The Current State of Research on Training Effectiveness
- First Online: 30 July 2020
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Cite this chapter
- Thomas N. Garavan 11 ,
- Fergal O’Brien 12 ,
- James Duggan 13 ,
- Claire Gubbins 14 ,
- Yanqing Lai 15 ,
- Ronan Carbery 16 ,
- Sinead Heneghan 17 ,
- Ronnie Lannon 18 ,
- Maura Sheehan 19 &
- Kirsteen Grant 20
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5 Citations
This chapter addresses the current state of research on training effectiveness in organisations. It summarises the key findings on what we know about training effectiveness, the research emphasis given to different components of the model, and how research informs the ways in which organisations should approach learning and development to maximise effectiveness. The chapter highlights the role of training needs analysis, the types of attendance policies that should be used, the most effective design of training delivery to maximise effectiveness, the relative effectiveness of training methods, the organisation of training content, the importance of learning or training transfer, and the types of outcomes that are derived from learning and development.
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Garavan, T.N. et al. (2020). The Current State of Research on Training Effectiveness. In: Learning and Development Effectiveness in Organisations. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-48900-7_5
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The Role of Training and Development on Organizational Effectiveness
Ismael, N. B., Othman, B. J., Gardi, B., Hamza, P. A., Sorguli, S., Aziz, H. M., Ahmed, S. A., Sabir, B. Y., Ali, B. J., Anwar, G. (2021). The Role of Training and Development on Organizational effectiveness. International Journal of Engineering, Business and Management, 5(3), 15–24
10 Pages Posted: 28 May 2021
Nechirwan Burhan Ismael
Cihan University
Baban Jabbar Othman
Knowledge university, bayar gardi, pshdar abdalla hamza, kurdistan technical institute, sarhang sorguli.
Knowledge University - College of Administration and Financial Sciences
Hassan Mahmood Aziz
Shahla ali ahmed, near east university, bawan yassin sabir, bayad jamal ali.
Komar University for Science and Technology
Govand Anwar
Knowledge University - Department of Business Administration
Date Written: May 22, 2021
The aim of this study is to investigate the relationship between training and development with organizational effectiveness. The research data is collected by developing questionnaire, the research is of qualitative method which tends to address the quality of things in a depth rather than numerical data about the questionnaire , its composed of two parts, the first one interested in collecting personal data, which the second section is shining light on the areas of (training, development and organization effectiveness) the sample were both male and female The researcher had collected the data at private universities by using a random sample , 120 questioners were delivered to different levels of employee at private universities and 102 of them responded to it , the analysis was undertaken by using SPSS. In this study, the researchers tried to shine a light on the training and development and how they can affect effectiveness of an organization for which the researchers decided to choose private universities to distribute my questionnaire and receiving them after they have filled it. the first research question that the researchers have found there is relationship between training and development and also the second research question that the researchers have found that there a direct impact of development programs on the organizational effectiveness and its progress and development is essential for an effective organization.
Keywords: Training, Development, Organizational Effectiveness, Private Universities
Suggested Citation: Suggested Citation
Cihan University ( email )
Street 100M Erbil, Kurdistan Region 0383-23 Iraq
Erbil, 44001 Iraq
Knowledge University - College of Administration and Financial Sciences ( email )
TRNC/Nicosia, Cyprus Nicosia Turkey
Bayad Jamal Ali (Contact Author)
Komar university for science and technology ( email ).
Sulaimani Qularesi Kurdistan, Sulaimani Iraq
Knowledge University - Department of Business Administration ( email )
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EMPLOYEE TRAINING AND DEVELOPMENT AS A MODEL FOR ORGANIZATIONAL SUCCESS
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This article reviewed employee training and development as a model for organizational performance and effectiveness. The various literatures reviewed on the topic in question showed that, training and development had positively correlated and claimed statistical significant relationship with employee performance and effectiveness and can advance organizational growth and success. In order to improve employee training and development as well as improved performance and service delivery, it is recommended that management should increase the number of employees taking part in training and development.
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The aim of this study was to explore the impact of training and development on employee performance. This study conducted under the framework of banking sector of Pakistan. Study finding reveal development leads to better employee performance, training and development both increase the employee performance. Organizations need to spend on training and development of its employees for sustainable long term competitive edge.
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The core theme of this study is to investigate relationship between human resource management and firm performance. This empirical study was three elements of human resources management that is training, skills and experience. The proposed study uses a sample size of 50 respondents. The target population is professionals working in different manufacturing sectors. The result shows that training, skills and experience are positively related with firm performance. Human capital management practices have a positive impact on firm performance. The organizations must enhance human capital by providing continuous training programs to update existing employee skills and abilities.
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"A case Study of Jordanian Private Sector transportation companies located in the Southern region of Jordan. A particular reference is made to the Govern ate of Maan ". ABSTRACT The Success or failure of modern business organizations depends on the quality of their human resources. Well trained and highly developed employees are considered as corner stone for such success. Hence the purpose of the study was to investigate the relationship between training , development, training and development and employees performance and productivity in selected Jordanian Private Sector transportation companies located in the Southern region of Jordan. The study was based on set of hypotheses that HOs: hypothesized no relationships between variables, while H1-H6 hypothesized the existence of relationships between stated variables. A quantitative approach is used Relevant data was collected through structured questionnaire. Subjects for the study consisted of 254 employees which constituted 60% of the total target population of 420 people. 254 structured questionnaire were distributed to employees on job location, 212 questionnaires were returned and only 188 were suitable for statistical analysis. SPSS version 16 has been used to for data analysis. Both descriptive and inferential statistics were used for data analysis. The statistical tools were aligned with the objective of the research. For this purpose, frequency tables, percentages, means and standard deviations were computed and substantively interpreted. Inferential statistics like Pearson product moment correlation coefficient (r) and linear regression were used to determine if there is a significant positive relationship existed between the independent variables (training and development) and dependent variables (performance and productivity). The findings indicated that training and development were positively correlated and claimed statistically significant relationship with employee performance and productivity. Analysis and interpretations were made at 0.05 level of significance. The study concluded that training and development have important impact on employee performance and productivity. Therefore, it was recommended that effective training programs and carefully set development plans should be provided to all employees to enable them to enhance their skills and upgrade their knowledge. Finally, foreseeable future research can be conducted to cover other variables like (capabilities, involvement so on) which might affect performance and productivity.
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1. Introduction
2. gan architecture, hierarchy, and variants, 2.1. where do the generated images originate noise vs. image, 2.2. improvement of quality for generated images, 3. selecting the appropriate gan for the research objectives, 3.1. three considerations, 3.1.1. image-to-image translation gans and interindividual anatomic variance, 3.1.2. high-quality image resolution and contrast, 3.1.3. unsupervised detection models, 3.2. examples of gan application to brain mr imaging, 3.2.1. cyclegan—brain infarction images for augmentation, 3.2.2. psp encoder-combined stylegan—brain vessel images for unsupervised anomaly detection, 4. input data training, 4.1. image data preprocessing protocols, 4.2. training saturation, 4.3. performance improvement and ablation study, 5. performance evaluation, 5.1. quantitative evaluation, 5.2. qualitative evaluation, 5.3. diagnostic performance evaluation, 6. conclusions, 7. future directions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.
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Click here to enlarge figure
Paper | Target Organ | Modality | Purpose | GAN Variants | Performance Evaluation |
---|---|---|---|---|---|
Wicaksono et al. (2023) [ ] | Intracranial artery | TOF-MRA * | Enhances resolution | Modified pix2pix | MS-SSIM *, 0.87 vs. 0.73 ISSM *, 0.60 vs. 0.35; Improved sensitivity and specificity in detecting aneurysms, stenoses, and occlusions |
Mason et al. (2023) [ ] | Prostate | mpMRI | Reconstruction | CycleGAN * | Improved quantitative deep learning score No qualitative improvement |
Ying et al. (2024) [ ] | Liver | CT and MRI | Augmentation | ICycleGAN * | Superior visual quality (SSIM *, PSNR *, NMAE *, FID *) |
Yuhan S. and Nak Young C. (2024) [ ] | Abdomen | CT → US | Segmentation and reconstruction | S-CycleGAN | Absent suitable metrics and evaluation |
Marzieh et al. (2023) [ ] | Brain, breast, and blood cancer | MRI Mammography | Unsupervised anomaly detection | f-anoGAN, GANomaly, and multi-KD | Unreliable performance for detecting abnormalities in medical images |
Seungjun et al. (2022) [ ] | Brain | CT | Unsupervised anomaly detection | CN *-StyleGAN | Shorter post-ADA * triage than pre-ADA * triage by 294 s in an emergency cohort median wait time |
Jinhao et al. (2023) [ ] | Neck and abdomen | NCCT * | CTA * reconstruction | CTA-GAN | Diagnostic accuracy for vascular diseases (accuracy = 94%) |
Wang et al. (2023) [ ] | Brain tumor | DSC MRI * | CBV * map reconstruction | Feature-consistent GAN + three-dimensional encoder–decoder network | The highest synthetic performance (SSIM *, 86.29% ± 4.30) Accuracy of grading gliomas (AUC *, 0.857 vs. 0.707) |
Seungju et al. (2023) [ ] | Breast cancer | Mammography | Unsupervised anomaly detection | StyleGAN2 | AUC *, sensitivity, and specificity of the classification performance (70.0%, 78.0%, and 52.0%) |
Architecture | GAN Variants | Detailed Characteristics | |
---|---|---|---|
Image-to-image translation | Suitable for medical image: preserve anatomical structure | Pix2pix [ ] | Applies conditions to generate detailed features Can generate high-quality images Requires paired dataset for training |
CycleGAN * [ ] | Uses unpaired data to generate images from different domains Suitable for image augmentation Unsuitable for organs with significant variance in shape and location | ||
Encoder-combined GANs [ , ] | Generates high-resolution images Enables unsupervised anomaly detection | ||
Noise-to-image translation | Not suitable for the medical images by itself: needs combination with an encoder or other GANs | cGAN * [ ] | Assigns conditions to generate required features Needs class labeling Can complicate the training process |
DCGAN * [ ] | Generates large-scale and high-quality images Unstable training process | ||
PGGAN * [ ] | Generates high resolution with fine image features Requires high computational costs and a large amount of training data | ||
StyleGAN [ , ] | Generates high resolution with fine image features Requires high computational costs and a large amount of training data Allows for the selective modification of desired image features |
Main Categories | Subcategories | Examples | Characteristics |
---|---|---|---|
Quantitative | Pixel-level metrics | PSNR *, SSIM *, and RMSE * | An objective evaluation method does not always correlate with radiologists’ evaluations |
Distribution metrics | FID * and IS * | ||
Adversarial evaluation | Another discriminator | Immediate feedback to the generator objective evaluation method does not always correlate with radiologists’ evaluations | |
Qualitative | Radiologist evaluation | Rating, ranking, preference, or pair wise comparison | Applicable to clinical diagnosis, requires time and effort, and there are different standards and biases within the evaluators |
Combined | Diagnostic performance | Accuracy, sensitivity, specificity, ROC * curve, and AUC * | Highest reliability in clinical diagnosis requires significant time and effort |
Normal → Synthetic Infarction | Infarction → Synthetic Normal | Total | |
---|---|---|---|
No. of generated images | 12 | 12 | 24 |
No. of consistent images | 9 | 10 | 19 |
Image production rate | 9/15 (60%) | 10/15 (67%) | 19/30 (63%) |
Black Background | Color Augmentation | ||||||
---|---|---|---|---|---|---|---|
Large Vessel | Medium Vessel | Small Vessel | Large Vessel | Medium Vessel | Small Vessel | ||
Rater 1 | Outer margin | 1.1 | 1.1 | 1.3 | 1.4 | 1.8 | 2.1 |
Diameter consistency | 1.0 | 1.5 | 1.5 | 1.3 | 1.3 | 1.9 | |
Separability | 0.1 | 0.4 | 1.0 | 0.3 | 0.5 | 0.6 | |
Rater 2 | Outer margin | 1.4 | 1.6 | 1.9 | 1.3 | 1.3 | 2.8 |
Diameter consistency | 1.5 | 1.8 | 2.3 | 1.9 | 2.4 | 2.4 | |
Separability | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
Rater 3 | Outer margin | 1.0 | 1.1 | 1.3 | 1.0 | 1.1 | 1.6 |
Diameter consistency | 1.0 | 1.1 | 1.0 | 1.0 | 1.1 | 1.3 | |
Separability | 0.7 | 0.8 | 1.0 | 0.4 | 0.8 | 0.8 | |
Rater 4 | Outer margin | 1.5 | 1.6 | 2.1 | 1.1 | 1.3 | 2.0 |
Diameter consistency | 1.5 | 1.6 | 2.6 | 1.5 | 1.8 | 1.9 | |
Separability | 1.0 | 1.0 | 1.0 | 0.4 | 0.5 | 0.9 | |
Total Average | Outer margin | 1.3 | 1.4 | 1.6 | 1.2 | 1.3 | 2.1 |
Diameter consistency | 1.3 | 1.5 | 1.8 | 1.4 | 1.6 | 1.9 | |
Separability | 0.7 | 0.8 | 1.0 | 0.5 | 0.7 | 0.8 |
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Yoon, J.T.; Lee, K.M.; Oh, J.-H.; Kim, H.-G.; Jeong, J.W. Insights and Considerations in Development and Performance Evaluation of Generative Adversarial Networks (GANs): What Radiologists Need to Know. Diagnostics 2024 , 14 , 1756. https://doi.org/10.3390/diagnostics14161756
Yoon JT, Lee KM, Oh J-H, Kim H-G, Jeong JW. Insights and Considerations in Development and Performance Evaluation of Generative Adversarial Networks (GANs): What Radiologists Need to Know. Diagnostics . 2024; 14(16):1756. https://doi.org/10.3390/diagnostics14161756
Yoon, Jeong Taek, Kyung Mi Lee, Jang-Hoon Oh, Hyug-Gi Kim, and Ji Won Jeong. 2024. "Insights and Considerations in Development and Performance Evaluation of Generative Adversarial Networks (GANs): What Radiologists Need to Know" Diagnostics 14, no. 16: 1756. https://doi.org/10.3390/diagnostics14161756
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We, the APA Style team, are not robots. We can all pass a CAPTCHA test , and we know our roles in a Turing test . And, like so many nonrobot human beings this year, we’ve spent a fair amount of time reading, learning, and thinking about issues related to large language models, artificial intelligence (AI), AI-generated text, and specifically ChatGPT . We’ve also been gathering opinions and feedback about the use and citation of ChatGPT. Thank you to everyone who has contributed and shared ideas, opinions, research, and feedback.
In this post, I discuss situations where students and researchers use ChatGPT to create text and to facilitate their research, not to write the full text of their paper or manuscript. We know instructors have differing opinions about how or even whether students should use ChatGPT, and we’ll be continuing to collect feedback about instructor and student questions. As always, defer to instructor guidelines when writing student papers. For more about guidelines and policies about student and author use of ChatGPT, see the last section of this post.
Quoting or reproducing the text created by ChatGPT in your paper
If you’ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or in a comparable section of your paper. For literature reviews or other types of essays or response or reaction papers, you might describe how you used the tool in your introduction. In your text, provide the prompt you used and then any portion of the relevant text that was generated in response.
Unfortunately, the results of a ChatGPT “chat” are not retrievable by other readers, and although nonretrievable data or quotations in APA Style papers are usually cited as personal communications , with ChatGPT-generated text there is no person communicating. Quoting ChatGPT’s text from a chat session is therefore more like sharing an algorithm’s output; thus, credit the author of the algorithm with a reference list entry and the corresponding in-text citation.
When prompted with “Is the left brain right brain divide real or a metaphor?” the ChatGPT-generated text indicated that although the two brain hemispheres are somewhat specialized, “the notation that people can be characterized as ‘left-brained’ or ‘right-brained’ is considered to be an oversimplification and a popular myth” (OpenAI, 2023).
OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat
You may also put the full text of long responses from ChatGPT in an appendix of your paper or in online supplemental materials, so readers have access to the exact text that was generated. It is particularly important to document the exact text created because ChatGPT will generate a unique response in each chat session, even if given the same prompt. If you create appendices or supplemental materials, remember that each should be called out at least once in the body of your APA Style paper.
When given a follow-up prompt of “What is a more accurate representation?” the ChatGPT-generated text indicated that “different brain regions work together to support various cognitive processes” and “the functional specialization of different regions can change in response to experience and environmental factors” (OpenAI, 2023; see Appendix A for the full transcript).
Creating a reference to ChatGPT or other AI models and software
The in-text citations and references above are adapted from the reference template for software in Section 10.10 of the Publication Manual (American Psychological Association, 2020, Chapter 10). Although here we focus on ChatGPT, because these guidelines are based on the software template, they can be adapted to note the use of other large language models (e.g., Bard), algorithms, and similar software.
The reference and in-text citations for ChatGPT are formatted as follows:
- Parenthetical citation: (OpenAI, 2023)
- Narrative citation: OpenAI (2023)
Let’s break that reference down and look at the four elements (author, date, title, and source):
Author: The author of the model is OpenAI.
Date: The date is the year of the version you used. Following the template in Section 10.10, you need to include only the year, not the exact date. The version number provides the specific date information a reader might need.
Title: The name of the model is “ChatGPT,” so that serves as the title and is italicized in your reference, as shown in the template. Although OpenAI labels unique iterations (i.e., ChatGPT-3, ChatGPT-4), they are using “ChatGPT” as the general name of the model, with updates identified with version numbers.
The version number is included after the title in parentheses. The format for the version number in ChatGPT references includes the date because that is how OpenAI is labeling the versions. Different large language models or software might use different version numbering; use the version number in the format the author or publisher provides, which may be a numbering system (e.g., Version 2.0) or other methods.
Bracketed text is used in references for additional descriptions when they are needed to help a reader understand what’s being cited. References for a number of common sources, such as journal articles and books, do not include bracketed descriptions, but things outside of the typical peer-reviewed system often do. In the case of a reference for ChatGPT, provide the descriptor “Large language model” in square brackets. OpenAI describes ChatGPT-4 as a “large multimodal model,” so that description may be provided instead if you are using ChatGPT-4. Later versions and software or models from other companies may need different descriptions, based on how the publishers describe the model. The goal of the bracketed text is to briefly describe the kind of model to your reader.
Source: When the publisher name and the author name are the same, do not repeat the publisher name in the source element of the reference, and move directly to the URL. This is the case for ChatGPT. The URL for ChatGPT is https://chat.openai.com/chat . For other models or products for which you may create a reference, use the URL that links as directly as possible to the source (i.e., the page where you can access the model, not the publisher’s homepage).
Other questions about citing ChatGPT
You may have noticed the confidence with which ChatGPT described the ideas of brain lateralization and how the brain operates, without citing any sources. I asked for a list of sources to support those claims and ChatGPT provided five references—four of which I was able to find online. The fifth does not seem to be a real article; the digital object identifier given for that reference belongs to a different article, and I was not able to find any article with the authors, date, title, and source details that ChatGPT provided. Authors using ChatGPT or similar AI tools for research should consider making this scrutiny of the primary sources a standard process. If the sources are real, accurate, and relevant, it may be better to read those original sources to learn from that research and paraphrase or quote from those articles, as applicable, than to use the model’s interpretation of them.
We’ve also received a number of other questions about ChatGPT. Should students be allowed to use it? What guidelines should instructors create for students using AI? Does using AI-generated text constitute plagiarism? Should authors who use ChatGPT credit ChatGPT or OpenAI in their byline? What are the copyright implications ?
On these questions, researchers, editors, instructors, and others are actively debating and creating parameters and guidelines. Many of you have sent us feedback, and we encourage you to continue to do so in the comments below. We will also study the policies and procedures being established by instructors, publishers, and academic institutions, with a goal of creating guidelines that reflect the many real-world applications of AI-generated text.
For questions about manuscript byline credit, plagiarism, and related ChatGPT and AI topics, the APA Style team is seeking the recommendations of APA Journals editors. APA Style guidelines based on those recommendations will be posted on this blog and on the APA Style site later this year.
Update: APA Journals has published policies on the use of generative AI in scholarly materials .
We, the APA Style team humans, appreciate your patience as we navigate these unique challenges and new ways of thinking about how authors, researchers, and students learn, write, and work with new technologies.
American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000
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The primary objective of this research was to determine the impact of training and development on employee performance, using Garissa County Referral Hospital in Kenya as a case study.
PDF | On May 19, 2018, Radhika Kapur published Training and Development | Find, read and cite all the research you need on ResearchGate
A formal training and development program is a preplanned method that includes performance evaluations and learning solutions that can be completed during work hours or outside work for a ...
In general, little human resource development occurs in small businesses (Hill & Stewart, 1999). In summary, a slowly growing number of authors are currently doing more research in the areas of training and development and its effects on employees that we have not seen in past literature.
Tannenbaum S. I. (2002). A strategic view of organizational training and learning. In Kraiger K. (Ed.), Creating, implementing, and maintaining effective training and development: State-of-the-art lessons for practice (pp. 10-52). San Francisco, CA: Jossey-Bass.
This chapter addresses the current state of research on training effectiveness in organisations. It summarises the key findings on what we know about training effectiveness, the research emphasis given to different components of the model, and how research informs the ways in which organisations should approach learning and development to maximise effectiveness.
Day, D., Bastardoz, N., Bisbey, T., Reyes, D., & Salas, E. (2021). Unlocking human potential through leadership training & development initiatives. Behavioral Science & Policy, 7(1), 41-54. The release of human possibilities is one of the most basic of social objectives and leadership goals. —John W. Gardner, American public servant and ...
Training and development research has a long tradition within applied psychology dating back to the early 1900s. Over the years, not only has interest in the topic grown but there have been dramatic changes in both the science and practice of training and development. In the current article, we examine the evolution of training and development research using articles published in the Journal ...
1468-2419. 1360-3736. As a global forum for training and development, the International Journal of Training and Development addresses important strategies for major societal, organisational and individual challenges within the discipline. Our research is aimed at the academic and wider communities, as well as those engaged in public policy ...
The article focuses on the relationship between the use of employee training and development and the competency-based approach. The objective of this article is to evaluate the use of the competency-based approach in employee training and development in organisations in the Czech Republic based on long-term research (n = 1,360) since the year ...
Employee performance impacts the bottom line of an organization. For this reason, it is the responsibility of organizational leaders to be aware of the importance of training and development's impact on the performance and evaluation of employees. Employee training and development assists the organization and employees in attaining diverse goals, such as improving morale, sense of security ...
When it comes to Oman Air, a training and development plan must be established before it can be properly executed. According to the findings of the study, there is a positive relationship between training and development and employee performance. Keywords: employee, training and development, Covid-19, pandemic.
The paper concludes with directions for future research by applying different level of analysis on exploring the impact of training practices on employee productivity.
KCES Institute of Management & Research, Jalgaon Abstract This paper presents a systematic literature review that explores the impact of employee training and development on organizational efficiency and effectiveness. ... development. Training evaluation can provide feedback on the effectiveness of training programs, identify areas ...
Abstract. The aim of this study is to investigate the relationship between training and development with organizational effectiveness. The research data is collected by developing questionnaire, the research is of qualitative method which tends to address the quality of things in a depth rather than numerical data about the questionnaire , its composed of two parts, the first one interested in ...
The purpose of this research is to investigate the impact of training and development as well as career planning in Nepalese service sector organizations. Data for this study were gathered from service organizations such as banks, insurance companies, telecommunications companies, hospitals, and colleges.
Training and development research has a long tradition within applied psychology dating back to the early 1900's. Over the years, not only has interest in the topic grown but there have been dramatic changes in both the science and practice of training and development. In the current article, we examine the evolution of training and ...
The research questions for the study were as follows: 1) Determine the role of training and development in relation to job performance among ministry employees; 2) Investigate whether training and development affect public service delivery; and 3) Identify methods for implementing training and development to improve job performance.
During the development phase, training design must be piloted to ensure the content is understandable and applicable to the learners. ... Benefits of employee training: McNamara (2016) The research question could help improve the existing practice, but it differs on the variables of the current study. ... He has published various research ...
This research is expected to be a reference for next research on HR training and development. Discover the world's research. ... This paper describes the development, implementation and impact of ...
Employees without proper training and development lack a firm to grasp on their duties and responsibilities. Training and development, according to (Shaw, 2011) is a process that provides employees with skills, information and understanding of the organization and its goals. Training and development helps employees in
International Journal of Training and Development: Volume 28, Issue 3. Pages: 255-384. September 2024. Previous Issue. GO TO SECTION. Export Citation(s) Export Citations. Format. Plain Text. RIS (ProCite, Reference Manager) ... RESEARCH ARTICLE. no. How orientation training socializes newcomers: The mediating role of learning in reducing ...
ompetency and to survive in a dynamic business environment. This study was conducted with the aim to investigate the effectiveness of training and d. velopment on employee performance at JK Pap. r Ltd, Songadh. The research employed descriptive analysis. Primary data was collected through distributing questionnaires to 100 employe.
The rapid development of deep learning in medical imaging has significantly enhanced the capabilities of artificial intelligence while simultaneously introducing challenges, including the need for vast amounts of training data and the labor-intensive tasks of labeling and segmentation. Generative adversarial networks (GANs) have emerged as a solution, offering synthetic image generation for ...
PDF | On Mar 16, 2019, Ravikant BALKRISHNA Sangurde published TRAINING AND DEVELOPMENT: PROCESS, TYPES AND IMPACT | Find, read and cite all the research you need on ResearchGate
In this post, I discuss situations where students and researchers use ChatGPT to create text and to facilitate their research, not to write the full text of their paper or manuscript. We know instructors have differing opinions about how or even whether students should use ChatGPT, and we'll be continuing to collect feedback about instructor ...