Face-to-Face Interaction with Pedagogical Agents, Twenty Years Later
Open accessAbstract
Johnson et al. ( International Journal of Artificial Intelligence in Education , 11 , 47–78, 2000 ) introduced and surveyed a new paradigm for interactive learning environments: animated pedagogical agents. The article argued for combining animated interface agent technologies with intelligent learning environments, yielding intelligent systems that can interact with learners in natural, human-like ways to achieve better learning outcomes. We outlined a variety of possible uses for pedagogical agents. But we offered only preliminary evidence that they improve learning, leaving that to future research and development. Twenty years have elapsed since work began on animated pedagogical agents. This article re-examines the concepts and predictions in the 2000 article in the context of the current state of the field. Some of the ideas in the paper have become well established and widely adopted, especially in game-based learning environments. Others are only now being realized, thanks to advances in immersive interfaces and robotics that enable rich face-to-face interaction between learners and agents. Research has confirmed that pedagogical agents can be beneficial, but not equally for all learning problems, applications, and learner populations. Although there is a growing body of research findings about pedagogical agents, many questions remain and much work remains to be done.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Computer-generated animated agents can use non-verbal facial cues, paralinguistic cues, and gestures as an additional form of feedback.
“Further, computer-generated animated agents can use non-verbal facial cues, paralinguistic cues (e.g., intonation in speech), and gestures as an additional form of feedback (Johnson & Lester, 2016).”
From Looking Beyond the Hype: Understanding the Effects of AI on Learning (2025) · cites this paper as Johnson & Lester, 2016
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Self-explanations: How students study and use examples in learning to solve problems
Chi, M. (1989) · Cognitive Science · doi:10.1016/0364-0213(89)90002-5 · Cited by 2,287 · see citing works
Self‐Explanations: How Students Study and Use Examples in Learning to Solve Problems
Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989) · Cognitive Science · doi:10.1207/s15516709cog1302_1 · Cited by 1,714 · see citing works
Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001) · Cognition and Instruction · doi:10.1207/s1532690xci1902_02 · Cited by 912 · see citing works
Self-citationLester, J. C., Converse, S. A., Kahler, S. E., Barlow, S., Stone, B. A., & Bhogal, R. S. (1997) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/258549.258797 · Cited by 812 · see citing works
Self-citationAnimated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments
Johnson, W. L., Rickel, J. W., & Lester, J. C. (2000) · Cited by 711 · see citing works
Self-citationLEARNING BY TEACHING: A NEW AGENT PARADIGM FOR EDUCATIONAL SOFTWARE
Biswas, G., Leelawong, K., Schwartz, D. L., Vye, N. J., & The Teachable Agents Group at Vande (2005) · Applied Artificial Intelligence · doi:10.1080/08839510590910200 · Cited by 463 · see citing works
Research-Based Design of Pedagogical Agent Roles: a Review, Progress, and Recommendations
Kim, Y. A., & Baylor, A. L. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0055-y · Cited by 423 · see citing works
Ivon, A., Cooper David, G., Winslow, B., Park, W. B., Kasia, M., & Robert, C. (2009) · Frontiers in Artificial Intelligence and Applications · doi:10.3233/978-1-60750-028-5-17 · Cited by 382 · see citing works
Integrating Learning, Problem Solving, and Engagement in Narrative-Centered Learning Environments
Rowe, J., Shores, L. R., Mott, B., & Lester, J. C. (2011) · International Journal of Artificial Intelligence in Education · doi:10.3233/jai-2011-019 · Cited by 346 · see citing works
Self-citationMultimodal affect recognition in learning environments
Kapoor, A., & Picard, R. W. (2005) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/1101149.1101300 · Cited by 342 · see citing works
An embodiment effect in computer-based learning with animated pedagogical agents.
Mayer, R. E., & DaPra, C. S. (2012) · Journal of Experimental Psychology Applied · doi:10.1037/a0028616 · Cited by 324 · see citing works
D’Mello, S. K., & Graesser, A. (2010) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-010-9074-4 · Cited by 323 · see citing works
How Effective are Pedagogical Agents for Learning? A Meta-Analytic Review
Schroeder, N. L., Adesope, O., & Gilbert, R. B. (2013) · Journal of Educational Computing Research · doi:10.2190/ec.49.1.a · Cited by 299 · see citing works
AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring
Nye, B. D., Graesser, A. C., & Hu, X. (2014) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-014-0029-5 · Cited by 298 · see citing works
The politeness effect: Pedagogical agents and learning outcomes
Wang, N., Johnson, W. L., Mayer, R. E., Rizzo, P., Shaw, E., & Collins, H. (2007) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2007.09.003 · Cited by 296 · see citing works
Self-citationSerious Use of a Serious Game for Language Learning
Lewis, W., & Johnson (2007) · International Journal of Artificial Intelligence in Education · doi:10.3233/jai-2010-0006 · Cited by 240 · see citing works
Shaw, E., Johnson, W. L., & Ganeshan, R. (1999) · doi:10.1145/301136.301210 · Cited by 217 · see citing works
Self-citationLester, J. C., Stone, B. A., & Stelling, G. D. (1999) · User Modeling and User-Adapted Interaction · doi:10.1023/a:1008374607830 · Cited by 202 · see citing works
Self-citationBiLAT: A Game-Based Environment for Practicing Negotiation in a Cultural Context
Kim, J. M., Hill, R. W., Durlach, P. J., Lane, H. C., Forbell, E., Core, M. G., Marsella, S., Pynadath, D. V., & Hart, J. (2009) · International Journal of Artificial Intelligence in Education · doi:10.3233/irg-2009-19(3)03 · Cited by 155 · see citing works
Interface agents: metaphors with character
LAUREL, B. K. (1990) · Center for the Study of Language and Information eBooks · Cited by 136 · see citing works
Integrating Pedagogical Agents into Virtual Environments
Johnson, W. L., Rickel, J. W., Stiles, R., & Munro, A. (1998) · PRESENCE Virtual and Augmented Reality · doi:10.1162/105474698565929 · Cited by 128 · see citing works
Self-citationModeling Learner Affect with Theoretically Grounded Dynamic Bayesian Networks
Sabourin, J., Mott, B. W., & Lester, J. C. (2011) · Affective Computing and Intelligent Interaction · doi:10.1007/978-3-642-24600-5_32 · Cited by 121 · see citing works
Self-citationVeletsianos, G. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.02.019 · Cited by 120 · see citing works
Woolf, B. P., Arroyo, I., Müldner, K., Burleson, W., Cooper, D. G., Dolan, R., & Christopherson, R. M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13388-6_37 · Cited by 117 · see citing works
Early Prediction of Student Frustration
McQuiggan, S. W., Lee, S., & Lester, J. C. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-74889-2_61 · Cited by 82 · see citing works
Self-citationHayes‐Roth, B., & Doyle, P. (1998) · Autonomous Agents and Multi-Agent Systems · doi:10.1023/a:1010019818773 · Cited by 72 · see citing works
Serious Use of a Serious Game for Language Learning
Johnson, W. L. (2007) · Cited by 67 · see citing works
Self-citationSwartout, W., Artstein, R., Forbell, E., Foutz, S., Lane, H. C., Lange, B., Morie, J., Noren, D., Rizzo, S., & Traum, D. (2013) · AI Magazine · doi:10.1609/aimag.v34i4.2487 · Cited by 61 · see citing works
Social interaction: multimodal conversation with social agents
Nagao, K., & Takeuchi, A. (1994) · Cited by 60 · see citing works
The Effects of Pedagogical Agent Voice and Animation on Learning, Motivation and Perceived Persona
Baylor, A. L., Ryu, J., & Shen, E. (2003) · EdMedia: World Conference on Educational Media and Technology · Cited by 57 · see citing works
Predicting Learning and Affect from Multimodal Data Streams in Task-Oriented Tutorial Dialogue.
Grafsgaard, J. F., Wiggins, J. B., Boyer, K. E., Wiebe, E., & Lester, J. C. (2014) · Cited by 52 · see citing works
Self-citationLester, J. C., Stone, B. A., & Stelling, G. D. (1999) · Springer eBooks · doi:10.1007/978-94-017-1118-0_5 · Cited by 37 · see citing works
Self-citationTime-offset interaction with a holocaust survivor
Artstein, R., Traum, D. R., Alexander, O., Leuski, A., Jones, A., Georgila, K., Debevec, P. E., Swartout, W., Maio, H., & Smith, S. (2014) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/2557500.2557540 · Cited by 29 · see citing works
McLaren, B. M., Александрович, С. С., & Aleven, V. (2014) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-014-0021-0 · Cited by 7 · see citing works
Cultural Training as Behavior Change
Johnson, W. L. (2015) · Procedia Manufacturing · doi:10.1016/j.promfg.2015.07.894 · Cited by 3 · see citing works
Self-citationLearning Through Storytelling, Not Documents
Schank, R. C. (2010) · eLearn · doi:10.1145/1872818.1872819 · Cited by 1 · see citing works
(2010) · Auerbach Publications eBooks · doi:10.1201/b10420-8 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- Johnson, W.L. (2015b). Constructing Virtual Role-Play Simulations. in R Sottilare, A. Graesser, X. Hu, K. Brawner (Eds.), Design Recommendations for Adaptive Intelligent Tutoring Systems: Authoring Tools, 3, 211-226. Orlando: US Army Research Laboratory.
- Johnson, W.L., Friedland, L., Schrider, P., Valente, A., & Sheridan, S. (2011). The Virtual Cultural Awareness Trainer (VCAT): Joint Knowledge Online's (JKO's) Solution to the Individual Operational Culture and Language Training Gap. In Proceedings of ITEC 2011. London: Clarion Events.
- Lester, J.C., Converse, S.A., Stone, B.A., Kahler, S.E., & Barlow, S.T. (1997b). Animated pedagogical agents and problem-solving effectiveness: A large-scale empirical evaluation. In Proceedings of the Eighth World Conference on Artificial Intelligence in Education (pp. 23-30). Amsterdam: IOS Press.
- Rickel, J., & Johnson, W.L. (1999). Virtual humans for team training in virtual reality. In Proceedings of the Ninth International Conference on Artificial Intelligence in Education. Amsterdam: IOS Press.
Cited by
Sorted by citations
Fryer, L. K., Ainley, M., Thompson, A., Gibson, A., & Sherlock, Z. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.05.045 · Cited by 448 · see citing works
Advancing the Science of Collaborative Problem Solving
Graesser, A. C., Fiore, S. M., Greiff, S., Andrews-Todd, J., Foltz, P. W., & Hesse, F. W. (2018) · Psychological Science in the Public Interest · doi:10.1177/1529100618808244 · Cited by 390 · see citing works
Dai, C., & Ke, F. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100087 · Cited by 319 · see citing works
Azevedo, R., Bouchet, F., Duffy, M. C., Harley, J. M., Taub, M., Trevors, G., Cloude, E. B., Dever, D. A., Wiedbusch, M. D., Wortha, F., et al. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.813632 · Cited by 230 · see citing works
Why Not Robot Teachers: Artificial Intelligence for Addressing Teacher Shortage
Edwards, B. I., & Cheok, A. D. (2018) · Applied Artificial Intelligence · doi:10.1080/08839514.2018.1464286 · Cited by 220 · see citing works
Cano, E. V., Andrés, S. M., & Menéses, E. L. (2021) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-021-00269-8 · Cited by 220 · see citing works
Makransky, G., Wismer, P., & Mayer, R. E. (2018) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12335 · Cited by 177 · see citing works
Personalized learning through AI
Jian, M. J. K. O. (2023) · Advances in Engineering Innovation · doi:10.54254/2977-3903/5/2023039 · Cited by 153 · see citing works
Reconsidering the voice effect when learning from a virtual human
Craig, S. D., & Schroeder, N. L. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.07.003 · Cited by 151 · see citing works
Mohammed, P. S., & Watson, E. ‘. (2019) · Perspectives on rethinking and reforming education · doi:10.1007/978-981-13-8161-4_2 · Cited by 173 · see citing works
Looking Beyond the Hype: Understanding the Effects of AI on Learning
Bauer, E., Greiff, S., Graesser, A. C., Scheiter, K., & Sailer, M. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10020-8 · Cited by 153 · see citing works
Digital Language Learning (DLL): Insights from Behavior, Cognition, and the Brain
Li, P., & Lan, Y. (2021) · Bilingualism Language and Cognition · doi:10.1017/s1366728921000353 · Cited by 159 · see citing works
Developing Embodied Conversational Agents for Coaching People in a Healthy Lifestyle: Scoping Review
Kramer, L. L., ter Stal, S., Mulder, B. C., de Vet, E., & van Velsen, L. (2020) · Journal of Medical Internet Research · doi:10.2196/14058 · Cited by 121 · see citing works
“In the educational context, Johnson and Lester [9] state that there is a significant body of experience and research findings related to pedagogical agents.”
BackgroundBarz, N., Benick, M., Dörrenbächer‐Ulrich, L., & Perels, F. (2023) · Review of Educational Research · doi:10.3102/00346543231167795 · Cited by 187 · see citing works
Wang, F., Li, W., Mayer, R. E., & Liu, H. (2017) · Journal of Educational Psychology · doi:10.1037/edu0000221 · Cited by 136 · see citing works
BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions
Calisto, F. M., Santiago, C., Nunes, N., & Nascimento, J. C. (2022) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2022.102285 · Cited by 125 · see citing works
Online Assessment in Higher Education: A Systematic Review
Heil, J., & Ifenthaler, D. (2023) · Online Learning · doi:10.24059/olj.v27i1.3398 · Cited by 168 · see citing works
Evaluating Artificial Intelligence in Education for Next Generation
Joshi, S., Rambola, R. K., & Churi, P. P. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1714/1/012039 · Cited by 139 · see citing works
Una revisión sistemática del uso de la inteligencia artificial en la educación
Bolaño-García, M., & Duarte-Acosta, N. (2023) · Revista Colombiana de Cirugía · doi:10.30944/20117582.2365 · Cited by 99 · see citing works
AI-based avatars are changing the way we learn and teach: benefits and challenges
Fink, M. C., Robinson, S. A., & Ertl, B. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1416307 · Cited by 109 · see citing works
Emotions are the experiential glue of learning environments in the 21st century
Graesser, A. (2019) · Learning and Instruction · doi:10.1016/j.learninstruc.2019.05.009 · Cited by 86 · see citing works
Moral considerations on social robots in education: A multi-stakeholder perspective
Smakman, M., Vogt, P., & Konijn, E. A. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104317 · Cited by 102 · see citing works
ElectronixTutor: an intelligent tutoring system with multiple learning resources for electronics
Graesser, A. C., Hu, X., Nye, B. D., VanLehn, K. A., Kumar, R. V., Heffernan, C., Heffernan, N. T., Woolf, B. P., Olney, A. M., Rus, V., et al. (2018) · International Journal of STEM Education · doi:10.1186/s40594-018-0110-y · Cited by 97 · see citing works
Dai, C., Ke, F., Pan, Y., Moon, J., & Liu, Z. (2024) · Educational Psychology Review · doi:10.1007/s10648-024-09855-4 · Cited by 91 · see citing works
Mouta, A., Llorente, A. M. P., & Sánchez, E. M. T. (2023) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-023-00384-9 · Cited by 149 · see citing works
Buttussi, F., & Chittaro, L. (2020) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2020.3033766 · Cited by 83 · see citing works
Artificial Intelligence in Intelligent Tutoring Robots: A Systematic Review and Design Guidelines
Yang, J., & Zhang, B. (2019) · Applied Sciences · doi:10.3390/app9102078 · Cited by 99 · see citing works
Graesser, A. C., Sabatini, J., & Li, H. (2021) · Annual Review of Psychology · doi:10.1146/annurev-psych-020821-113042 · Cited by 88 · see citing works
Do Learners Recognize and Relate to the Emotions Displayed By Virtual Instructors?
Lawson, A. P., Mayer, R. E., Adamo‐Villani, N., Beneš, B., Lei, X., & Cheng, J. (2021) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00238-2 · Cited by 67 · see citing works
Supporting Interest in Science Learning with a Social Robot
Michaelis, J. E., & Mutlu, B. (2019) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3311927.3323154 · Cited by 66 · see citing works
Emerging Roles and Relationships Among Humans and Interactive AI Systems
Lindgren, H. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2435693 · Cited by 73 · see citing works
Animated pedagogical agents enhance learning outcomes and brain activity during learning
Li, W., Wang, F., Mayer, R. E., & Liu, T. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12634 · Cited by 58 · see citing works
Pérez-Marín, D. (2021) · Digital · doi:10.3390/digital1010002 · Cited by 57 · see citing works
Dever, D. A., Sonnenfeld, N. A., Wiedbusch, M. D., Schmorrow, S. G., Amon, M. J., & Azevedo, R. (2023) · Metacognition and Learning · doi:10.1007/s11409-023-09346-x · Cited by 60 · see citing works
The effects of animated pedagogical agents in an English-as-a-foreign-language learning environment
Carlotto, T., & Jaques, P. A. (2016) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2016.06.001 · Cited by 53 · see citing works
Hamid, O. H., Smith, N. L., & Barzanji, A. (2017) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2017.8104891 · Cited by 52 · see citing works
Challenges for IT-Enabled Formative Assessment of Complex 21st Century Skills
Webb, M., Prasse, D., Phillips, M., Kadijevich, D. M., Angeli, C., Strijker, A., Carvalho, A. A. A., Andresen, B. B., Dobozy, E., & Laugesen, H. (2018) · Technology Knowledge and Learning · doi:10.1007/s10758-018-9379-7 · Cited by 53 · see citing works
A Systematic Review of Voice-based Intelligent Virtual Agents in EFL Education
Katsarou, E. C., Wild, F., Sougari, A.-M., & Chatzipanagiotou, P. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i10.37723 · Cited by 50 · see citing works
The Power of Voice to Convey Emotion in Multimedia Instructional Messages
Lawson, A. P., & Mayer, R. E. (2021) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00282-y · Cited by 49 · see citing works
Getting smart: towards critical digital literacy pedagogies
Knight, J., Dooly, M., & Barberà, E. (2020) · Social Semiotics · doi:10.1080/10350330.2020.1836815 · Cited by 45 · see citing works
Fun and frustrating: Students’ perspectives on practising speaking English with virtual humans
Ericsson, E., Hashemi, S. S., & Lundin, J. (2023) · Cogent Education · doi:10.1080/2331186x.2023.2170088 · Cited by 42 · see citing works
How to Harness Generative AI to Accelerate Human Learning
Johnson, W. L. (2023) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-023-00367-w · Cited by 41 · see citing works
Self-citationThe role of Artificial Intelligence in Education: Current Trends and Future Prospects
Yousuf, M., & Wahid, A. (2021) · International Conference on Information Science and Communications Technologies (ICISCT) · doi:10.1109/icisct52966.2021.9670009 · Cited by 40 · see citing works
Huang, H., Chen, Y., & Rau, P. P. (2021) · Universal Access in the Information Society · doi:10.1007/s10209-021-00835-x · Cited by 38 · see citing works
“Better than my professor?” How to develop artificial intelligence tools for higher education
Triberti, S., Fuccio, R. D., Scuotto, C., Marsico, E., & Limone, P. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1329605 · Cited by 50 · see citing works
Zgambo, M., Costello, M., Buhlmann, M., Maldon, J., Anyango, E., & Adama, E. A. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106796 · Cited by 39 · see citing works
Sahakiants, I., & Dorner, G. (2021) · Thunderbird International Business Review · doi:10.1002/tie.22233 · Cited by 35 · see citing works
Digital Disruption In Teaching And Testing
Wyatt‐Smith, C., Lingard, B., & Heck, E. (2021) · Routledge eBooks · doi:10.4324/9781003045793 · Cited by 37 · see citing works
Lawson, A. P., & Mayer, R. E. (2022) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2022.102080 · Cited by 35 · see citing works
Learning with Digital Agents: An Analysis based on the Activity Theory
Dolata, M., Katsiuba, D., Wellnhammer, N., & Schwabe, G. (2023) · Journal of Management Information Systems · doi:10.1080/07421222.2023.2172775 · Cited by 37 · see citing works
A Framework for Design of Conversational Agents to Support Health Self-Care for Older Adults
Morrow, D. G., Lane, H. C., & Rogers, W. A. (2020) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820964085 · Cited by 31 · see citing works
Learning with virtual humans: Introduction to the special issue
Schroeder, N. L., & Craig, S. D. (2021) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1863114 · Cited by 30 · see citing works
How to guide learners' processing of multimedia lessons with pedagogical agents
Li, W., Wang, F., & Mayer, R. E. (2022) · Learning and Instruction · doi:10.1016/j.learninstruc.2022.101729 · Cited by 29 · see citing works
Lane, H. C., & Schroeder, N. L. (2022) · ACM eBooks · doi:10.1145/3563659.3563669 · Cited by 29 · see citing works
Feasibility and usability of MentorPal, a framework for rapid development of virtual mentors
Nye, B. D., Davis, D. M., Rizvi, S. Z., Carr, K., Swartout, W., Thacker, R., & Shaw, K. (2020) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1771640 · Cited by 28 · see citing works
Jochecová, K., Černý, M., Stachoň, Z., Švédová, H., Káčová, N., Chmelík, J., Brůža, V., Kvarda, O., Ugwitz, P., Šašinková, A., et al. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11030180 · Cited by 30 · see citing works
Twenty-five Years of Learning with Pedagogical Agents: History, Barriers, and Opportunities
Siegle, R. F., Schroeder, N. L., Lane, H. C., & Craig, S. D. (2023) · TechTrends · doi:10.1007/s11528-023-00869-3 · Cited by 27 · see citing works
Automated Essay Scoring Systems
Ifenthaler, D. (2022) · Handbook of Open, Distance and Digital Education · doi:10.1007/978-981-19-0351-9_59-1 · Cited by 26 · see citing works
Putman, R. S. (2016) · Educational Technology Research and Development · doi:10.1007/s11423-016-9499-5 · Cited by 25 · see citing works
Examining the effects of a virtual character on learning and engagement in serious games
Gamage, V., & Ennis, C. (2018) · Motion in Games · doi:10.1145/3274247.3274499 · Cited by 25 · see citing works
Avatars in the educational metaverse
Islam, M. Z., & Wang, G. (2025) · Visual Computing for Industry Biomedicine and Art · doi:10.1186/s42492-025-00196-9 · Cited by 27 · see citing works
Virtual discrete trial training for teacher trainees
Sveinbjörnsdóttir, B., Jóhannsson, S. H., Oddsdóttir, J., Sigurðardóttir, T. Þ., Valdimarsson, G. I., & Vilhjálmsson, H. H. (2019) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-018-0288-9 · Cited by 24 · see citing works
Teng, D., Wang, X., Xia, Y., Zhang, Y., Tang, L., Chen, Q., Zhang, R., Xie, S., & Yu, W. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13264-z · Cited by 27 · see citing works
Student Modeling for Individuals and Groups: the BioWorld and HOWARD Platforms
Lajoie, S. P. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00219-x · Cited by 23 · see citing works
Atif, A., Jha, M., Richards, D., & BILGIN, A. A. B. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823410-5.00013-9 · Cited by 25 · see citing works
FAtiMA Toolkit: Toward an Accessible Tool for the Development of Socio-emotional Agents
Mascarenhas, S. F., Guimarães, M., Prada, R., Santos, P. A., Dias, J., & Paiva, A. (2022) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3510822 · Cited by 23 · see citing works
Zipp, S. A., & Craig, S. D. (2019) · Educational Technology Research and Development · doi:10.1007/s11423-019-09647-6 · Cited by 20 · see citing works
Open Student Modeling Research and its Connections to Educational Assessment
Zapata‐Rivera, D. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00206-2 · Cited by 22 · see citing works
Human-robot dynamics: a psychological insight into the ethics of social robotics
Boch, A., & Thomas, B. R. (2024) · International Journal of Ethics and Systems · doi:10.1108/ijoes-01-2024-0034 · Cited by 21 · see citing works
Automated Disengagement Tracking Within an Intelligent Tutoring System
Su, C., Fang, Y., Shi, G., Sabatini, J., Greenberg, D., Frijters, J. C., & Graesser, A. C. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.595627 · Cited by 21 · see citing works
Negative Feedback In Your Face: Examining the Effects of Proxemics and Gender on Learning
Jeong, D. C., Feng, D., Krämer, N. C., Miller, L. C., & Marsella, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67401-8_19 · Cited by 21 · see citing works
Authenticity perceptions in virtual environments
Mikeska, J. N., & Howell, H. (2021) · Information and Learning Sciences · doi:10.1108/ils-10-2020-0234 · Cited by 19 · see citing works
Pedagogical Agents to Support Embodied, Discovery-Based Learning
Abdullah, A., Adil, M., Rosenbaum, L. F., Clemmons, M., Shah, M., Abrahamson, D., & Neff, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67401-8_1 · Cited by 19 · see citing works
Scenarios in virtual learning environments for one-to-one communication skills training
Lala, R., Jeuring, J. T., van Dortmont, J., & van Geest, M. (2017) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-017-0054-1 · Cited by 17 · see citing works
Yan, Y., & Du, Q. (2025) · Virtual Reality · doi:10.1007/s10055-025-01158-5 · Cited by 16 · see citing works
Comparing a Robot Tutee to a Human Tutee in a Learning-By-Teaching Scenario with Children
Serholt, S., Ekström, S., Küster, D., Ljungblad, S., & Pareto, L. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.836462 · Cited by 15 · see citing works
Zou, J., Gauthier, S., Pellerin, H., Gargot, T., Archambault, D., Chétouani, M., Cohen, D., & Anzalone, S. M. (2024) · International Journal of Social Robotics · doi:10.1007/s12369-024-01104-6 · Cited by 14 · see citing works
Embodied AI-Guided Interactive Digital Teachers for Education
Zhao, Z., Yin, Z., Sun, J., & Hui, P. (2024) · doi:10.1145/3680533.3697070 · Cited by 14 · see citing works
Graesser, A. C., Lippert, A. M., & Hampton, A. J. (2017) · Springer eBooks · doi:10.1007/978-3-319-64274-1_12 · Cited by 14 · see citing works
Assessment as, for, and of Twenty-First Century Learning Using Information Technology: An Overview
Webb, M., & Ifenthaler, D. (2018) · Springer international handbooks of education · doi:10.1007/978-3-319-71054-9_37 · Cited by 14 · see citing works
Users' perceptions of empathic dialogue cues
Richards, D., BILGIN, A. A. B., & Ranjbartabar, H. (2018) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3267851.3267857 · Cited by 14 · see citing works
Learner Control Aids Learning from Instructional Videos with a Virtual Human
Schroeder, N. L., Chin, J., & Craig, S. D. (2019) · Technology Knowledge and Learning · doi:10.1007/s10758-019-09417-6 · Cited by 14 · see citing works
Audio-visual speech comprehension in noise with real and virtual speakers
Nirme, J., Sahlén, B. S., Åhlander, V. L., Brännström, K. J., & Haake, M. (2019) · Speech Communication · doi:10.1016/j.specom.2019.11.005 · Cited by 13 · see citing works
Cognitive Impact of Anthropomorphized Robot Gaze
Spatola, N., & Huguet, P. (2021) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3459994 · Cited by 13 · see citing works
Prompting for Socially Intelligent Agents with ChatGPT
Antunes, A. S., Campos, J., Guimarães, M., Dias, J., & Santos, P. A. (2023) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3570945.3607303 · Cited by 16 · see citing works
Modeling Goal Setting Within a Multimedia Environment on Complex Physics Content
Twyford, J., & Craig, S. D. (2016) · Journal of Educational Computing Research · doi:10.1177/0735633116667371 · Cited by 13 · see citing works
Predicting Dialogue Acts for Intelligent Virtual Agents with Multimodal Student Interaction Data.
Min, W., Wiggins, J. B., Pezzullo, L. G., Vail, A. K., Boyer, K. E., Mott, B., Frankosky, M. H., Wiebe, E., & Lester, J. C. (2016) · Educational Data Mining · Cited by 13 · see citing works
Self-citationCheng, J., Zhou, W., Lei, X., Adamo‐Villani, N., & Beneš, B. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49062-1_11 · Cited by 13 · see citing works
A Physically Embodied Robot Teacher (PERT) as a Facilitator for Peer Learning
Edwards, B. I., Muniru, I. O., Khougali, N., Cheok, A. D., & Prada, R. (2018) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2018.8658445 · Cited by 13 · see citing works
Pedagogical-Agent Learning Companions in a Virtual Reality Educational Experience
Novick, D., Afravi, M., Camacho, A., Rodriguez, A. E., & Hinojos, L. J. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21817-1_15 · Cited by 12 · see citing works
Math Trainer as a Chatbot Via System (Push) Messages for Android
Kabiljagić, M., Wachtler, J., Ebner, M., & Ebner, M. (2022) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v16i17.33351 · Cited by 12 · see citing works
What is instructional strategy? Seeking hidden dimensions
Gibbons, A. S. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-020-09820-2 · Cited by 12 · see citing works
Designing a Novel Robot Activist Model for Interactive Child Rights Education
Chew, E., Khan, U. S., & Lee, P. H. (2021) · International Journal of Social Robotics · doi:10.1007/s12369-021-00751-3 · Cited by 12 · see citing works
Web-Based Embodied Conversational Agents and Older People
Llorach, G., Agenjo, J., Blat, J., & Sayago, S. (2019) · Human-computer interaction series · doi:10.1007/978-3-030-06076-3_8 · Cited by 12 · see citing works
Use of Artificial Intelligence in Education: A Systematic Review
DUARTE, N., Pérez, Y. M., Beltran, A., & García, M. B. (2023) · International Conference on Industrial Engineering and Operations Management (IEOM) · doi:10.46254/sa04.20230169 · Cited by 18 · see citing works
The voice quality of pedagogical agent impacts learning and agent perceptions
Siegle, R. F., & Craig, S. D. (2024) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13027 · Cited by 11 · see citing works
Toward Caring Assessment Systems
Zapata‐Rivera, D. (2017) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3099023.3099106 · Cited by 11 · see citing works
Supporting Empathy Training Through Virtual Patients
Olsen, J. K., & Oertel, C. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-52240-7_43 · Cited by 11 · see citing works
Wiedbusch, M. D., Lester, J. C., & Azevedo, R. (2023) · Metacognition and Learning · doi:10.1007/s11409-023-09336-z · Cited by 11 · see citing works
Self-citationThe Impact of Artificial Intelligence (AI) and Robotics on Higher Education
Naqvi, G., Iqbal, F., Yousaf, J., & Tariq, R. (2023) · Journal of Management Practices Humanities and Social Sciences · doi:10.33152/jmphss-7.3.2 · Cited by 11 · see citing works
- Authors
- Johnson, W. L., & Lester, J. C.
- Affiliations
- Alelo (United States) (US)
- North Carolina State University (US)
- Corresponding author
- Johnson, W. Lewis
- Venue
- International Journal of Artificial Intelligence in Education
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 26
- Issue
- 1
- Pages
- 25-36
- ISSN
- 1560-4292 (ISSN-L)
- OpenAlex
- W2171876690
- Cited by
- 255
- References
- 37
- Citations by year
- 2026: 49 · 2025: 24 · 2024: 20 · 2023: 24 · 2022: 24 · 2021: 36 · 2020: 24 · 2019: 20 · 2018: 14 · 2017: 15 · 2016: 5
- FWCI
- 11.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
- Funders
- National Science Foundation (1321056, 1409639, 1138497, 1344803, 0822200, 1020229)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- educational agents, animated agents, face-to-face interaction, smart learning environments, game-based learning, immersive interfaces, educational robotics, human-agent interaction, learning outcomes
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review