Multimodal Avatars and Human Simulations in Teaching Practical Skills and Training of Clinical Psychology, Psychotherapy, and Related Mental Health Specialists
Abstract
Psychology students face limitations in opportunities for supervised practice, constrained by access to clients, the costs of standardized patient programs, and ethical barriers. Novel teaching instruments in the form of multimodal avatars and human simulations have been proposed as innovative solutions, yet their effectiveness remains unclear. This review aimed to answer the question: to what extent do existing systems support skill acquisition in psychology training? A structured search of nine databases (2015–2025) identified seven eligible studies. Solutions from the studies were classified into five categories: basic virtual patient simulations, chatbot-based avatars, mixed reality avatars, virtual reality avatars, and virtual world avatars. Results show that digital simulation solutions are feasible, engaging, and accepted by students. There is evidence of improved training in diagnostic reasoning, questioning strategies, and self-efficacy. However, traditional actor-based simulations are still more effective for developing interpersonal skills. Technological issues, such as limited interactivity and the Uncanny Valley effects, hurt realism and reduce training gains. In conclusion, these technologies have promise as supplements to traditional training. Yet, the field remains underdeveloped and will require further design-focused improvements to reach its full potential.
Get full access to this article
View all access and purchase options for this article.
References
Al-Ansi A. M., Jaboob M., Garad A., Al-Ansi A. (2023). Analyzing augmented reality (AR) and virtual reality (VR) recent development in education. Social Sciences & Humanities Open, 8(1), 100532. https://doi.org/10.1016/j.ssaho.2023.100532
American Psychological Association. (2018). JARS–Qual | qualitative meta-analysis article reporting standards information recommended for inclusion in manuscripts reporting qualitative meta-analyses. American Psychological Association. https://apastyle.apa.org/jars/qualitative
Bassett C. (2019). The computational therapeutic: Exploring Weizenbaum’s ELIZA as a history of the present. AI & Society, 34(4), 803–812. https://doi.org/10.1007/s00146-018-0825-9
Bearman M., Palermo C., Allen L. M., Williams B. (2015). Learning empathy through simulation: A systematic literature review. Simulation in Healthcare, 10(5), 308–319. https://doi.org/10.1097/SIH.0000000000000113
Bell D. J., Self M. M., Davis III C., Conway F., Washburn J. J., Crepeau-Hobson F. (2020). Health service psychology education and training in the time of COVID-19: Challenges and opportunities. American Psychologist, 75(7), 919. https://doi.org/10.1037/amp0000673
Bennett M., Williams T., Thames D., Scheutz M. (2017). Differences in interaction patterns and perception for teleoperated and autonomous humanoid robots. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6589–6594). https://ieeexplore.ieee.org/abstract/document/8206571/
Bjork E. L., Bjork R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. Psychology and the Real World: Essays Illustrating Fundamental Contributions to Society, 2(59–68), 56–64. https://psycnet.apa.org/record/2011-19926-008
Brown T., Mann B., Ryder N., Subbiah M., Kaplan J. D., Dhariwal P., Neelakantan A., Shyam P., Sastry G., Askell A. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901. https://doi.org/10.48550/arXiv.2005.14165
Brubacher S. P., Powell M. B., Johnson M. S., Cano M. L., Hassan S. Z., Riegler M. A., Halvorsen P., Baugerud G. A. (2025). Experts’ views on artifical intelligence-based child chatbots to train investigative interviewing skills. Applied Cognitive Psychology, 39(2), e70048. https://doi.org/10.1002/acp.70048
Cerf V. (1973). Parry encounters the doctor. https://www.rfc-editor.org/rfc/rfc439.html
Chen D., Kong X., Wei Q. (2021). Design and development of psychological virtual simulation experiment teaching system. Computer Applications in Engineering Education, 29(2), 481–490. https://doi.org/10.1002/cae.22293
Ciekanowska A., Kiszczak-Gliński A., Dziedzic K. (2021). Comparative analysis of Unity and Unreal Engine efficiency in creating virtual exhibitions of 3D scanned models. Journal of Computer Sciences Institute, 20, 247–253. https://doi.org/10.35784/jcsi.2698
Colby K. M., Hilf F. D., Weber S., Kraemer H. C. (1972). Turing-like indistinguishability tests for the validation of a computer simulation of paranoid processes. Artificial Intelligence, 3, 199–221. https://doi.org/10.1016/0004-3702(72)90049-5
Davitadze M., Ooi E., Ng C. Y., Zhou D., Thomas L., Hanania T., Blaggan P., Evans N., Chen W., Melson E., Arlt W., Kempegowda P. (2022). SIMBA: Using Kolb’s learning theory in simulation-based learning to improve participants’ confidence. BMC Medical Education, 22(1), 116. https://doi.org/10.1186/s12909-022-03176-2
Ellawa R. H. (2014). Virtual patients as activities: Exploring the research implications of an activity theoretical stance. Perspectives on Medical Education, 3(4), 266–277. https://doi.org/10.1007/S40037-014-0134-Z
Fang Z., Cai L., Wang G. (2021). Metahuman creator the starting point of the metaverse. 2021 International Symposium on Computer Technology and Information Science (ISCTIS) (pp. 154–157). https://ieeexplore.ieee.org/abstract/document/9603558/
Fares O. H., Aversa J., Lee S. H., Jacobson J. (2024). Virtual reality: A review and a new framework for integrated adoption. International Journal of Consumer Studies, 48(2), e13040. https://doi.org/10.1111/ijcs.13040
Fink M. C., Robinson S. A., Ertl B. (2024). AI-based avatars are changing the way we learn and teach: Benefits and challenges. Frontiers in Education, 9, 1416307. https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2024.1416307/fullhttps://doi.org/10.3389/feduc.2024.1416307
Goghari V. M., Hagstrom S., Madon S., Messer-Engel K. (2020). Experiences and learnings from professional psychology training partners during the COVID-19 pandemic: Impacts, challenges, and opportunities. Canadian Psychology/Psychologie Canadienne, 61(3), 167. https://doi.org/10.1037/cap0000250
Graesser A. C., Chipman P., Haynes B. C., Olney A. (2005). Autotutor: An intelligent tutoring system with mixed-initiative dialogue. IEEE Transactions on Education, 48(4), 612–618. https://doi.org/10.1109/TE.2005.856149
Gratch J., Marsella S. (2004). A domain-independent framework for modeling emotion. Cognitive Systems Research, 5(4), 269–306. https://doi.org/10.1016/j.cogsys.2004.02.002
Harless W. G., Drennon G. G., Marxer J. J., Root J. A., Miller G. E. (1971). CASE: A computer-aided simulation of the clinical encounter. Academic Medicine, 46(5), 443–448. https://doi.org/10.1097/00001888-197105000-00009
Hattie J., Timperley H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
Herrington J., Reeves T. C., Oliver R. (2014). Authentic learning environments. In Spector J. M., Merrill M. D., Elen J., Bishop M. J. (Eds.), Handbook of research on educational communications and technology (pp. 401–412). Springer New York. https://doi.org/10.1007/978-1-4614-3185-5_32
Hossain S. I., Kelson J., Morrison B. (2024). The use of virtual patient simulations in psychology: A scoping review. Australasian Journal of Educational Technology, 40(6), 76–91. https://doi.org/10.14742/ajet.9559
Howell H., Mikeska J. N. (2021). Approximations of practice as a framework for understanding authenticity in simulations of teaching. Journal of Research on Technology in Education, 53(1), 8–20. https://doi.org/10.1080/15391523.2020.1809033
Islam M. Z., Wang G. (2025). Avatars in the educational metaverse. Visual Computing for Industry, Biomedicine, and Art, 8(1), 15. https://doi.org/10.1186/s42492-025-00196-9
Krizhevsky A., Sutskever I., Hinton G. E. (2012). Imagenet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems, 25, 1–9. https://doi.org/10.1145/3065386
Krüger M., Gilbert D., Kuhlen T. W., Gerrits T. (2024). Game engines for immersive visualization: Using unreal engine beyond entertainment. PRESENCE: Virtual and Augmented Reality, 33, 31–55. https://doi.org/10.1162/pres_a_00416
Lavoie P., Deschênes M.-F., Nolin R., Bélisle M., Garneau A. B., Boyer L., Lapierre A., Fernandez N. (2020). Beyond technology: A scoping review of features that promote fidelity and authenticity in simulation-based health professional education. Clinical Simulation in Nursing, 42, 22–41. https://doi.org/10.1016/j.ecns.2020.02.001
Lester J. C., Converse S. A., Kahler S. E., Barlow S. T., Stone B. A., Bhogal R. S. (1997). The persona effect: Affective impact of animated pedagogical agents. Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (pp. 359–366). https://doi.org/10.1145/258549.258797
Levin O., Frei-Landau R., Flavian H., Miller E. C. (2023). Creating authenticity in simulation-based learning scenarios in teacher education. European Journal of Teacher Education, 48(2), 291–312. https://doi.org/10.1080/02619768.2023.2175664
Magill M., Mastroleo N. R., Martino S. (2022). Technology-Based methods for training counseling skills in behavioral health: A scoping review. Journal of Technology in Behavioral Science, 7(3), 325–336. https://doi.org/10.1007/s41347-022-00252-8
Makransky G., Petersen G. B. (2021). The cognitive affective model of immersive learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educational Psychology Review, 33(3), 937–958. https://doi.org/10.1007/s10648-020-09586-2
Masahiro M., MacDorman K. F., Kageki N. (2012). The uncanny valley. IEEE Robotics & Automation Magazine, 19(2), 98–100. https://doi.org/10.1109/MRA.2012.2192811
Mayer R. E. (2010). Learning with technology. In The nature of learning: Using research to inspire practice (pp. 179–198). OECD Publishing.
Mayer R. E. (2020). Multimedia learning (3rd ed.). Cambridge University Press.
McKim J. (2022). Animation without animators: From motion capture to MetaHumans. Animation Studies 2.0. https://eprints.bbk.ac.uk/id/eprint/50248/
Morrison B. W., Kelson J., Morrison N. M. V., Bennett G. (2025). You’re virtually a psychologist: Enhancing professional psychology education through virtual client simulations. Australian Psychologist, 1–8. https://doi.org/10.1080/00050067.2025.2547800
Nagendran A., Compton S., Follette W. C., Golenchenko A., Compton A., Grizou J. (2022). Avatar led interventions in the metaverse reveal that interpersonal effectiveness can be measured, predicted, and improved. Scientific Reports, 12(1), 21892. https://doi.org/10.1038/s41598-022-26326-4
Narciss S. (2013). Designing and evaluating tutoring feedback strategies for digital learning. Digital Education Review, 23, 7–26. https://revistes.ub.edu/index.php/der/article/view/11284
Omer A. T., Ali E. M., Elhassan M. E., Ibrahim S. A., Ahmed Y. S. (2024). Medical education challenges during the war crisis in Sudan: A cross-sectional study, 2023–2024. BMC Medical Education, 24(1), 1354. https://doi.org/10.1186/s12909-024-06358-2
Pomerantz A. M. (2016). Clinical psychology: Science, practice, and culture. Sage Publications. https://books.google.com/books?hl=en&lr=&id=fCBuDQAAQBAJ&oi=fnd&pg=PP1&dq=Pomerantz,+A.+M.+(2003).+Clinical+psychology:+Science,+practice,+and+culture.+Thousand+Oaks,+CA:+SAGE.&ots=IJ6kwAFkJ_&sig=bmF5swql-6EP3sF7syrrsNCLq-I
Rickel J., Johnson W. L. (1999). Animated agents for procedural training in virtual reality: Perception, cognition, and motor control. Applied Artificial Intelligence, 13(4–5), 343–382. https://doi.org/10.1080/088395199117315
Røed R. K., Powell M. B., Riegler M. A., Baugerud G. A. (2023). A field assessment of child abuse investigators’ engagement with a child-avatar to develop interviewing skills. Child Abuse & Neglect, 143, 106324. https://doi.org/10.1016/j.chiabu.2023.106324
Rogers S. L., Hollett R., Li Y. R., Speelman C. P. (2022). An evaluation of virtual reality role-play experiences for helping-profession courses. Teaching of Psychology, 49(1), 78–84. https://doi.org/10.1177/0098628320983231
Russell-Stamp M., Norman J. R., Parker K. (2025). Avatars vs. Actors: Comparison shows little difference in role-play simulations for psychology students. International Journal for the Scholarship of Teaching and Learning, 19(1), 7. https://doi.org/10.20429/ijsotl.2025.190107
Schraw G., Lehman S. (2001). Situational interest: A review of the literature and directions for future research. Educational Psychology Review, 13(1), 23–52. https://doi.org/10.1023/A:1009004801455
Shieber S. M. (1994). Lessons from a Restricted Turing Test (No. arXiv:cmp-lg/9404002). arXiv. https://doi.org/10.48550/arXiv.cmp-lg/9404002
Swartout W., Artstein R., Forbell E., Foutz S., Lane H. C., Lange B., Morie J. F., Rizzo A. S., Traum D. (2013). Virtual humans for learning. AI Magazine, 34(4), 13–30. https://doi.org/10.1609/aimag.v34i4.2487
Triola M., Feldman H., Kalet A. L., Zabar S., Kachur E. K., Gillespie C., Anderson M., Griesser C., Lipkin M. (2006). A randomized trial of teaching clinical skills using virtual and live standardized patients. Journal of General Internal Medicine, 21(5), 424–429. https://doi.org/10.1111/j.1525-1497.2006.00421.x
Uwamahoro O. (2015). The effect of virtual simulation on the development of basic counseling skills, self-reported immersion experience, self-reported counselor self-efficacy, and self-reported anxiety of counselors-in-training. https://stars.library.ucf.edu/etd/1255/
Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L., Gomez A. N., Kaiser Ł., Polosukhin I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30, 1–11.https://doi.org/10.48550/arXiv.1706.03762
Walkiewicz M., Zalewski B., Guziak M. (2022). Affect and cognitive closure in students—A step to personalised education of clinical assessment in psychology with the use of simulated and virtual patients. Healthcare, 10(6), 1076. https://www.mdpi.com/2227-9032/10/6/1076https://doi.org/10.3390/healthcare10061076
Washburn M., Parrish D. E., Bordnick P. S. (2020). Virtual patient simulations for brief assessment of mental health disorders in integrated care settings. Social Work in Mental Health, 18(2), 121–148. https://doi.org/10.1080/15332985.2017.1336743
Weiss A., Wurhofer D., Lankes M., Tscheligi M. (2009). Autonomous vs. Tele-operated: How people perceive human-robot collaboration with hrp-2. Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction (pp. 257–258). https://doi.org/10.1145/1514095.1514164
Weizenbaum J. (1966). ELIZA—A computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36–45. https://doi.org/10.1145/365153.365168
Zgheib N. K., Sabra R. (2025). How a sudden war affected our medical school: Reflections and lessons learned on adaptability and equity while preserving academic standards. BMC Medical Education, 25(1), 808. https://doi.org/10.1186/s12909-025-07415-0
Zook S. S., Hulton L. J., Dudding C. C., Stewart A. L., Graham A. C. (2018). Scaffolding interprofessional education: Unfolding case studies, virtual world simulations, and patient-centered care. Nurse Educator, 43(2), 87–91. https://doi.org/10.1097/NNE.0000000000000430
Biographies
Jakub F. Juranek is a PhD candidate at the Institute of Psychology of the Polish Academy of Sciences, focusing on research related to the psychology of time, particularly the creation of machine learning/AI models aimed at predicting subjective experiences of time. He is interested in innovative methods of teaching and learning. In the learning domain, he is attracted mainly to the potential of utilizing custom-crafted learning experiences, using AI predictive capabilities combined with the processing of neuropsychophysiological and other (e.g., visual facial and emotion recognition) cues to create interactive, personal, and adaptable learning systems. In teaching, he is interested in the possibilities of using AI-driven avatars and human simulations as skills training facilitators and synthetic tutors. He works as a software and data engineer, with 12+ years of experience in development, data analysis, and software quality assurance roles. Additional current research undertakings include the study of the experience of time during the war in Ukraine and its utility as a predictor of positive and negative posttraumatic changes and posttraumatic growth in individuals as well as exploration of various aspects of attitudes toward AI.
Cite
Cite
Cite
OR
Download to reference manager
If you have citation software installed, you can download citation data to the citation manager of your choice
Information, rights and permissions
Information
Published In
Article first published online: March 6, 2026
Issue published: March 2026
Keywords
Authors
Metrics and citations
Metrics
Journals metrics
This article was published in Psychology Learning & Teaching.
View All Journal MetricsPublication usage*
Total views and downloads: 33
*Publication usage tracking started in December 2016
Publications citing this one
Receive email alerts when this publication is cited
Web of Science: 0
Crossref:
There are no citing articles to show.
Figures and tables
Figures & Media
Tables
View Options
Access options
If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:
I am signed in as:
View my profileSign out
I can access personal subscriptions, purchases, paired institutional access and free tools such as favourite journals, email alerts and saved searches.
loading institutional access options
Alternatively, view purchase options below:
Purchase 24 hour online access to view and download content.
Access journal content via a DeepDyve subscription or find out more about this option.
