Artificial intelligence technologies, in-person and online learning in higher education: A review of the impact on perceptual features, psychological climate and academic performance
- Авторлар: Ulyanina O.A.1,2, Vikhrova E.N.2
-
Мекемелер:
- Moscow State University of Psychology & Education
- Moscow Institute of Physics and Technology (National Research University)
- Шығарылым: Том 22, № 2 (2025)
- Беттер: 337-360
- Бөлім: PERSONALITY IN CONTEMPORARY EDUCATIONAL ENVIRONMENT
- URL: https://journal-vniispk.ru/2313-1683/article/view/365331
- DOI: https://doi.org/10.22363/2313-1683-2025-22-2-337-360
- EDN: https://elibrary.ru/VDDJBF
- ID: 365331
Дәйексөз келтіру
Толық мәтін
Аннотация
Rapid digitalization of higher education and the rise of artificial intelligence (AI) in instruction call for careful evaluation of their impact on students. Traditional face-to-face lectures and those given by an AI-avatar, remote online courses, each create distinct conditions that shape the classroom psychological climate and comfort. Prior research shows AI integration increases engagement, but comparative evidence on comfort, performance, and perception across formats remains limited. The purpose of this review is to examine students’ perceptions of three instructional formats (in-person, online, AI-avatar lectures), their impact on class psychological climate and academic performance, and the risks and prospects of AI use in higher education. This narrative review synthesizes literature on AI applications in higher education over approximately the past seven years, drawing on Russian (RSCI, eLIBRARY) and international (Scopus, Web of Science) databases, as well as relevant reports and surveys. Empirical studies (2018–2025, Russian/English) comparing pedagogical formats or assessing AI’s impact on students were included, while incomplete reports, duplicates, and irrelevant works were excluded. Review findings indicate that most students rated face-to-face instruction as most comfortable, though well-designed online courses and realistic avatar lectures yielded comparable satisfaction. No single format was universally superior; instructional effectiveness depended on contextual factors. Online learning outcomes varied; in some cases they equaled or exceeded in-person results. Early studies of AI-avatar lectures showed neutral-to-positive reception, noting clear speech and accessibility. The presence of a virtual instructor positively influenced satisfaction, and visual feedback proved more effective than text-only interaction. Students’ digital literacy facilitated adaptation, while skill gaps or low trust contributed to anxiety. Risks included reduced live communication, limited avatar authenticity, academic dishonesty, and ethical concerns. Overall, AI-avatars and digital technologies can enhance interactivity and flexibility in higher education but cannot fully replace live human contact. Therefore, a balanced, human-centered implementation that accounts for psychological factors is recommended.
Авторлар туралы
Olga Ulyanina
Moscow State University of Psychology & Education; Moscow Institute of Physics and Technology (National Research University)
Хат алмасуға жауапты Автор.
Email: ulyaninaoa@mgppu.ru
ORCID iD: 0000-0001-9300-4825
SPIN-код: 9283-7824
Scopus Author ID: 57207950411
ResearcherId: AAF-2050-2020
Doctor of Psychology, Associate Professor, Head of the Federal Coordination Center for the Development of Psychological and Pedagogical Assistance in the Education System of the Russian Federation, Moscow State University of Psychology & Education; Chief Research Fellow of the Center for Applied Linguistic Research and Testing “ISTOK”, Moscow Institute of Physics and Technology
29 Sretenka St, Moscow, 127051, Russian Federation; 9/3 Institutsky lane, Dolgoprudny, 141701, Russian FederationEkaterina Vikhrova
Moscow Institute of Physics and Technology (National Research University)
Email: vikhrova.en@mipt.ru
ORCID iD: 0009-0006-9233-8894
ResearcherId: MTF-7487-2025
Ph.D. in Philology, Associate Professor, Associate Professor of the Department of Foreign Languages
9/3 Institutsky lane, Dolgoprudny, 141701, Russian FederationӘдебиет тізімі
- Adnan, M., & Anwar, K. (2020). Online learning amid the COVID-19 pandemic: Students perspectives. Journal of Pedagogical Sociology and Psychology, 2(1), 45–51. https://doi.org/10.33902/jpsp.2020261309
- Alarifi, B.N., & Song, S. (2024). Online vs in-person learning in higher education: effects on student achievement and recommendations for leadership. Humanities and Social Sciences Communications, 11(1), 86. https://doi.org/10.1057/s41599-023-02590-1
- Allen, I.E., & Seaman, J. (2017). Digital learning compass: Distance education enrollment report 2017. Wellesley, MA: Babson Survey Research Group.
- Almazova, N., Krylova, E., Rubtsova, A., & Odinokaya, M. (2020). Challenges and opportunities for russian higher education amid COVID-19: Teachers’ perspective. Education Sciences, 10(12), 368. https://doi.org/10.3390/educsci10120368
- Apoki, U.C., Hussein, A.M.A., Al-Chalabi, H.K.M., Badica, C., & Mocanu, M.L. (2022). The role of pedagogical agents in personalised adaptive learning: A review. Sustainability, 14(11), 6442. https://doi.org/10.3390/su14116442
- Audet, É.C., Levine, S.L., Metin, E., Koestner, S., & Barcan, S. (2021). Zooming their way through university: Which Big 5 traits facilitated students’ adjustment to online courses during the COVID-19 pandemic. Personality and Individual Differences, 180, 110969. https://doi.org/10.1016/j.paid.2021.110969
- Bailenson, J.N. (2021). Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. Technology, Mind, and Behavior, 2(1). https://doi.org/10.1037/tmb0000030
- Balkaya, S., & Akkucuk, U. (2021). Adoption and use of learning management systems in education: The role of playfulness and self-management. Sustainability, 13(3), 1127. https://doi.org/10.3390/su13031127
- Bao, W. (2020). COVID-19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies, 2(2), 113–115. https:// doi.org/10.1002/hbe2.191
- Baticulon, R.E., Sy, J.J., Alberto, N.R.I., Baron, M.B.C., Mabulay, R.E.C., Rizada, L.G.T., Tiu, C.J.S., Clarion, C.A., & Reyes, J.C.B. (2021). Barriers to online learning in the time of COVID-19: A national survey of medical students in the Philippines. Medical Science Educator, 31(2), 615–626. https://doi.org/10.1007/s40670-021-01231-z
- Bernard, R.M., Abrami, P.C., Borokhovski, E., Wade, C.A., Tamim, R.M., Surkes, M.A., & Bethel, E.C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289. https:// doi.org/10.3102/0034654309333844
- Bernard, R.M., Abrami, P.C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., Wallet, P.A., Fiset, M., & Huang, B. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379–439. https://doi.org/10.3102/00346543074003379
- Bernard, R.M., Borokhovski, E., Schmid, R.F., Tamim, R.M., & Abrami, P.C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. Journal of Computing in Higher Education, 26(1), 87–122. https:// doi.org/10.1007/s12528-013-9077-3
- Besser, A., Flett, G.L., & Zeigler-Hill, V. (2022). Adaptability to a sudden transition to online learning during the COVID-19 pandemic: Understanding the challenges for students. Scholarship of Teaching and Learning in Psychology, 8(2), 85–105. https:// doi.org/10.1037/stl0000198
- Bond, M., Bedenlier, S., Marín, V.I., & Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18(1), 50. https://doi.org/10.1186/s41239-021-00282-x
- Bondarenko, N.V., Varlamova, T.A., Gokhberg, L.M., Zorina, O.A., Kuznetsova, V.I., Ozerova, O.K., Portnyagina, O.N., Shkaleva, E.V., & Schugal, N.B. (2025). Indicators of Education in the Russian Federation: 2025: Data Book. Moscow: HSE University. (In Russ.) https://doi.org/10.17323/978-5-7598-3030-6
- Bono, R., Núñez-Peña, M.I., Campos-Rodríguez, C., González-Gómez, B., & Quera, V. (2024). Sudden transition to online learning: Exploring the relationships among measures of student experience. International Journal of Educational Research Open, 6, 100332. https://doi.org/10.1016/j.ijedro.2024.100332
- Broadbent, J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. The Internet and Higher Education, 33, 24–32. https:// doi.org/10.1016/j.iheduc.2017.01.004
- Broadbent, J., & Poon, W.L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13. https://doi.org/10.1016/j.iheduc.2015.04.007
- Clark, R.C., & Mayer, R.E. (Eds.). (2016). e-Learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. Hoboken, NJ: John Wiley & Sons, Inc. https://doi.org/10.1002/9781119239086
- Coman, C., Țîru, L.G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M.C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability, 12(24), 10367. https://doi.org/10.3390/su122410367
- Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
- Ferri, F., Grifoni, P., & Guzzo, T. (2020). Online learning and emergency remote teaching: Opportunities and challenges in emergency situations. Societies, 10(4), 86. https:// doi.org/10.3390/soc10040086
- Fu, P., Gao, C., Chen, X., Zhang, Z., Chen, J., & Yang, D. (2024). Proactive personality and its impact on online learning engagement through positive emotions and learning motivation. Scientific Reports, 14(1), 28144. https://doi.org/10.1038/s41598-024-79776-3
- Garris, C.P., & Fleck, B. (2022). Student evaluations of transitioned-online courses during the COVID-19 pandemic. Scholarship of Teaching and Learning in Psychology, 8(2), 119–139. https://doi.org/10.1037/stl0000229
- Garrison, D.R. (2011). E-Learning in the 21st century: A framework for research and practice (2nd ed.). New York: Routledge. https://doi.org/10.4324/9780203838761
- Garrison, D.R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/s1096-7516(00)00016-6
- Hodges, C.B., Moore, S., Lockee, B.B., Trust, T., & Bond, M.A. (2024). The difference between emergency remote teaching and online learning. In T. Martindale, T.B. Amankwatia, L. Cifuentes & A.A. Piña (Eds.), Handbook of research in online learning (pp. 511–522). Leiden: Brill. https://doi.org/10.1163/9789004702813_021
- Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S.B., Santos, O.C., Rodrigo, M.T., Cukurova, M., Bittencourt, I.I., & Koedinger, K.R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1
- Kizilcec, R.F., Pérez-Sanagustín, M., & Maldonado, J.J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104, 18–33. https://doi.org/10.1016/j.compedu.2016.10.001
- Kostikova, L.P., Yesenina, N.Ye., & Olkov, A.S. (2025). Artificial intelligence in the educational environment of the modern university: the results of the student survey. Scientific-Methodological Electronic Journal “Koncept”, (2), 93–109. (In Russ.) https:// doi.org/10.24412/2304-120X-2025-11022
- Lancaster, T., & Cotarlan, C. (2021). Contract cheating by STEM students through a file sharing website: A Covid-19 pandemic perspective. International Journal for Educational Integrity, 17(1), 3. https://doi.org/10.1007/s40979-021-00070-0
- Lowenthal, P.R., & Snelson, C. (2017). In search of a better understanding of social presence: An investigation into how researchers define social presence. Distance Education, 38(2), 141–159. https://doi.org/10.1080/01587919.2017.1324727
- Marinova, M.M. (2022). The influence of the VR environment on the level of anxiety. Experimental Psychology (Russia), 15(2), 49–58. (In Russ.) https://doi.org/10.17759/exppsy.2022150204
- Mayer, R.E. (2020). Multimedia Learning (3rd ed.). Cambridge: Cambridge University Press. https://doi.org/10.1017/9781316941355
- Means, B., Toyama, Y., Murphy, R., Baki, M., & Jones, K. (2010). Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies. Washington, DC: US Department of Education.
- Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record: The Voice of Scholarship in Education, 115(3), 1–47. https://doi.org/10.1177/016146811311500307
- Mishra, L., Gupta, T., & Shree, A. (2020). Online teaching-learning in higher education during lockdown period of COVID-19 pandemic. International Journal of Educational Research Open, 1, 100012. https://doi.org/10.1016/j.ijedro.2020.100012
- OECD. (2021). OECD digital education outlook 2021: Pushing the frontiers with artificial intelligence, blockchain and robots. Paris: OECD Publishing. https:// doi.org/10.1787/589b283f-en
- Oliveira, W., Hamari, J., Joaquim, S., Toda, A.M., Palomino, P.T., Vassileva, J., & Isotani, S. (2022). The effects of personalized gamification on students’ flow experience, motivation, and enjoyment. Smart Learning Environments, 9(1), 16. https://doi.org/10.1186/s40561-022-00194-x
- Osipova, L.B. (2024). Artificial intelligence in education: real opportunities and prospects. PNRPU Sociology and Economics Bulletin, (1), 60–73. (In Russ.) https://doi.org/10.15593/2224-9354/2024.1.5
- Palvia, S., Aeron, P., Gupta, P., Mahapatra, D., Parida, R., Rosner, R., & Sindhi, S. (2018). Online education: Worldwide status, challenges, trends, and implications. Journal of Global Information Technology Management, 21(4), 233–241. https://doi.org/10.1080/1097198x.2018.1542262
- Panigrahi, R., Srivastava, P.R., & Sharma, D. (2018). Online learning: Adoption, continuance, and learning outcome — A review of literature. International Journal of Information Management, 43, 1–14. https://doi.org/10.1016/j.ijinfomgt.2018.05.005
- Pobokin, P.A., Ivchenkova, J.Y., & Kapustina, V.U. (2021). Correction of psychological defenses and anxiety of students using VR training programs. Psychological-Educational Studies, 13(4), 147–161. (In Russ.) https://doi.org/10.17759/psyedu.2021130409
- Polushko, A.O., & Saulenko, N.I. (2021). Influence of distance learning on the psycho-emotional state of students. Forcipe, 4(S1), 711. (In Russ.)
- Radha, R., Mahalakshmi, K., Kumar, V.S., & Saravanakumar, A.R. (2020). E-learning during lockdown of COVID-19 pandemic: A global perspective. International Journal of Control and Automation, 13(4), 1088–1099.
- Rahman, M.M., & Watanobe, Y. (2023). ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783
- Richardson, J.C., Maeda, Y., Lv, J., & Caskurlu, S. (2017). Social presence in relation to students’ satisfaction and learning in the online environment: A meta-analysis. Computers in Human Behavior, 71, 402–417. https://doi.org/10.1016/j.chb.2017.02.001
- Richter, S., Kishore, S., Piven, I., Dodd, P., & Bate, G. (2025). Chatbots in tertiary education: Exploring the impact of warm and competent avatars on self-directed learning. British Journal of Educational Technology, 56(5), 2102–2124. https://doi.org/10.1111/bjet.13610
- Schroeder, N.L., Adesope, O.O., & Gilbert, R.B. (2013). How effective are pedagogical agents for learning? A meta-analytic review. Journal of Educational Computing Research, 49(1), 1–39. https://doi.org/10.2190/ec.49.1.a
- Tan, S.F. (2024). Perceptions of students on artificial intelligence-generated content avatar utilization in learning management system. Asian Association of Open Universities Journal, 19(2), 170–185. https://doi.org/10.1108/aaouj-12-2023-0142
- Ukenova, A., Bekmanova, G., Zaki, N., Kikimbayev, M., & Altaibek, M. (2025). Assessment and improvement of avatar-based learning system: From linguistic structure alignment to sentiment-driven expressions. Sensors, 25(6), 1921. https://doi.org/10.3390/s25061921
- Vallis, C., Wilson, S., Gozman, D., & Buchanan, J. (2024). Student perceptions of AI-generated avatars in teaching business ethics: We might not be impressed. Postdigital Science and Education, 6(2), 537–555. https://doi.org/10.1007/s42438-023-00407-7
- Vo, H.M., Zhu, C., & Diep, N.A. (2017). The effect of blended learning on student performance at course-level in higher education: A meta-analysis. Studies in Educational Evaluation, 53, 17–28. https://doi.org/10.1016/j.stueduc.2017.01.002
- Yarullina, L.R. (2020). Digital learning in higher school: Psychological risks and effects. World of Science. Pedagogy and Psychology, 8(6), 30. (In Russ.)
- Yokoyama, S. (2019). Academic self-efficacy and academic performance in online learning: A mini review. Frontiers in Psychology, 9, 2794. https://doi.org/10.3389/fpsyg.2018.02794
- Zawacki-Richter, O., Marín, V.I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0
- Zhang, R., & Wu, Q. (2024). Impact of using virtual avatars in educational videos on user experience. Scientific Reports, 14(1), 6592. https://doi.org/10.1038/s41598-024-56716-9
- Zhao, Y., Lei, J., Lai, B.Y.C., & Tan, H.S. (2005). What makes the difference? A practical analysis of research on the effectiveness of distance education. Teachers College Record: The Voice of Scholarship in Education, 107(8), 1836–1884. https://doi.org/10.1111/j.1467-9620.2005.00544.x
Қосымша файлдар

