colleagues [ 10 ] found that autonomy satisfaction was positively whereas autonomy frustration was negatively related to intrinsic motivation in a sample of university students during COVID-19. The same held true for competence satisfaction and dissatisfaction. A recent study compared secondary school students who perceived themselves as highly competent in dealing with their school-related tasks during pandemic-induced distance learning to those who perceived themselves as low in competence [ 11 ]. Students with high perceived competence not only reported higher intrinsic motivation but also implemented more self-regulated learning strategies (such as goal setting, planning, time management and metacognitive strategies) and procrastinated less than students who perceived themselves as low in competence. Of the three basic psychological needs, the findings on the influence of social relatedness on intrinsic motivation have been most ambiguous. While in some studies, social relatedness enhanced intrinsic motivation (e.g., [ 12 ]), others could not establish a clear connection (e.g., [ 13 ]).
Intrinsic motivation, in turn, is regarded as particularly important for learning behavior and success (e.g., [ 6 , 14 ]). For example, students with higher intrinsic motivation tend to engage more in learning activities [ 9 , 15 ], show higher persistence [ 16 ] and procrastinate less [ 6 , 17 , 18 ]. Notably, intrinsic motivation is considered to be particularly important in distance learning, where students have to regulate their learning themselves. Distance-learning students not only have to consciously decide to engage in learning behavior but also persist despite manifold distractions and less external regulation [ 4 ].
Previous research also indicates that the satisfaction of each basic need uniquely contributes to the regulation of learning behavior [ 19 ]. Indeed, studies have shown a positive relationship between persistence and the three basic needs (autonomy [ 20 ]; competence [ 21 ]; social relatedness [ 22 ]). Furthermore, all three basic psychological needs have been found to be related to procrastination. In previous research with undergraduate students, autonomy-supportive teaching behavior was positively related to satisfaction of the needs for autonomy and competence, both of which led to less procrastination [ 23 ]. A qualitative study by Klingsieck and colleagues [ 18 ] supports the findings of previous studies on the relations of perceived competence and autonomy with procrastination, but additionally suggests a lack of social relatedness as a contributing factor to procrastination. Haghbin and colleagues [ 24 ] likewise found that people with low perceived competence avoided challenging tasks and procrastinated.
SDT has been applied in research across various contexts, including work (e.g., [ 25 ]), health (e.g., [ 26 ]), everyday life (e.g., [ 27 ]) and education (e.g., [ 15 , 28 ]). Moreover, the pivotal role of the three basic psychological needs for learning outcomes and functioning has been shown across multiple countries, including collectivistic as well as individualistic cultures (e.g., [ 29 , 30 ]), leading to the conclusion that satisfaction of the three basic needs is a fundamental and universal determinant of human motivation and consequently learning success [ 31 ].
Self-determination theory in a distance learning setting during COVID-19
As Chen and Jang [ 28 ] observed, SDT lends itself particularly well to investigating distance learning, as the three basic needs for autonomy, competence and social relatedness all relate to important aspects of distance learning. For example, distance learning usually offers students greater freedom in deciding where and when they want to learn [ 32 ]. This may provide students with a sense of agency over their learning, leading to increased perceived autonomy. At the same time, it requires students to regulate their motivation and learning more independently [ 4 ]. In the unique context of distance learning during COVID-19, it should be noted that students could not choose whether and to what extent to engage in distance learning, but had to comply with external stipulations, which in turn may have had a negative effect on perceived autonomy. Furthermore, distance learning may also influence perceived competence, as this is in part developed by receiving explicit or implicit feedback from teachers and peers [ 33 ]. Implicit feedback in particular may be harder to receive in a distance learning setting, where informal discussions and social cues are largely absent. The lack of face-to-face contact may also impede social relatedness between students and their peers as well as students and their teachers. Well-established communication practices are crucial for distance learning success (see [ 34 ] for an overview). However, providing a nurturing social context requires additional effort and guidance from teachers, which in turn necessitates sufficient skills and preparation on their part [ 34 , 35 ]. Moreover, the sudden switch to distance learning due to COVID-19 did not leave teachers and students time to gradually adjust to the new learning situation [ 36 ]. As intrinsic motivation is considered particularly relevant in the context of distance education [ 28 , 37 ], applying the SDT framework to the novel situation of pandemic-induced distance learning may lead to important insights that allow for informed recommendations for teachers and educational institutions about how to proceed in the context of continued distance teaching and learning.
In summary, the COVID-19 situation is a completely new environment, and basic need satisfaction during learning under pandemic-induced conditions has not been explored before. Considering that closures of educational institutions have affected billions of students worldwide and have been strongly debated in some countries, it seems particularly relevant to gain insights into which factors consistently influence conducive or maladaptive learning behavior in these circumstances in a wide range of countries and contextual settings.
Therefore, the overall goal of this study is to investigate the well-established relationship between the three basic needs for autonomy, competence, and social relatedness with intrinsic motivation in the new and specific situation of pandemic-induced distance learning. Firstly, we examine the relationship between each of the basic needs with intrinsic motivation. We expect that perceived satisfaction of the basic needs for autonomy (H1a), competence (H1b) and social relatedness (H1c) would be positively related to intrinsic motivation. In our second research question, we furthermore extend SDT’s predictions regarding two important aspects of learning behavior–procrastination (as a consequence of low or absent intrinsic motivation) and persistence (as the implementation of the volitional part of motivation) and hypothesize that each basic need will be positively related to persistence and negatively related to procrastination, both directly (procrastination: H2a –c; persistence: H3a –c) and mediated by intrinsic motivation (procrastination: H4a –c; persistence: H5a –c). We also proposed that perceived autonomy, competence, and social relatedness would have a direct negative relation with procrastination (H6a –c) and a direct positive relation with persistence (H7a –c). Finally, we investigate SDT’s claim of universality, and assume that the aforementioned relationships will emerge across countries we therefore expect a similar pattern of results in all observed countries (H8a –c). As previous studies have indicated that gender [ 4 , 17 , 38 ] and age [ 39 , 40 ]. May influence intrinsic motivation, persistence, and procrastination, we included participants’ gender and age as control variables.
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Study design
Due to the circumstances, we opted for a cross-sectional study design across multiple countries, conducted as an online survey. We decided for an online-design due to the pandemic-related restrictions on physical contact with potential survey participants as well as due to the potential to reach a larger audience. As we were interested in the current situation in schools than in long-term development, and we were particularly interested in a large-scale section of the population in multiple countries, we decided on a cross-sectional design. In addition, a multi-country design is particularly interesting in a pandemic setting: During this global health crisis, educational institutions in all countries face the same challenge (to provide distance learning in a way that allows students to succeed) but do so within different frameworks depending on the specific measures each country has implemented. This provides a unique basis for comparing the effects of need fulfillment on students’ learning behavior cross-nationally, thus testing the universality of SDT.
Sample and procedure
The study was carried out across 17 countries, with central coordination taking place in Austria. It was approved and supported by the Austrian Federal Ministry of Education, Science and Research and conducted online. International cooperation partners were recruited from previously established research networks (e.g., European Family Support Network [COST Action 18123]; Transnational Collaboration on Bullying, Migration and Integration at School Level [COST Action 18115]; International Panel on Social), resulting in data collection in 16 countries (Albania, China, Croatia, Estonia, Finland, Germany, Iceland, Japan, Kosovo, Lithuania, Poland, Malta, North Macedonia, Romania, Sweden, USA) in addition to Austria. Data collection was carried out between April and August 2020. During this period, all participating countries were in some degree of pandemic-induced lockdown, which resulted in universities temporarily switching to distance learning. The online questionnaires were distributed among university students via online surveys by the research groups in each respective country. No restrictions were placed on participation other than being enrolled at a university in the sampling country. Participants were informed about the goals of the study, expected time it would take to fill out the questionnaire, voluntariness of participation and anonymity of the acquired data. All research partners ensured that all ethical and legal requirements related to data collection in their country context were met.
Only data from students who gave their written consent to participate, had reached the age of majority (18 or older) and filled out all questions regarding the study’s main variables were included in the analyses (for details on data cleaning rules and exclusion criteria, see [ 41 ]). Additional information on data collection in the various countries is provided in S1 Table in S1 File .
The overall sample of N = 15,462 students was predominantly female (71.7%, 27.4% male and 0.7% diverse) and ranged from 18 to 71 years, with the average participant age being 24.41 years ( SD = 6.93, Mdn = 22.00). Sample descriptives per country are presented in Table 1 .
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https://doi.org/10.1371/journal.pone.0257346.t001
The variables analyzed here were part of a more extensive questionnaire; the complete questionnaire, as well as the analysis code and the data set, can be found at OSF [ 42 ] In order to take the unique situation into account, existing scales were adapted to the current pandemic context (e.g., adding “In the current home-learning situation …”), and supplemented with a small number of newly developed items. Subsequently, the survey was revised based on expert judgements from our research group and piloted with cognitive interview testing. The items were sent to the research partners in English and translated separately by each respective research team either using the translation-back-translation method or by at least two native-speaking experts. Subsequently, any differences were discussed, and a consolidated version was established.
To assure the reliability of the scales, we analyzed them using alpha coefficients separately for each country (see S2–S18 Tables in S1 File ). All items were answered on a rating scale from 1 (= strongly agree) to 5 (= strongly disagree) and students were instructed to answer with regard to the current situation (distance learning during the COVID-19 lockdown). Analyses were conducted with recoded items so that higher values reflected higher agreement with the statements.
Perceived autonomy was measured with two newly constructed items (“Currently, I can define my own areas of focus in my studies” and “Currently, I can perform tasks in the way that best suits me”; average α = .78, ranging from .62 to .86).
Perceived competence was measured with three items, which were constructed based on the Work-related Basic Need Satisfaction Scale (W-BNS; [ 25 ]) and transferred to the learning context (“Currently, I am dealing well with the demands of my studies”, “Currently, I have no doubts about whether I am capable of doing well in my studies” and “Currently, I am managing to make progress in studying for university”; average α = .83, ranging from .74 to .91).
Perceived social relatedness was assessed with three items, based on the W-BNS [ 43 ], (“Currently, I feel connected with my fellow students”, “Currently, I feel supported by my fellow students”) and the German Basic Psychological Need Satisfaction and Frustration Scale [ 44 ]; “Currently, I feel connected with the people who are important to me (family, friends)”; average α = .73, ranging from .64 to .88).
Intrinsic motivation was measured with three items which were slightly adapted from the Scales for the Measurement of Motivational Regulation for Learning in University Students (SMR-LS; [ 45 ]; “Currently, doing work for university is really fun”, “Currently, I am really enjoying studying and doing work for university” and “Currently, I find studying for university really exciting”; average α = .91, ranging from .83 to .94).
Procrastination was measured with three items adapted from the Procrastination Questionnaire for Students (Prokrastinationsfragebogen für Studierende; PFS; [ 46 ]): “In the current home-learning situation, I postpone tasks until the last minute”, “In the current home-learning situation, I often do not manage to start a task when I set out to do so”, and “In the current home-learning situation, I only start working on a task when I really need to”; average α = .88, ranging from .74 to .91).
Persistence was measured with three items adapted from the EPOCH measure [ 47 ]: “In the current home-learning situation, I finish whatever task I begin”, “In the current home-learning situation, I keep at my tasks until I am done with them” and “In the current home-learning situation, once I make a plan to study, I stick to it”; average α = .81, ranging from .74 to .88).
Data analysis.
Data analyses were conducted using IBM SPSS version 26.0 and Mplus version 8.4. First, we tested for measurement invariance between countries prior to any substantial analyses. We conducted a multigroup confirmatory factor analysis (CFAs) for all scales individually to test for configural, metric, and scalar invariance [ 48 , 49 ] (see S19 Table in S1 File ). We used maximum likelihood parameter estimates with robust standard errors (MLR) to deal with the non-normality of the data. CFI and RMSEA were used as indicators for absolute goodness of model fit. In line with Hu and Bentler [ 50 ], the following cutoff scores were considered to reflect excellent and adequate fit to the data, respectively: (a) CFI > 0.95 and CFI > 0.90; (b) RMSEA < .06 and RMSEA < .08. Relative model fit was assessed by comparing BICs of the nested models, with smaller BIC values indicating a better trade-off between model fit and model complexity [ 51 ]. Configural invariance indicates a factor structure that is universally applicable to all subgroups in the analysis, metric invariance implies that participants across all groups attribute the same meaning to the latent constructs measured, and scalar invariance indicates that participants across groups attribute the same meaning to the levels of the individual items [ 51 ]. Consequently, the extent to which the results can be interpreted depends on the level of measurement invariance that can be established.
For the main analyses, three latent multiple group mediation models were computed, each including one of the basic psychological needs as a predictor, intrinsic motivation as the mediator and procrastination and persistence as the outcomes. These three models served to test the hypothesis that perceived autonomy, competence and social relatedness are related to levels of procrastination and persistence, both directly and mediated through intrinsic motivation. We used bootstrapping in order to provide analyses robust to non-normal distribution variations, specifying 5,000 bootstrap iterations [ 52 ]. Results were estimated using the maximum likelihood (ML) method. Bias-corrected bootstrap confidence intervals are reported.
Finally, in an exploratory step, we investigated the international applicability of the direct and mediated effects. To this end, an additional set of latent mediation models was computed where the path estimates were fixed in order to create an average model across all countries. This was prompted by the consistent patterns of results across countries we observed in the multigroup analyses. Model fit indices of these average models were compared to those of the multigroup models in order to establish the similarity of path coefficients between countries.
Statistical prerequisites
Table 2 provides overall descriptive statistics and correlations for all variables (see S2–S18 Tables in S1 File for descriptive statistics for the individual countries).
https://doi.org/10.1371/journal.pone.0257346.t002
Metric measurement variance, but not scalar measurement invariance could be established for a simple model including the three individual items and no inter-correlations between perceived competence, perceived social relatedness, intrinsic motivation, and procrastination. For these four variables, the metric invariance model had a good absolute fit, whereas the scalar model did not, due to too high RMSEA; moreover, the relative fit was best for the metric model compared to both the configural and scalar model (see S18 Table in S1 File ). Metric, but not scalar invariance could also be established for persistence after modelling residual correlations between items 1 and 2 and items 2 and 3 of the scale. This was necessary due to the similar wording of the items (see “Measures” section for item wordings). Consequently, the same residual correlations were incorporated into all mediation models.
Finally, as the perceived autonomy scale consisted of only two items, it had to be fitted in a model with a correlating factor in order to compute measurement invariance. Both perceived competence and perceived social relatedness were correlated with perceived autonomy ( r = .59** and r = .31**, respectively; see Table 2 ). Therefore, we fit two models combining perceived autonomy with each of these factors; in both cases, metric measurement invariance was established (see S19 Table in S1 File ).
In summary, these results suggest that the meaning of all constructs we aimed to measure was understood similarly by participants across different countries. Consequently, we were able to fit the same mediation model in all countries and compare the resulting path coefficients.
Both gender and age were statistically significantly correlated with perceived competence, perceived social relatedness, intrinsic motivation, procrastination, and persistence (see S20–S22 Tables in S1 File ).
Mediation analyses
Autonomy hypothesis..
We hypothesized that higher perceived autonomy would relate to less procrastination and more persistence, both directly and indirectly (mediated through intrinsic learning motivation). Indeed, perceived autonomy was related negatively to procrastination (H6a) in most countries. Confidence intervals did not include zero in 10 out of 17 countries, all effect estimates were negative and standardized effect estimates ranged from b stand = - .02 to -.46 (see Fig 1 ). Furthermore, perceived autonomy was directly positively related to persistence in most countries. Specifically, for the direct effect of perceived autonomy on persistence (H7a), all but one country (USA, b stand = -.02; p = .621; CI [-.13, .08]) exhibited distinctly positive effect estimates ranging from b stand = .18 to .72 and confidence intervals that did not include zero.
Countries are ordered by sample size from top (highest) to bottom (lowest).
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In terms of indirect effects of perceived autonomy on procrastination mediated by intrinsic motivation (H7a), confidence intervals did not include zero in 8 out of 17 countries and effect estimates were mostly negative, ranging from b stand = -.33 to .03. Indirect effects of perceived autonomy on persistence (mediated by intrinsic motivation; H5a) were distinctly positive and confidence intervals did not include zero in 12 out of 17 countries. The indirect effect estimates and confidence intervals for all remaining countries were consistently positive, with the standardized effect estimates ranging from b stand = .13 to .39, indicating a robust, positive mediated effect of autonomy on persistence. Fig 2 displays the unstandardized path coefficients and their two-sided 5% confidence intervals for the indirect effects of perceived autonomy on procrastination via intrinsic motivation (left) and of perceived autonomy on persistence via intrinsic motivation (right).
https://doi.org/10.1371/journal.pone.0257346.g002
Unstandardized and standardized path coefficients, standard errors, p-values and bias-corrected bootstrapped confidence intervals for the direct and indirect effects of perceived autonomy on procrastination and persistence for each country are provided in S23–S26 Tables in S1 File , respectively.
Competence hypothesis. Secondly, we hypothesized that higher perceived competence would relate to less procrastination and more persistence both directly and indirectly, mediated through intrinsic learning motivation. Direct effects on procrastination (H6b) were negative in most countries and confidence intervals did not include zero in 10 out of 17 countries (see Fig 3 ).
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Standardized effect estimates ranged from b stand = -.02 to -.60, with 10 out of 17 countries exhibiting at least a medium-sized effect. Correspondingly, effect estimates for the direct effects on persistence were positive everywhere except the USA and confidence intervals did not include zero in 14 out of 17 countries (see Fig 3 ). Standardized effect estimates ranged from b stand = -.05 to .64 with 14 out of 17 countries displaying an at least medium-sized positive effect.
The pattern of results for the indirect effects of perceived competence on procrastination mediated by learning motivation (H4b) is illustrated in Fig 4 : Effect estimates were negative with the exception of China and the USA. Confidence intervals did not include zero in 7 out of 17 countries. Standardized effect estimates range between b stand = .06 and -.46. Indirect effects of perceived competence on persistence were positive everywhere except for two countries and confidence intervals did not include zero in 7 out of 17 countries (see Fig 4 ). Standardized effect estimates varied between b stand = -.07 and .46 (see S23–S26 Tables in S1 File for unstandardized and standardized path coefficients).
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Social relatedness hypothesis.
Finally, we hypothesized that stronger perceived social relatedness would be both directly and indirectly (mediated through intrinsic learning motivation) related to less procrastination and more persistence. The pattern of results was more ambiguous here than for perceived autonomy and perceived competence. Direct effect estimates on procrastination (H6c) were negative in 12 countries; however, the confidence intervals included zero in 12 out of 17 countries (see Fig 5 ). Standardized effect estimates ranged from b stand = -.01 to b stand = .33. The direct relation between perceived social relatedness and persistence (H7c) yielded 14 negative and three positive effect estimates. Confidence intervals did not include zero in 7 out of 17 countries (see Fig 5 ), with standardized effect estimates ranging from b stand = -.01 to b stand = .31.
https://doi.org/10.1371/journal.pone.0257346.g005
In terms of indirect effects of perceived social relatedness being related to procrastination mediated by intrinsic motivation (H4c), the pattern of results was consistent: All effect estimates except those for the USA were clearly negative, and confidence intervals did not include zero in 15 out of 17 countries (see Fig 6 ). Standardized effect estimates ranged between b stand = .00 and b stand = -.46. Indirect paths of perceived social relatedness on persistence showed positive effect estimates and standardized effect estimates ranging from b stand = .00 to .44 and confidence intervals not including zero in 16 out of 17 countries (see Fig 6 ; see S23–S26 Tables in S1 File for unstandardized and standardized path coefficients).
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Meta-analytic approach
Due to the overall similarity of the results across many countries, we decided to compute, in an additional, exploratory step, the same models with path estimates fixed across countries. This resulted in three models with average path estimates across the entire sample. Standardized path coefficients for the direct and indirect effects of the basic psychological needs on procrastination and persistence are presented in S27 and S28 Tables in S1 File , respectively. We compared the model fits of these three average models to those of the multigroup mediation models: If the fit of the average model is better than that of the multigroup model, it indicates that the individual countries are similar enough to be combined into one model. The amount of explained variance per model, outcome variable and country are provided in S29 Table in S1 File for procrastination and S30 Table in S1 File for persistence.
Perceived autonomy.
Relative model fit was better for the perceived autonomy model with fixed paths (BIC = 432,707.89) compared to the multigroup model (BIC = 432,799.01). Absolute model fit was equally good in the multigroup model (RMSEA = 0.05, CFI = 0.98, TLI = 0.97) and in the fixed path model (RMSEA = 0.05, CFI = 0.97, TLI = 0.97). Consequently, the general model in Fig 7 describes the data from all 17 countries equally well. The average amount of explained variance, however, is slightly higher in the multigroup model, with 19.9% of the variance in procrastination and 33.7% of the variance in persistence explained, as compared to 18.3% and 27.6% in the fixed path model. The amount of variance explained increased substantially in some countries when fixing the paths: in the multigroup model, explained variance ranges from 2.2% to 44.4% for procrastination and from 0.9% to 69.9% for persistence, compared to 13.0% - 27.7% and 18.2% to 63.2% in the fixed path model. Notably, the amount of variance explained did not change much in the three countries with the largest samples, Austria, Sweden, and Finland; countries with much smaller samples and larger confidence intervals were more affected.
*** p = < .001.
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Overall, perceived autonomy had significant direct and indirect effects on both procrastination and persistence; higher perceived autonomy was related to less procrastination directly ( b unstand = -.27, SE = .02, p = < .001) and mediated by learning motivation ( b unstand = -.20, SE = .01, p = < .001) and to more persistence directly ( b unstand = .24, SE = .01, p = < .001) and mediated by learning motivation ( b unstand = .12, SE = .01, p = < .001). Direct effects for the autonomy model are shown in Fig 7 ; for the indirect effects see Table 3 .
https://doi.org/10.1371/journal.pone.0257346.t003
Effects of age and gender varied across countries (see S20 Table in S1 File ).
Perceived competence.
For the perceived competence model, relative fit decreased when fixing the path coefficient estimates (BIC = 465,830.44 to BIC = 466,020.70). The absolute fit indices were also better for the multigroup model (RMSEA = 0.05, CFI = 0.97, TLI = 0.96) than for the fixed path model (RMSEA = 0.06, CFI = 0.96, TLI = 0.96). Hence, multigroup modelling describes the data across all countries somewhat better than a fixed path model as depicted in Fig 8 . Correspondingly, the fixed path model explained less variance on average than did the multigroup model, with 23.2% instead of 24.3% of the variance in procrastination and 32.9% instead of 37.3% of the variance in persistence explained. Explained variance ranged from 1.0% to 51.9% for procrastination in the multigroup model, as compared to 13.9% - 34.4% in the fixed path model. The amount of variance in persistence explained ranged from 1.0% to 58.1% in the multigroup model and from 23.5% to 55.9% in the fixed path model (see S29 and S30 Tables in S1 File ).
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Overall, higher perceived competence was related to less procrastination ( b unstand = -.44, SE = .02, p = < .001) and to higher persistence ( b unstand = .32, SE = .01, p = < .001). These effects were partly mediated by intrinsic learning motivation ( b unstand = -.11, SE = .01, p = < .001, and b unstand = .07, SE = .01, p = < .001, respectively; see Table 3 ). Effects of gender and age varied between countries, see S21 Table in S1 File .
Perceived social relatedness.
Finally, the perceived social relatedness model with fixed paths had a relatively better model fit (BIC = 479,428.46) than the multigroup model (BIC = 479,604.61). Likewise, the absolute model fit was similar in the model with path coefficients fixed across countries (RMSEA = 0.05, CFI = 0.97, TLI = 0.96) and the multigroup model (RMSEA = 0.05, CFI = 0.97, TLI = 0.97). The multigroup model explained 17.6% of the variance in procrastination and 26.3% of the variance in persistence, as compared to 15.2% and 21.6%, respectively in the fixed path model. Explained variance for procrastination ranged between 0.5% and 48.1% in the multigroup model, and from 9.0% to 23.0% in the fixed path model. Similarly, the multigroup model explained between 1.0% and 56.5% of the variance in persistence across countries, while the fixed path model explained between 15.6% and 48.3% (see S29 and S30 Tables in S1 File ).
Hence, the fixed path model depicted in Fig 9 is well-suited for describing data across all 17 countries. Higher perceived social relatedness is related to less procrastination both directly ( b unstand = -.06, SE = .01, p = < .001) and indirectly through learning motivation ( b unstand = -.12, SE = .01, p = < .001). Likewise, it is related to higher persistence both directly ( b unstand = .07, SE = .01, p = < .001) and indirectly through learning motivation ( b unstand = .08, SE = .00, p = < .001; see Table 3 ). Effects of gender and age are shown in S22 Table in S1 File .
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The aim of this study was to extend current research on the association between the basic psychological needs for autonomy, competence, and social relatedness with intrinsic motivation and two important aspects of learning behavior—procrastination and persistence—in the new and unique situation of pandemic-induced distance learning. We also investigated SDT’s [ 7 ] postulate that the relation between basic psychological need satisfaction and active (persistence) as well as passive (procrastination) learning behavior is mediated by intrinsic motivation. To test the theory’s underlying claim of universality, we collected data from N = 15,462 students across 17 countries in Europe, Asia, and North America.
Confirming our hypothesis, we found that the three basic psychological needs were consistently and positively related to intrinsic motivation in all countries except for the USA (H1a - c). This consistent result is in line with self-determination theory [ 7 ] and other previous studies (e.g., 9), which have found that satisfaction of the three basic needs for autonomy, competence and social relatedness is related to higher intrinsic motivation. Notably, the association with intrinsic motivation was stronger for perceived autonomy and perceived competence than for perceived social relatedness. This also has been found in previous studies [ 4 , 9 , 28 ]. Pandemic-induced distance learning, where physical and subsequential social contact in all areas of life was severely constricted, might further exacerbate this discrepancy, as instructors may have not been able to establish adequate communication structures due to the rapid switch to distance learning [ 36 , 53 ]. As hypothesized, intrinsic motivation was in general negatively related to procrastination (H2a - c) and positively related to persistence (H3a - c), indicating that students who are intrinsically motivated are less prone to procrastination and more persistent when studying. This again underlines the importance of intrinsic motivation for adaptive learning behavior, even and particularly in a distance learning setting, where students are more prone to disengage from classes [ 34 ].
The mediating effect of intrinsic motivation on procrastination and persistence
Direct effects of the basic needs on the outcomes were consistently more ambiguous (with smaller effect estimates and larger confidence intervals, including zero in more countries) than indirect effects mediated by intrinsic motivation. This difference was particularly pronounced for perceived social relatedness, where a clear negative direct effect on procrastination (H6c) could be observed only in the three countries with the largest sample size (Austria, Sweden, Finland) and Romania, whereas the confidence interval in most countries included zero. Moreover, in Estonia there was even a clear positive effect. The unexpected effect in the Estonian sample may be attributed to the fact that this country collected data only from international exchange students. Since the lockdown in Estonia was declared only a few weeks after the start of the semester, international exchange students had only a very short period of time to establish contacts with fellow students on site. Accordingly, there was probably little integration into university structures and social contacts were maintained more on a personal level with contacts from the home country. Thus, such students’ fulfillment of this basic need might have required more time and effort, leading to higher procrastination and less persistence in learning.
A diametrically opposite pattern was observed for persistence (H7c), where some direct effects of social relatedness were unexpectedly negative or close to zero. We therefore conclude that evidence for a direct negative relationship between social relatedness and procrastination and a direct positive relationship between social relatedness and persistence is lacking. This could be due to the specificity of the COVID-19 situation and resulting lockdowns, in which maintaining social contact took students’ focus off learning. In line with SDT, however, indirect effects of perceived social relatedness on procrastination (H4c) and persistence (H5c) mediated via intrinsic motivation were much more visible and in the expected directions. We conclude that, while the direct relation between perceived social relatedness and procrastination is ambiguous, there is strong evidence that the relationship between social relatedness and the measured learning behaviors is mediated by intrinsic motivation. Our results strongly underscore SDT’s assumption that close social relations promote intrinsic motivation, which in turn has a positive effect on learning behavior (e.g., [ 6 , 14 ]). The effects for perceived competence exhibited a somewhat clearer and hypothesis-conforming pattern. All direct effects of perceived competence on procrastination (H6b) were in the expected negative direction, albeit with confidence intervals spanning zero in 7 out of 17 countries. Direct effects of perceived competence on persistence (H7b) were consistently positive with the exception of the USA, where we observed a very small and non-significant negative effect. Indirect effects of perceived competence on procrastination (H4b) and persistence (H5b) as mediated by intrinsic motivation were mostly consistent with our expectations as well. Considering this overall pattern of results, we conclude that there is strong evidence that perceived competence is negatively associated with procrastination and positively associated with persistence. Furthermore, our results also support SDT’s postulate that the relationship between perceived competence and the measured learning behaviors is mediated by intrinsic motivation.
It is notable that the estimated direct effects of perceived competence on procrastination and persistence were higher than the indirect effects in most countries we investigated. Although SDT proposes that perceived competence leads to higher intrinsic motivation, Deci and Ryan [ 8 ] also argue that it affects all types of motivation and regulation, including less autonomous forms such as introjected and identified motivation, indicating that if the need for competence is not satisfied, all types of motivation are negatively affected. This may result in a general amotivation and lack of action. In our study, we only investigated intrinsic motivation as a mediator. For future research, it might be advantageous to further differentiate between different types of externally and internally controlled behavior. Furthermore, perceived competence increases when tasks are experienced as optimally challenging [ 7 , 54 ]. However, in order for instructors to provide the optimal level of difficulty and support needed, frequent communication with students is essential. Considering that data collection for the present study took place at a time of great uncertainty, when many countries had only transitioned to distance learning a few weeks prior, it is reasonable to assume that both structural support as well as communication and feedback mechanisms had not yet matured to a degree that would favor individualized and competency-based work.
However, our findings corroborate those from earlier studies insofar as they underline the associations between perceived competence and positive learning behavior (e.g., [ 19 ]), that is, lower procrastination [ 18 ] and higher persistence (e.g., [ 21 ]), even in an exceptional situation like pandemic-induced distance learning.
Turning to perceived autonomy, although the confidence intervals for the direct effects of perceived autonomy on procrastination (H6a) did span zero in most countries with smaller sample sizes, all effect estimates indicated a negative relation with procrastination. We expected these relationships from previous studies [ 18 , 23 ]; however, the effect might have been even more pronounced in the relatively autonomous learning situation of distance learning, where students usually have increased autonomy in deciding when, where, and how to learn. While this bears the risk of procrastination, it also comes with the opportunity to consciously delay less pressing tasks in favor of other, more important or urgent tasks (also called strategic delay ) [ 5 ], resulting in lower procrastination. In future studies, it might be beneficial to differentiate between passive forms of procrastination and active strategic delay in order to obtain more detailed information on the mechanisms behind this relationship. Direct effects of autonomy on persistence (H7a) were consistently positive. Students who are free to choose their preferred time and place to study may engage more with their studies and therefore be more persistent.
Indirect effects of perceived autonomy on procrastination mediated by intrinsic motivation (H4a) were negative in all but two countries (China and the USA), which is generally consistent with our hypothesis and in line with previous research (e.g., [ 23 ]). Additionally, we found a positive indirect effect of autonomy on persistence (H5a), indicating that autonomy and intrinsic motivation play a crucial role in students’ persistence in a distance learning setting. Based on our results, we conclude that perceived autonomy is negatively related to procrastination and positively related to persistence, and that this relationship is mediated by intrinsic motivation. It is worth noting that, unlike with perceived competence, the direct and indirect effects of perceived autonomy on the outcomes procrastination and persistence were similarly strong, suggesting that perceived autonomy is important not only as a driver of intrinsic motivation but also at a more direct level. It is important to make the best possible use of the opportunity for greater autonomy that distance learning offers. However, autonomy is not to be equated with a lack of structure; instead, learners should be given the opportunity to make their own decisions within certain framework conditions.
The applicability of self-determination theory across countries
Overall, the results of our mediation analysis for the separate countries support the claim posited by SDT that basic need satisfaction is essential for intrinsic motivation and learning across different countries and settings. In an exploratory analysis, we tested a fixed path model including all countries at once, in order to test whether a simplified general model would yield a similar amount of explained variance. For perceived autonomy and social relatedness, the model fit increased, whereas for perceived competence it decreased slightly compared to the multigroup model. However, all fixed path models exhibited adequate model fit. Considering that the circumstances in which distance learning took place in different countries varied to some degree (see also Limitations), these findings are a strong indicator for the universality of SDT.
Study strengths and limitations
Although the current study has several strengths, including a large sample size and data from multiple countries, three limitations must be considered. First, it must be noted that sample sizes varied widely across the 17 countries in our study, with one country above 6,000 (Austria), two above 1,000 (Finland and Sweden) and the rest ranging between 104 and 905. Random sampling effects are more problematic in smaller samples; hence, this large variation weakens our ability to conduct cross-country comparisons. At the same time, small sample sizes weaken the interpretability of results within each country; thus, our results for Austria, Finland and Sweden are considerably more robust than for the remaining fourteen countries. Additionally, two participating countries collected specific subsamples: In China, participants were only recruited from one university, a nursing school. In Estonia, only international exchange students were invited to participate. Nevertheless, with the exception of the unexpected positive direct relationship between social relatedness and procrastination, all observed divergent effects were non-significant. Indeed, this adds to the support for SDT’s claims to universality regarding the relationship between perceived autonomy, competence, and social relatedness with intrinsic motivation: Results in the included countries were, despite their differing subsamples, in line with the overall trend of results, supporting the idea that SDT applies equally to different groups of learners.
Second, due to the large number of countries in our sample and the overall volatility of the situation, learning circumstances were not identical for all participants. Due to factors such as COVID-19 case counts and national governments’ political priorities, lockdown measures varied in their strictness across settings. Some universities were fully closed, some allowed on-site teaching for particular groups (e.g., students in the middle of a laboratory internship), and some switched to distance learning but held exams on site (see S1 Table in S1 File for further information). Therefore, learning conditions were not as comparable as in a strict experimental setting. On the other hand, this strengthens the ecological validity of our study. The fact that the pattern of results was similar across contexts with certain variation in learning conditions further supports the universal applicability of SDT.
Finally, due to the novelty of the COVID-19 situation, some of the measures were newly developed for this study. Due to the need to react swiftly and collect data on the constantly evolving situation, it was not possible to conduct a comprehensive validation study of the instruments. Nevertheless, we were able to confirm the validity of our instruments in several ways, including cognitive interview testing, CFAs, CR, and measurement invariance testing.
Conclusion and future directions
In general, our results further support previous research on the relation between basic psychological need fulfilment and intrinsic motivation, as proposed in self-determination theory. It also extends past findings by applying this well-established theory to the new and unique situation of pandemic-induced distance learning across 17 different countries. Moreover, it underlines the importance of perceived autonomy and competence for procrastination and persistence in this setting. However, various other directions for further research remain to be pursued. While our findings point to the relevance of social relatedness for intrinsic motivation in addition to perceived competence and autonomy, further research should explore the specific mechanisms necessary to promote social connectedness in distance learning. Furthermore, in our study, we investigated intrinsic motivation, as the most autonomous form of motivation. Future research might address different types of externally and internally regulated motivation in order to further differentiate our results regarding the relations between basic need satisfaction and motivation. Finally, a longitudinal study design could provide deeper insights into the trajectory of need satisfaction, intrinsic motivation and learning behavior during extended periods of social distancing and could provide insights into potential forms of support implemented by teachers and coping mechanisms developed by students.
Supporting information
https://doi.org/10.1371/journal.pone.0257346.s001
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Capturing the benefits of remote learning
How education experts are applying lessons learned in the pandemic to promote positive outcomes for all students
Vol. 52 No. 6 Print version: page 46
- Schools and Classrooms
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With schools open again after more than a year of teaching students outside the classroom, the pandemic sometimes feels like a distant memory. The return to classrooms this fall brings major relief for many families and educators. Factors such as a lack of reliable technology and family support, along with an absence of school resources, resulted in significant academic setbacks, not to mention stress for everyone involved.
But for all the downsides of distance learning, educators, psychologists, and parents have seen some benefits as well. For example, certain populations of students found new ways to be more engaged in learning, without the distractions and difficulties they faced in the classroom, and the general challenges of remote learning and the pandemic brought mental health to the forefront of the classroom experience.
Peter Faustino, PsyD, a school psychologist in Scarsdale, New York, said the pandemic also prompted educators and school psychologists to find creative new ways of ensuring students’ emotional and academic well-being. “So many students were impacted by the pandemic, so we couldn’t just assume they would find resources on their own,” said Faustino. “We had to work hard at figuring out new ways to connect with them.”
Here are some of the benefits of distance learning that school psychologists and educators have observed and the ways in which they’re implementing those lessons post-pandemic, with the goal of creating a more equitable, productive environment for all students.
Prioritizing mental health
Faustino said that during the pandemic, he had more mental health conversations with students, families, and teachers than ever. “Because COVID-19 affected everyone, we’re now having mental health discussions as school leaders on a daily and weekly basis,” he said.
This renewed focus on mental health has the potential to improve students’ well-being in profound ways—starting with helping them recover from the pandemic’s effects. In New York City, for example, schools are hiring more than 600 new clinicians, including psychologists , to screen students’ mental health and help them process pandemic-related trauma and adjust to the “new normal” of attending school in person.
Educators and families are also realizing the importance of protecting students’ mental health more generally—not only for their health and safety but for their learning. “We’ve been seeing a broader appreciation for the fact that mental health is a prerequisite for learning rather than an extracurricular pursuit,” said Eric Rossen, PhD, director of professional development and standards at the National Association of School Psychologists.
As a result, Rossen hopes educators will embed social and emotional learning components into daily instruction. For example, teachers could teach mindfulness techniques in the classroom and take in-the-moment opportunities to help kids resolve conflicts or manage stress.
Improved access to mental health resources in schools is another positive effect. Because of physical distancing guidelines, school leaders had to find ways to deliver mental health services remotely, including via online referrals and teletherapy with school psychologists and counselors.
Early in the pandemic, Faustino said he was hesitant about teletherapy’s effectiveness; now, he hopes to continue offering a virtual option. Online scheduling and remote appointments make it easier for students to access mental health resources, and some students even enjoy virtual appointments more, as they can attend therapy in their own spaces rather than showing up in the counselor’s office. For older students, Faustino said that level of comfort often leads to more productive, open conversations.
Autonomy as a key to motivation
Research suggests that when students have more choices about their materials and activities, they’re more motivated—which may translate to increased learning and academic success. In a 2016 paper, psychology researcher Allan Wigfield, PhD, and colleagues make the case that control and autonomy in reading activities can improve both motivation and comprehension ( Child Development Perspectives , Vol. 10, No. 3 ).
During the period of online teaching, some students had opportunities to learn at their own pace, which educators say improved their learning outcomes—especially in older students. In a 2020 survey of more than 600 parents, researchers found the second-most-valued benefit of distance learning was flexibility—not only in schedule but in method of learning.
In a recent study, researchers found that 18% of parents pointed to greater flexibility in a child’s schedule or way of learning as the biggest benefit or positive outcome related to remote learning ( School Psychology , Roy, A., et al., in press).
This individualized learning helps students find more free time for interests and also allows them to conduct their learning at a time they’re most likely to succeed. During the pandemic, Mark Gardner, an English teacher at Hayes Freedom High School in Camas, Washington, said he realized how important student-centered learning is and that whether learning happens should take precedence over how and when it occurs.
For example, one of his students thrived when he had the choice to do work later at night because he took care of his siblings during the day. Now, Gardner posts homework online on Sundays so students can work at their own pace during the week. “Going forward, we want to create as many access points as we can for kids to engage with learning,” he said.
Rosanna Breaux , PhD, an assistant professor of psychology and assistant director of the Child Study Center at Virginia Tech, agrees. “I’d like to see this flexibility continue in some way, where—similar to college—students can guide their own learning based on their interests or when they’re most productive,” she said.
During the pandemic, many educators were forced to rethink how to keep students engaged. Rossen said because many school districts shared virtual curricula during the period of remote learning, older students could take more challenging or interesting courses than they could in person. The same is true for younger students: Megan Hibbard, a teacher in White Bear Lake, Minnesota, said many of her fifth graders enjoyed distance learning more than in-person because they could work on projects that aligned with their interests.
“So much of motivation is discovering the unique things the student finds interesting,” said Hunter Gehlbach, PhD, a professor and vice dean at the Johns Hopkins School of Education. “The more you can facilitate students spending more time on the things they’re really interested in, the better.”
Going forward, Rossen hopes virtual curricula will allow students greater opportunities to pursue their interests, such as by taking AP classes, foreign languages, or vocational electives not available at their own schools.
Conversely, Hibbard’s goal is to increase opportunities for students to pursue their interests in the in-person setting. For example, she plans to increase what she calls “Genius Hours,” a time at the end of the school day when students can focus on high-interest projects they’ll eventually share with the class.
Better understanding of children's needs
One of the most important predictors of a child’s success in school is parental involvement in their education. For example, in a meta-analysis of studies, researchers linked parental engagement in their middle schoolers’ education with greater measures of success (Hill, N. E., & Tyson, D. F., Developmental Psychology , Vol. 45, No. 3, 2009).
During the pandemic, parents had new opportunities to learn about their kids and, as a result, help them learn. According to a study by Breaux and colleagues, many parents reported that the pandemic allowed them a better understanding of their child’s learning style, needs, or curriculum.
James C. Kaufman , PhD, a professor of educational psychology at the University of Connecticut and the father of an elementary schooler and a high schooler, said he’s had a front-row seat for his sons’ learning for the first time. “Watching my kids learn and engage with classmates has given me some insight in how to parent them,” he said.
Stephen Becker , PhD, a pediatric psychologist at Cincinnati Children’s Hospital Medical Center, said some parents have observed their children’s behavior or learning needs for the first time, which could prompt them to consider assessment and Individualized Education Program (IEP) services. Across the board, Gehlbach said parents are realizing how they can better partner with schools to ensure their kids’ well-being and academic success.
For example, Samantha Marks , PsyD, a Florida-based clinical psychologist, said she realized how much help her middle school daughter, a gifted and talented student with a 504 plan (a plan for how the school will offer support for a student’s disability) for anxiety, needed with independence. “Bringing the learning home made it crystal clear what we needed to teach our daughter to be independent and improve executive functioning” she said. “My takeaway from this is that more parents need to be involved in their children’s education in a healthy, helpful way.”
Marks also gained a deeper understanding of her daughter’s mental health needs. Through her 504 plan, she received help managing her anxiety at school—at home, though, Marks wasn’t always available to help, which taught her the importance of helping her daughter manage her anxiety independently.
Along with parents gaining a deeper understanding of their kids’ needs, the pandemic also prompted greater parent participation in school. For example, Rossen said his kids’ school had virtual school board meetings; he hopes virtual options continue for events like back-to-school information sessions and parenting workshops. “These meetings are often in the evening, and if you’re a single parent or sole caregiver, you may not want to pay a babysitter in order to attend,” he said.
Brittany Greiert, PhD, a school psychologist in Aurora, Colorado, says culturally and linguistically diverse families at her schools benefited from streamlined opportunities to communicate with administrators and teachers. Her district used an app that translates parent communication into 150 languages. Parents can also remotely participate in meetings with school psychologists or teachers, which Greiert says she plans to continue post-pandemic.
Decreased bullying
During stay-at-home orders, kids with neurodevelopmental disorders experienced less bullying than pre-pandemic (McFayden, T. C., et al., Journal of Rural Mental Health , No. 45, Vol. 2, 2021). According to 2019 research, children with emotional, behavioral, and physical health needs experience increased rates of bullying victimization ( Lebrun-Harris, L. A., et al., ), and from the U.S. Department of Education suggests the majority of bullying takes place in person and in unsupervised areas (PDF) .
Scott Graves , PhD, an associate professor of educational studies at The Ohio State University and a member of APA’s Coalition for Psychology in Schools and Education (CPSE), said the supervision by parents and teachers in remote learning likely played a part in reducing bullying. As a result, he’s less worried his Black sons will be victims of microaggressions and racist behavior during online learning.
Some Asian American families also report that remote learning offered protection against racism students may have experienced in person. Shereen Naser, PhD, an associate professor of psychology at Cleveland State University and a member of CPSE, and colleagues found that students are more comfortable saying discriminatory things in school when their teachers are also doing so; Naser suspects this trickle-down effect is less likely to happen when students learn from home ( School Psychology International , 2019).
Reductions in bullying and microaggressions aren’t just beneficial for students’ long-term mental health. Breaux said less bullying at school results in less stress, which can improve students’ self-esteem and mood—both of which impact their ability to learn.
Patricia Perez, PhD, an associate professor of international psychology at The Chicago School of Professional Psychology and a member of CPSE, said it’s important for schools to be proactive in providing spaces for support and cultural expression for students from vulnerable backgrounds, whether in culture-specific clubs, all-school assemblies that address racism and other diversity-related topics, or safe spaces to process feelings with teachers.
According to Rossen, many schools are already considering how to continue supporting students at risk for bullying, including by restructuring the school environment.
One principal, Rossen said, recently switched to single-use bathrooms to avoid congregating in those spaces once in-person learning commences to maintain social distancing requirements. “The principal received feedback from students about how going to the bathroom is much less stressful for these students in part due to less bullying,” he said.
More opportunities for special needs students
In Becker and Breaux’s research, parents of students with attention-deficit/hyperactivity disorder (ADHD), particularly those with a 504 plan and IEP, reported greater difficulties with remote learning. But some students with special learning needs—including those with IEPs and 504 plans—thrived in an at-home learning environment. Recent reporting in The New York Times suggests this is one reason many students want to continue online learning.
According to Cara Laitusis, PhD, a principal research scientist at Educational Testing Service ( ETS ) and a member of CPSE, reduced distractions may improve learning outcomes for some students with disabilities that impact attention in a group setting. “In assessments, small group or individual settings are frequently requested accommodations for some students with ADHD, anxiety, or autism. Being in a quiet place alone without peers for part of the instructional day may also allow for more focus,” she said. However, she also pointed out the benefits of inclusion in the classroom for developing social skills with peers.
Remote learning has improved academic outcomes for students with different learning needs, too. Marks said her seventh-grade daughter, a visual learner, appreciated the increase in video presentations and graphics. Similarly, Hibbard said many of her students who struggle to grasp lessons on the first try have benefited from the ability to watch videos over again until they understand. Post-pandemic, she plans to record bite-size lessons—for example, a 1-minute video of a long division problem—so her students can rewatch and process at their own rate.
Learners with anxiety also appreciate the option not to be in the classroom, because the social pressures of being surrounded by peers can make it hard to focus on academics. “Several of my students have learned more in the last year simply due to the absence of anxiety,” said Rosie Reid, an English teacher at Ygnacio Valley High School in Concord, California, and a 2019 California Teacher of the Year. “It’s just one less thing to negotiate in a learning environment.”
On online learning platforms, it’s easier for kids with social anxiety or shyness to participate. One of Gardner’s students with social anxiety participated far more in virtual settings and chats. Now, Gardner is brainstorming ways to encourage students to chat in person, such as by projecting a chat screen on the blackboard.
Technology has helped school psychologists better engage students, too. For example, Greiert said the virtual setting gave her a new understanding of her students’ personalities and needs. “Typing out their thoughts, they were able to demonstrate humor or complex thoughts they never demonstrated in person,” she said. “I really want to keep incorporating technology into sessions so kids can keep building on their strengths.”
Reid says that along with the high school students she teaches, she’s seen her 6-year-old daughter benefit from learning at her own pace in the familiarity of her home. Before the pandemic, she was behind academically, but by guiding her own learning—writing poems, reading books, playing outside with her siblings—she’s blossomed. “For me, as both a mother and as a teacher, this whole phenomenon has opened the door to what education can be,” Reid said.
Eleanor Di Marino-Linnen, PhD, a psychologist and superintendent of the Rose Tree Media School District in Media, Pennsylvania, says the pandemic afforded her district a chance to rethink old routines and implement new ones. “As challenging as it is, it’s definitely an exciting time to be in education when we have a chance to reenvision what schools have looked like for many years,” she said. “We want to capitalize on what we’ve learned.”
Further reading
Why are some kids thriving during remote learning? Fleming, N., Edutopia, 2020
Remote learning has been a disaster for many students. But some kids have thrived. Gilman, A., The Washington Post , Oct. 3, 2020
A preliminary examination of key strategies, challenges, and benefits of remote learning expressed by parents during the COVID-19 pandemic Roy, A., et al., School Psychology , in press
Remote learning during COVID-19: Examining school practices, service continuation, and difficulties for adolescents with and without attention-deficit/hyperactivity disorder Becker S. P., et al., Journal of Adolescent Health , 2020
Recommended Reading
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With school closures, teachers can keep their lessons going remotely
Mar 05, 2020
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I spent more than a decade working in schools as a teacher and administrator. Whenever there was an event that caused the school to close, I found a way to ensure that students didn’t lose valuable learning time. We call this “distance learning” and many teachers, whether they work in a virtual school or are faced with a unique event, are exploring how to make it work. Currently, we’re facing such an event. Concerns over the transmission of COVID-19 are closing schools across the globe, and millions of students are unable to physically attend school.
To help with this, we recently announced that advanced Hangouts Meet features are available for free to anyone who uses G Suite around the world. This means you’ll be able to put up to 250 people on a Hangouts Meet call—an entire class or group of classes can join a lesson simultaneously. You’ll get live-streaming for up to 100,000 viewers within your domain, so that you can do a virtual school assembly or stream a lecture. Plus, you can record meetings and save them to Google Drive. When students can’t join the lesson, they’ll be able to access the content later.
For educators preparing for potential school closures—or currently facing them—here are a few other ways to handle distance learning.
Keep students engaged while they’re at home
Virtual learning can be isolating and disengaging for students. Sitting in front of a screen for hours watching videos may compel a student to fast forward or even skip a lesson altogether. To keep them engaged, open up virtual discussions about what they’re learning. In a lesson exploring the water cycle, challenge students to pause the video and join a discussion in Google Classroom (using the Stream) about the last time they experienced a thunderstorm. You can also use comments in Google Docs and Classroom to have a two-way discussion with students as you give feedback on their work—another great strategy to engage when you can’t see them in person.
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Frequently assess student learning
Formative assessments help you make sure students are continuing to progress while away from school. Check for understanding during group instruction by asking a poll question in the middle of a lesson and showing the results in real time. This can also help you “take attendance” in a virtual setting. Quizzes in Google Forms offer auto-grading features, allow you to embed videos, images, and as many answer choices as you want. You can also assign graded discussions in Google Classroom , and students can demonstrate their knowledge through project-based learning assignments using Slide presentations, Docs or Sites.
Continue to connect with Hangouts Meet
When students’ routines are disrupted, many realize how much they actually miss the structure of school, and learning with their teacher. It’s important to maintain that feeling of comfort and safety during a time of uncertainty.
If your students have Wi-Fi access, you can see them virtually on Hangouts Meet . You can also use this platform to create video discussion sections for students to engage with one another and support their peers who might be struggling with concepts. Turn on live captions to help students focus, and so that students who are deaf or hard of hearing can read spoken language during the call.
Scheduling is another challenge that may arise. Using Calendar Appointment Slots , students who need extra help can sign up to meet 1:1 or in small groups with you. Due to intermittent or lack of Wi-Fi access, or shifting childcare solutions, not all students may be able to join a virtual classroom at the same time. Your instruction will likely be a mixture of live video and sharing recordings of your lessons for students who couldn’t make it. Thankfully, advanced features in Hangouts Meet allow you to record your lessons to share with students.
Check in with how your students are feeling
Social Emotional Learning can continue in a distance learning setting as well. Just as you can use Hangouts Meet to “be” there for your students and maintain your classroom culture, you can provide other ways for students to share and process their emotions while away from school. Using Google Forms , create mood check-ins for students to share their emotional state on a daily basis. Within the Form, students can request a conference with the teacher if they need extra support. You can also set up a private blog for students to reflect on the experience by journaling or recording video reflections.
Think beyond the clock
With distance learning, you don’t have to worry about time constraints of the normal school day: rushing students into the classroom or hurrying to finish your lesson before the bell rings. Students can take more time on some activities and breeze through lessons that come naturally to them. Take advantage of this opportunity and design your lessons to include more “choose your own adventure” activities rather than a fixed schedule of lectures and lessons.
Explore more approaches to distance learning
As educators and administrators set up contingency plans and consider making classrooms fully virtual, we’re here to help. We’ve seen educational leaders reaching out to one another, sharing ideas and providing support through Google Educator Groups , and other social networks, including Twitter and Facebook . Check out this webinar on distance learning strategies, find resources in the Teacher Center , and continue to share ways you support remote learners .
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Information technology-integrated curriculum and distance learning during covid-19 pandemic in preschool †.
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1. Introduction
2. information technology-integrated curriculum, distance learning, and teachers’ roles in preschool, 3. parents’ views on curriculum and distance learning for young children, 4.1. participants, 4.2. data analysis and verification, 5.1. implementation of the information technology-integrated curriculum before the pandemic, 5.2. implementation of the information technology-integrated curriculum during the pandemic, 5.3. parents’ views on the curriculum and distance learning, 6. discussion and conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.
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Code | Education Level | Teaching Experience | Type of Preschool | Type of Distance Learning |
---|---|---|---|---|
T1 | College | 10 years | private | asynchronous learning |
T2 | College | 6 years | private | blended (hybrid) learning |
T3 | Master | 5 years | public | asynchronous learning |
T4 | Master | 25 years | public | asynchronous learning |
Code | Education Level | Children’s Age | Children’s Teacher | Main Facilitator |
---|---|---|---|---|
P1 | College | 5 years old | T1 | Mother |
P2 | Junior College | 4 years old | T2 | Mother |
P3 | College | 6 years old | T3 | Mother |
P4 | Master | 5 years old | T4 | Mother |
Phases of Implementation | Teaching Activities | T1 | T2 | T3 | T4 |
---|---|---|---|---|---|
Teaching Preparation | create teaching resources | ◎ | ◎ | ||
Teaching Process | support activities | ◎ | ◎ | ◎ | |
complement and enhance children’s learning experiences | ◎ | ◎ | |||
record children’s progress | ◎ | ◎ | |||
provide interactive teaching activities | ◎ | ◎ | |||
offer information technology and media resources for learning corners | ◎ | ◎ | ◎ | ||
Post-Teaching | integrate learning activities | ◎ | |||
assess children’s learning | ◎ |
Type of Distance Learning | Teacher | Asynchronous Course Content | Synchronous Course Content | ||
---|---|---|---|---|---|
Teaching Activities Across the Six Major Learning Areas | Special Courses | Teaching Material Resource Packs | Thematic Learning Activities, Learning Corners, and Group Discussions | ||
Asynchronous learning | T1 | ◎ | ◎ | ||
T3 | ◎ | ||||
T4 | ◎ | ||||
Blended (Hybrid) learning | T2 | ◎ | ◎ | ◎ |
Parents’ Roles | P1 | P2 | P3 | P4 |
---|---|---|---|---|
companions | ◎ | |||
teaching assistants | ◎ | ◎ | ◎ | |
observers | ◎ | |||
recorders of children’s learning outcomes | ◎ | ◎ | ◎ | |
time controllers | ◎ |
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Huang, Y.-F.; Liang, P.-H. Information Technology-Integrated Curriculum and Distance Learning During COVID-19 Pandemic in Preschool. Eng. Proc. 2024 , 74 , 9. https://doi.org/10.3390/engproc2024074009
Huang Y-F, Liang P-H. Information Technology-Integrated Curriculum and Distance Learning During COVID-19 Pandemic in Preschool. Engineering Proceedings . 2024; 74(1):9. https://doi.org/10.3390/engproc2024074009
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Assessing the Experience of Distance Teaching During Confinement: A Study on Behaviors and Attitudes of Higher Education Professors
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- Saadeddine Igamane 11 &
- Lalla Fatima Zohra Alami Talbi 12
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The paper aims to investigate and explain the involvement level of Moroccan university teachers in distance teaching during the COVID-19 containment period using the social representation theory framework and econometric model based on demographic and institutional variables.
Overall, the results reveal that the selected variables exert a limited influence on teachers’ involvement in distance education. However, factors such as institutional support, ICT proficiency, availability of suitable workspace, gender and teachers’ rank contribute significantly to explaining their low to average involvement in remote teaching during COVID-19 confinement period. Furthermore, institutional support and ICT proficiency emerged as the most influential factors, highlighting the crucial role of organizational support and technological proficiency in facilitating effective distance education. These findings underscore the need for targeted interventions and support mechanisms to strengthen faculty involvement in distance education initiatives, which ultimately improves the quality of distance educational experiences for students.
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Marinoni, G., Land, H.V., Jensen, T.: The Impact of COVID-19 on Higher Education Around the World: IAU Global Survey Report. International Association of Universities. Paris: UNESCO House (2020)
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Igamane, S., Alami Talbi, L.F. (2024). Assessing the Experience of Distance Teaching During Confinement: A Study on Behaviors and Attitudes of Higher Education Professors. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2024. Lecture Notes in Networks and Systems, vol 1100. Springer, Cham. https://doi.org/10.1007/978-3-031-68660-3_25
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Distance education during the COVID-19 outbreak: A cross-sectional study among medical students in North of Jordan
Affiliations.
- 1 Department of Obstetrics and Gynecology, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
- 2 Department of Obstetrics and Gynecology, Faculty of Medicine, Yarmouk University, Irbid, Jordan.
- 3 Department of Pharmacology, Faculty of Medicine, Jordan University of Science and Technology, Irbi, Jordan.
- 4 Medical Students, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
- 5 Princess Salma, Faculty of Nursing, Al-al-Bayt University, Jordan.
- PMID: 33042535
- PMCID: PMC7531436
- DOI: 10.1016/j.amsu.2020.09.036
Introduction: In the spot of the new emerging COVID-19 pandemic and its major impact worldwide on day-to-day activities many rules had to be changed in order to fight this pandemic. Lockdown started in Jordan and around the globe affecting several aspects of life including economy, education, entertainment, and government policies. Regarding education, the priority was to ensure the safety and progress of the educational process. Thus, new methods of teaching had to be applied using the online learning at Jordan University of Science and Technology (JUST), Faculty of Medicine. This study was done to assess (1) Class Experience (2) Students and Lecturers' Interaction (3) Online Learning Advantages & Disadvantages (4) Students' Preference.
Methods: A cross sectional study was conducted Convenience sampling technique was used to collect the data from the participants using a survey composed of 18 questions on Google Forms platform. A link was sent to the undergraduate medical students at the Jordan University of Science & Technology via their e-learning accounts (n = 3700). The form was available from May 22nd, 2020 to May 30th, 2020 for 8 days long. Data analysis was done using SPSS V 23.
Results: 2212 out of 3700 students responded, (55.8%) of them were in the basic years and (44.2%) of them were in the clinical years. (55.8%) of students started to take online lectures after 3 weeks. (45.7%) used the hybrid teaching method (asynchronous and synchronous), (31.4%) used live classes, and 22.8% recorded classes. Zoom was the most used platform. (48.7%) and (57%) of clinical students and basic students express their interaction as bad, while the others had good and excellent interaction. Maintaining social distance was the most advantage of online teaching, while poor technical setup and no direct contact were the most disadvantage, furthermore inability to have real clinical access was a significant problem for clinical students (p < .001). With reference to students' preferences 75% of students were not pleased with their experience and 42% of students prefer to integrate online learning with traditional learning.
Conclusion: Most medical students at JUST preferred the traditional face-to-face teaching method over the solo online teaching methods with recommendations to convert to a more integrated educational system. Also, a well-established infrastructure should be done in involving online teaching.
Keywords: Covid-19; Jordan; Medical students; Online learning.
© 2020 The Author(s).
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