The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research

Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics

Kaugeranna, R., Kaugeranna, E., & Aion, (. S. 4. 6. (2023) · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · doi:10.4230/lipics.giscience.2023.43 · Cited by 13,695 · see citing works

Machine learning: Trends, perspectives, and prospects

Jordan, M. I., & Mitchell, T. M. (2015) · Science · doi:10.1126/science.aaa8415 · Cited by 9,955 · see citing works

Systematic review of research on artificial intelligence applications in higher education – where are the educators?

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242 · see citing works

Mental disorders among college students in the World Health Organization World Mental Health Surveys

Auerbach, R. P., Alonso, J., Axinn, W. G., Cuijpers, P., Ebert, D. D., Green, J. G., Hwang, I., Kessler, R. C., Liu, H., Mortier, P., et al. (2016) · Psychological Medicine · doi:10.1017/s0033291716001665 · Cited by 1,587 · see citing works

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

Sarker, I. H. (2022) · SN Computer Science · doi:10.1007/s42979-022-01043-x · Cited by 1,208 · see citing works

Large language models generate functional protein sequences across diverse families

Madani, A., Krause, B., Greene, E. R., Subramanian, S., Mohr, B. P., Holton, J. M., Olmos, J. L., Xiong, C., Sun, Z. Z., Socher, R., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01618-2 · Cited by 1,078 · see citing works

Bias in peer review

Lee, C. J., Sugimoto, C. R., Zhang, G., & Cronin, B. (2013) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22784 · Cited by 1,000 · see citing works

Artificial intelligence for mental health and mental illnesses: an overview

Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H.-C., & Jeste, D. V. (2019) · Current Psychiatry Reports · doi:10.1007/s11920-019-1094-0 · Cited by 970 · see citing works

ChatGPT listed as author on research papers: many scientists disapprove

Stokel-Walker, C. (2023) · Nature · doi:10.1038/d41586-023-00107-z · Cited by 868 · see citing works

The role of AI in drug discovery: challenges, opportunities, and strategies

Blanco-González, A., Cabezón, A., Seco-González, A., Conde-Torres, D., Antelo-Riveiro, P., Piñeiro, Á., & Garcia-Fandino, R. (2023) · Pharmaceuticals · doi:10.3390/ph16060891 · Cited by 690 · see citing works

Introducing artificial intelligence training in medical education

Paranjape, K., Schinkel, M., Nannan Panday, R., Car, J., & Nanayakkara, P. (2019) · JMIR Medical Education · doi:10.2196/16048 · Cited by 634 · see citing works

ChatGPT - Reshaping medical education and clinical management

Khan, R. A., Jawaid, M., Khan, A. R., & Sajjad, M. (2023) · Pakistan Journal of Medical Sciences · doi:10.12669/pjms.39.2.7653 · Cited by 628 · see citing works

Human- versus Artificial Intelligence

Korteling, J. E. (., van de Boer-Visschedijk, G. C., Blankendaal, R. A. M., Boonekamp, R. C., & Eikelboom, A. R. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.622364 · Cited by 619 · see citing works

The benefits and challenges of chatgpt: An overview

Deng, J., & Lin, Y. (2023) · Frontiers in Computing and Intelligent Systems · doi:10.54097/fcis.v2i2.4465 · Cited by 611 · see citing works

Reviewer bias in single- versus double-blind peer review

Tomkins, A., Zhang, M., & Heavlin, W. D. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707323114 · Cited by 605 · see citing works

Tools such as ChatGPT threaten transparent science; here are our ground rules for their use

(2023) · Nature · doi:10.1038/d41586-023-00191-1 · Cited by 605 · see citing works

Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse?

O’Connor, S., & ChatGPT (2023) · Nurse Education in Practice · doi:10.1016/j.nepr.2022.103537 · Cited by 585 · see citing works

Machine learning and natural language processing in mental health: systematic review

Le Glaz, A., Haralambous, Y., Kim-Dufor, D.-H., Lenca, P., Billot, R., Ryan, T. C., Marsh, J., DeVylder, J., Walter, M., Berrouiguet, S., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/15708 · Cited by 576 · see citing works

The limitations to our understanding of peer review

Tennant, J. P., & Ross-Hellauer, T. (2020) · Research Integrity and Peer Review · doi:10.1186/s41073-020-00092-1 · Cited by 384 · see citing works

CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities

Lee, M., Liang, P., & Yang, Q. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502030 · Cited by 345 · see citing works

The impact of artificial intelligence on human society and bioethics

Tai, M. C.-T. (2020) · Tzu Chi Medical Journal · doi:10.4103/tcmj.tcmj_71_20 · Cited by 326 · see citing works

Plagiarism in the age of massive generative pre-trained transformers (GPT-3)

Dehouche, N. (2021) · Ethics in Science and Environmental Politics · doi:10.3354/esep00195 · Cited by 296 · see citing works

Using AI to write scholarly publications

Hosseini, M., Rasmussen, L. M., & Resnik, D. B. (2024) · Accountability in Research · doi:10.1080/08989621.2023.2168535 · Cited by 286 · see citing works

Artificial Intelligence in Pharmaceutical and Healthcare Research

Bhattamisra, S. K., Banerjee, P., Gupta, P., Mayuren, J., Patra, S., & Candasamy, M. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7010010 · Cited by 283 · see citing works

ChatGPT passing USMLE shines a spotlight on the flaws of medical education

Mbakwe, A. B., Lourentzou, I., Celi, L. A., Mechanic, O. J., & Dagan, A. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000205 · Cited by 273 · see citing works

Fighting reviewer fatigue or amplifying bias? Considerations and recommendations for use of ChatGPT and other large language models in scholarly peer review

Hosseini, M., & Horbach, S. P. J. M. (2023) · Research Integrity and Peer Review · doi:10.1186/s41073-023-00133-5 · Cited by 243 · see citing works

Speeding up to keep up: exploring the use of AI in the research process

Chubb, J., Cowling, P., & Reed, D. (2022) · AI & SOCIETY · doi:10.1007/s00146-021-01259-0 · Cited by 218 · see citing works

Making better career decisions: From challenges to opportunities

Gati, I., & Kulcsár, V. (2021) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2021.103545 · Cited by 216 · see citing works

Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Crothers, E. N., Japkowicz, N., & Viktor, H. L. (2023) · IEEE Access · doi:10.1109/access.2023.3294090 · Cited by 196 · see citing works

AI chatbots not yet ready for clinical use

Yeung, J. A., Kraljevic, Z., Luintel, A., Balston, A., Idowu, E., Dobson, R. J., & Teo, J. T. (2023) · doi:10.1101/2023.03.02.23286705 · Cited by 176 · see citing works

AI chatbots not yet ready for clinical use.

Au Yeung, J., Kraljevic, Z., Luintel, A., Balston, A., Idowu, E., Dobson, R. J., & Teo, J. T. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1161098 · Cited by 176 · see citing works

Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes

Grunhut, J., Wyatt, A. T., & Marques, O. (2021) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205211036836 · Cited by 161 · see citing works

Using ChatGPT to conduct a literature review

Haman, M., & Školník, M. (2024) · Accountability in Research · doi:10.1080/08989621.2023.2185514 · Cited by 144 · see citing works

Artificial Intelligence for Career Guidance – Current Requirements and Prospects for the Future

Westman, S., Kauttonen, J., Klemetti, A., Korhonen, N., Manninen, M., Mononen, A., Niittymäki, S., & Paananen, H. (2021) · IAFOR Journal of Education · doi:10.22492/ije.9.4.03 · Cited by 111 · see citing works

Can an artificial intelligence chatbot be the author of a scholarly article?

Lee, J. Y. (2023) · Journal of Educational Evaluation for Health Professions · doi:10.3352/jeehp.2023.20.6 · Cited by 108 · see citing works

Best Practices for Using AI When Writing Scientific Manuscripts

Buriak, J. M., Akinwande, D., Artzi, N., Brinker, C. J., Burrows, C. J., Chan, W. C. W., Chen, C., Chen, X., Chhowalla, M., Chi, L., et al. (2023) · ACS Nano · doi:10.1021/acsnano.3c01544 · Cited by 106 · see citing works

Demystifying artificial intelligence in pharmacy

Nelson, S. D., Walsh, C. G., Olsen, C. A., McLaughlin, A. J., LeGrand, J., Schutz, N., & Lasko, T. A. (2020) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/zxaa218 · Cited by 87 · see citing works

Bridging the skill gap between the acquired university curriculum and the requirements of the job market: A data-driven analysis of scientific literature

Aljohani, N. R., Aslam, M. A., Khadidos, A. O., & Hassan, S. (2022) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2022.100190 · Cited by 81 · see citing works

Is the future of peer review automated?

Schulz, R., Barnett, A., Bernard, R., Brown, N. J. L., Byrne, J. A., Eckmann, P., Gazda, M. A., Kilicoglu, H., Prager, E. M., Salholz-Hillel, M., et al. (2022) · BMC Research Notes · doi:10.1186/s13104-022-06080-6 · Cited by 80 · see citing works

Artificial Intelligence in Psychiatry

Fakhoury, M. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-981-32-9721-0_6 · Cited by 77 · see citing works

(Re)Introducing Vygotsky’s Thought: From Historical Overview to Contemporary Psychology

Vasileva, O. V., & Balyasnikova, N. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01515 · Cited by 73 · see citing works

Artificial Intelligence-Assisted Bioinformatics, Microneedle, and Diabetic Wound Healing: A “New Deal” of an Old Drug

Xue, Y., Chen, C., Tan, R., Zhang, J., Fang, Q., Jin, R., Mi, X., Sun, D., Xue, Y., Wang, Y., et al. (2022) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.2c08994 · Cited by 64 · see citing works

Fighting reviewer fatigue or amplifying bias? Considerations and recommendations for use of ChatGPT and other Large Language Models in scholarly peer reviewPreprint

Hosseini, M., & Horbach, S. (2023) · Research Square · doi:10.21203/rs.3.rs-2587766/v1 · Cited by 43 · see citing works

SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Manakul, P., Liusie, A., & Gales, M. J. F. (2023) · arXiv · doi:10.48550/arxiv.2303.08896 · Cited by 38 · see citing works

Exploring Students’ Use of a Mobile Application to Support Their Self-Regulated Learning Processes

Baars, M., Khare, S., & Ridderstap, L. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.793002 · Cited by 36 · see citing works

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

D’Agostino, D., Clematis, A., Quarati, A., Cesini, D., Chiappori, F., Milanesi, L., & Ivan Merelli, A. (2013) · BioMed Research International · doi:10.1155/2013/138012 · Cited by 34 · see citing works

A hybrid scheme for Automated Essay Grading based on LVQ and NLP techniques

Shehab, A., Elhoseny, M., & Hassanien, A. (2016) · International Computer Engineering Conference · doi:10.1109/icenco.2016.7856447 · Cited by 32 · see citing works

Align My Curriculum: A Framework to Bridge the Gap between Acquired University Curriculum and Required Market Skills

Almaleh, A. I., Aslam, M. A., Saeedi, K., et al. (2019) · Sustainability · doi:10.3390/su11092607 · Cited by 31 · see citing works

An Agile Digital Platform to Support Population Health—A Case Study of a Digital Platform to Support Patients with Delirium Using IoT, NLP, and AI

Tanniru, M. R., Agarwal, N., Sokan, A. E., & Hariri, S. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18115686 · Cited by 29 · see citing works

Prior and Prejudice

Stelmakh, I., Shah, N. B., Singh, A., & Daumé, H. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449149 · Cited by 22 · see citing works

Dynamic NLP Enabled Chatbot for Rural Health Care in India

S, A. S., Rajalakshmi, N. R., Victer Paul., P., et al. (2022) · doi:10.1109/iccsea54677.2022.9936389 · Cited by 22 · see citing works

Empowering Beginners in Bioinformatics with ChatGPTPreprint

Shue, E., Liu, L., Li, B., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.07.531414 · Cited by 22 · see citing works

Data Science Curriculum Design: A Case Study

Hassan, I. B., Ghanem, T. M., Jacobson, D., et al. (2021) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3408877.3432443 · Cited by 21 · see citing works

Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization

(2020) · doi:10.1145/3386392 · Cited by 20 · see citing works

Role of Artificial Intelligence and Machine Learning in Bioinformatics: Drug Discovery and Drug RepurposingPreprint

Quazi, S. (2021) · Preprints.org · doi:10.20944/preprints202105.0346.v1 · Cited by 19 · see citing works

NLPeer: A Unified Resource for the Computational Study of Peer Review

Dycke, N., Kuznetsov, I., & Gurevych, I. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2023.acl-long.277 · Cited by 19 · see citing works

Editorial: Artificial Intelligence in Bioinformatics and Drug Repurposing: Methods and Applications

Zheng, P., Wang, S., Wang, X., & Zeng, X. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.870795 · Cited by 18 · see citing works

Searching for essential genes and drug discovery in breast cancer and periodontitis via text mining and bioinformatics analysis

Luo, L., Zheng, W., Chen, C., & Sun, S. (2021) · Anti-Cancer Drugs · doi:10.1097/cad.0000000000001108 · Cited by 17 · see citing works

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer

Alkaitis, M. S., Agrawal, M., Riely, G. J., Razavi, P., & Sontag, D. A. (2021) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00139 · Cited by 14 · see citing works

The New Paradigms In Education and Support of Critical Thinking with Artificial Intelligence (AI) Tools

Kouzov, O. (2019) · Serdica Journal of Computing · doi:10.55630/sjc.2019.13.27-40 · Cited by 13 · see citing works

Chemical Structure Databases in Drug Discovery

Gupta, P. P., Bastikar, V. A., & Chhajed, S. S. (2018) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-5225-7326-5.ch002 · Cited by 5 · see citing works

Gene Expression, Network Analysis, and Drug Discovery of Neurofibromatosis Type 2-Associated Vestibular Schwannomas Based on Bioinformatics Analysis

Huang, Q., Zhai, S., Liao, X., et al. (2020) · Journal of Oncology · doi:10.1155/2020/5976465 · Cited by 5 · see citing works

HELTRAK - A Medical Application with Chatbot Based on AI

SureshKumar, M., Niranjan Kumar, S., Chris Joel, S., et al. (2022) · 2022 1st International Conference on Computational Science and Technology (ICCST) · doi:10.1109/iccst55948.2022.10040438 · Cited by 4 · see citing works

Research on the Application of AI in the Field of Education Big Data Mining

Zhao, W. Z., Wang, Z., & Zhu, L. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1992/3/032091 · Cited by 3 · see citing works

Automated Essay Grading System using NLP Techniques

Shetty, P., Yadav, K., & Kunder, P. (2020) · International Journal of Engineering and Advanced Technology · doi:10.35940/ijeat.e9880.069520 · Cited by 3 · see citing works

Mitigating Socio-lingustic Bias in Job Recommendation

Deshpande, K. V., Pan, S., & Foulds, J. R. (2020) · Maryland Shared Open Access Repository (USMAI Consortium) · doi:10.13016/m2kdhx-zene · Cited by 2 · see citing works

Using Natural Language Processing to Explore Mental Health Insights From UK Tweets During the COVID-19 Pandemic: Infodemiology Study (Preprint)Preprint

Marshall, C., Lanyi, K., Green, R., et al. (2021) · doi:10.2196/preprints.32449 · Cited by 2 · see citing works

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study (Preprint)Preprint

Elkin, P. L., Mullin, S., Mardekian, J., et al. (2021) · doi:10.2196/preprints.28946 · Cited by 1 · see citing works

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., Badreldin, H. A., et al. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04698-z · Cited by 3,146 · see citing works

Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis

Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784 · see citing works

Impact of AI assistance on student agency

Darvishi, A., Khosravi, H., Sadiq, S., Gašević, D., & Siemens, G. (2024) · Computers & Education · doi:10.1016/j.compedu.2023.104967 · Cited by 548 · see citing works

Artificial intelligence and social media on academic performance and mental well-being: student perceptions of positive impact in the age of smart learning

Shahzad, M. F., Xu, S., Lim, W. M., Yang, X., & Khan, Q. R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e29523 · Cited by 205 · see citing works

INSTITUTIONAL POLICIES ON ARTIFICIAL INTELLIGENCE IN UNIVERSITY LEARNING, TEACHING AND RESEARCH

Spivakovsky, O. V., Omelchuk, S. A., Kobets, V. V., Valko, N. V., & Malchykova, D. S. (2023) · Information Technologies and Learning Tools · doi:10.33407/itlt.v97i5.5395 · Cited by 73 · see citing works

Perceived institutional support and its effects on student perceptions of AI learning in higher education: the role of mediating perceived learning outcomes and moderating technology self-efficacy

Jeilani, A., & Abubakar, S. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1548900 · Cited by 64 · see citing works

Assessing the accuracy and consistency of ChatGPT in clinical pharmacy management: a preliminary analysis with clinical pharmacy experts worldwide

Al-Dujaili, Z., Omari, S., Pillai, J., & Al Faraj, A. (2023) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2023.08.012 · Cited by 56 · see citing works

Artificial Intelligence in Higher Education: Enhancing Learning Systems and Transforming Educational Paradigms

Imran, M., Almusharraf, N., Abdellatif, M. S., & Abbasova, M. Y. (2024) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v18i18.49143 · Cited by 51 · see citing works

Psychometric properties of the persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS).

Moodi Ghalibaf, A., Moghadasin, M., Emadzadeh, A., & Mastour, H. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04553-1 · Cited by 29 · see citing works

A qualitative survey on perception of medical students on the use of large language models for educational purposes

Mondal, H., Karri, J. K. K., Ramasubramanian, S., Mondal, S., Juhi, A., & Gupta, P. (2025) · Advances in Physiology Education · doi:10.1152/advan.00088.2024 · Cited by 28 · see citing works

Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity

Ncube, P. D. N., Dzvapatsva, G. P., Matobobo, C., & Ranga, M. M. (2026) · AI and Ethics · doi:10.1007/s43681-025-00871-w · Cited by 31 · see citing works

Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review

Amankwaa, I., Ekpor, E., Cudjoe, D., Kobiah, E., Fuseini, A.-K. J., Diebieri, M., Gyamfi, S., & Brownie, S. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106822 · Cited by 20 · see citing works

Evaluating generative artificial intelligence adoption in management education using AI–human augmentation and expectation confirmation theory

Kumar, A., Baijal, A., & Kharat, M. (2025) · Journal of International Education in Business · doi:10.1108/jieb-07-2024-0086 · Cited by 6 · see citing works

When the Robotic Maths Tutor is Wrong - Can Children Identify Mistakes Generated by ChatGPT?

Helal, M., Holthaus, P., Wood, L., Velmurugan, V., Lakatos, G., Moros, S., & Amirabdollahian, F. (2024) · 2024 5th International Conference on Artificial Intelligence, Robotics and Control (AIRC) · doi:10.1109/airc61399.2024.10672220 · Cited by 6 · see citing works

Fluency Illusion: A Review on Influence of ChatGPT in Classroom Settings

Kumar, S., Mikayelyan, A., & Vorfolomeyeva, O. (2026) · Information · doi:10.3390/info17030299 · Cited by 11 · see citing works

Triadic fusion: investigating the educational impact of AI, AR, and NLP integration in creating immersive and conversational learning environments

Samala, A. D., & Rawas, S. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2025.2554987 · Cited by 5 · see citing works

Exploring the integration of AI and national quality courses in China: a study on teaching practices in nursing smart education

Jing, Z., & Mouhong, Z. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08289-y · Cited by 4 · see citing works

The Design of Curriculum Structure in the Synthesis of School Curriculum

Nian-jin, D. (2008) · Curriculum，Teaching Material and Method

The Teachers' Curriculum Identity: An Issue Needs Further Study

Xiao-lian, H. (2011) · Teacher Education Research

Postgraduates' Curriculum-selecting Intention and System Reform

De-xia, G. (2009) · Journal of University of Science and Technology Beijing(Social Sciences Edition)

Comparative analysis of the 2019 revised Nuri curriculum and the Japanese kindergarten curriculum

Shin, M. H., & Jang, S. O. (2023) · Korean Association For Learner-Centered Curriculum And Instruction · doi:10.22251/jlcci.2023.23.6.347

On the Paradigm Change of Physical Education Curriculum: the Analysis of Three Typical PE Curriculum Models

Yuan-yan, G. (2004) · China Sports