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2022, 4(2): 153-172

Published Date:2022-4-20 DOI: 10.1016/j.vrih.2021.11.001

Motivation effect of animated pedagogical agent's personality and feedback strategy types on learning in virtual training environment


The personality and feedback of an animated pedagogical agent (APA) are vital social-emotional features that render the agent perceptually believable. Their effects on learning during virtual training need to be examined.
In this paper, an explanation model is proposed to clarify the underlying mechanism of how these two features affect learners. Two studies were conducted to investigate the model. In Study 1, the effect of the APA's personality type and feedback strategy on flow experience and performance was reexamined, revealing significant effects of the feedback strategy on flow and performance and a marginally significant effect of the personality type on performance. To explore the mechanism behind these effects, a theoretical model is proposed by distinguishing between intrinsic and extrinsic motivation effects. In Study 2, the model was evaluated, and the APA's personality type was found to significantly influence the factors in the path of the extrinsic motivation effect rather than those in the path of the intrinsic motivation effect.
In contrast, the feedback strategy affected factors in the path of the intrinsic motivation effect.
These results validated the proposed model. Further distinguishing the two motivation effects is necessary to understand the respective effects of an APA's personality and feedback features on learning experiences and outcomes.


Human-centered computing ; Visualization ; Visualization design and evaluation methods

Cite this article

Yulong BIAN, Chao ZHOU. Motivation effect of animated pedagogical agent's personality and feedback strategy types on learning in virtual training environment. Virtual Reality & Intelligent Hardware, 2022, 4(2): 153-172 DOI:10.1016/j.vrih.2021.11.001


1. Kim Y, Baylor A L, Shen E. Pedagogical agents as learning companions: the impact of agent emotion and gender. Journal of Computer Assisted Learning, 2007, 23(3): 220–234 DOI:10.1111/j.1365-2729.2006.00210.x

2. Dunsworth Q, Atkinson R K. Fostering multimedia learning of science: Exploring the role of an animated agent's image. Computers & Education, 2007, 49(3): 677–690 DOI:10.1016/j.compedu.2005.11.010

3. Kim C. The role of affective and motivational factors in designing personalized learning environments. Educational Technology Research and Development, 2012, 60(4): 563–584 DOI:10.1007/s11423-012-9253-6

4. Lin L J, Atkinson R K, Christopherson R M, Joseph S S, Harrison C J. Animated agents and learning: Does the type of verbal feedback they provide matter? Computers & Education, 2013, 67: 239–249 DOI:10.1016/j.compedu.2013.04.017

5. Beale R, Creed C. Affective interaction: How emotional agents affect users. International Journal of Human-Computer Studies, 2009, 67(9): 755–776 DOI:10.1016/j.ijhcs.2009.05.001

6. Terzis V, Moridis C N, Economides A A. The effect of emotional feedback on behavioral intention to use computer based assessment. Computers & Education, 2012, 59(2): 710–721 DOI:10.1016/j.compedu.2012.03.003

7. Bian Y L, Yang C L, Gao F Q, Li H Y, Zhou S S, Li H C, Sun X W, Meng X X. A framework for physiological indicators of flow in VR games: construction and preliminary evaluation. Personal and Ubiquitous Computing, 2016, 20(5): 821–832 DOI:10.1007/s00779-016-0953-5

8. Hu C, Walker M A, Neff M, Fox Tree J E. Storytelling agents with personality and adaptivity. In: Intelligent Virtual Agents. Cham: Springer International Publishing, 2015: 181–193 DOI:10.1007/978-3-319-21996-7_19

9. McRorie M, Sneddon I, McKeown G, Bevacqua E, de Sevin E, Pelachaud C. Evaluation of four designed virtual agent personalities. IEEE Transactions on Affective Computing, 2012, 3(3): 311–322 DOI:10.1109/t-affc.2011.38

10. Ogawa Y, Kikuchi H. Assigning a personality to a spoken dialogue agent by behavior reporting. New Generation Computing, 2017, 35(2): 181–209 DOI:10.1007/s00354-017-0012-4

11. Read S J, Miller L C. Virtual personalities: a neural network model of personality. Personality and Social Psychology Review, 2002, 6(4): 357–369 DOI:10.1207/s15327957pspr0604_10

12. Bian Y L, Yang C L, Guan D D, Xiao S, Gao F Q, Shen C A, Meng X X. Effects of pedagogical agent's personality and emotional feedback strategy on Chinese students' learning experiences and performance: a study based on virtual Tai Chi training studio. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. San Jose California, New York, NY, USA, ACM, 2016, 433–444 DOI:10.1145/2858036.2858351

13. Dekker T W G. Personality in embodied conversational agents: Effects on user experience. Proc. of 17th Twente Student Conference on IT, 2012

14. Hanna N, Richards D. The impact of virtual agent personality on a shared mental model with humans during collaboration. AAMAS, 2015, 1777–1778

15. Mumm J, Mutlu B. Designing motivational agents: The role of praise, social comparison, and embodiment in computer feedback. Computers in Human Behavior, 2011, 27(5): 1643–1650 DOI:10.1016/j.chb.2011.02.002

16. Shiban Y, Schelhorn I, Jobst V, Hörnlein A, Puppe F, Pauli P, Mühlberger A. The appearance effect: Influences of virtual agent features on performance and motivation. Computers in Human Behavior, 2015, 49: 5–11 DOI:10.1016/j.chb.2015.01.077

17. van der Meij H, van der Meij J, Harmsen R. Animated pedagogical agents effects on enhancing student motivation and learning in a science inquiry learning environment. Educational Technology Research and Development, 2015, 63(3): 381–403 DOI:10.1007/s11423-015-9378-5

18. Yılmaz R, Kılıç-Çakmak E. Educational interface agents as social models to influence learner achievement, attitude and retention of learning. Computers & Education, 2012, 59(2): 828–838 DOI:10.1016/j.compedu.2012.03.020

19. Chen C H, Chou M H. Enhancing middle school students' scientific learning and motivation through agent-based learning. Journal of Computer Assisted Learning, 2015, 31(5): 481–492 DOI:10.1111/jcal.12094

20. Lim H C, Stocker R, Barlow M, Larkin H. Interplay of ethical trust and social moral norms: Environment modelling and computational mechanisms in agent-based social simulation (ABSS). Web Intelligence and Agent Systems: an International Journal, 2011, 9(4): 377–391 DOI:10.3233/wia-2011-0225

21. Liew T W, Tan S M. Virtual agents with personality: Adaptation of learner-agent personality in a virtual learning environment. In: 2016 Eleventh International Conference on Digital Information Management (ICDIM). Porto, Portugal, IEEE, 2016, 157–162 DOI:10.1109/icdim.2016.7829758

22. Deci E L, Ryan R M. Intrinsic motivation and self-determination in human behavior. Springer Science & Business Media, 2013

23. Lepper M R, Corpus J H, Iyengar S S. Intrinsic and extrinsic motivational orientations in the classroom: Age differences and academic correlates. Journal of Educational Psychology, 2005, 97(2): 184

24. Lindebaum D. Rhetoric or remedy? A critique on developing emotional intelligence. Academy of Management Learning & Education, 2009, 8(2): 225–237 DOI:10.5465/amle.2009.41788844

25. Dinçer S, Doğanay A. The effects of multiple-pedagogical agents on learners’ academic success, motivation, and cognitive load. Computers & Education, 2017, 111: 74–100 DOI:10.1016/j.compedu.2017.04.005

26. Ryan R M, Deci E L. Intrinsic and extrinsic motivations: classic definitions and new directions. Contemporary Educational Psychology, 2000, 25(1): 54–67 DOI:10.1006/ceps.1999.1020

27. Reeve J, Deci E L. Elements of the competitive situation that affect intrinsic motivation. Personality and Social Psychology Bulletin, 1996, 22(1): 24–33 DOI:10.1177/0146167296221003

28. Vansteenkiste M, Deci E L. Competitively contingent rewards and intrinsic motivation: can losers remain motivated? Motivation and Emotion, 2003, 27(4): 273–299 DOI:10.1023/a:1026259005264

29. Nass C, Moon Y. Machines and mindlessness: social responses to computers. Journal of Social Issues, 2000, 56(1): 81–103 DOI:10.1111/0022-4537.00153

30. Vasile C. Impulsivity dynamics in Romanian teachers’ personality. Procedia-Social and Behavioral Sciences, 2012, 69: 2101–2107 DOI:10.1016/j.sbspro.2012.12.172

31. Fortier M S, Vallerand R J, Guay F. Academic motivation and school performance: toward a structural model. Contemporary Educational Psychology, 1995, 20(3): 257–274 DOI:10.1006/ceps.1995.1017

32. Schneider T R. The role of neuroticism on psychological and physiological stress responses. Journal of Experimental Social Psychology, 2004, 40(6): 795–804 DOI:10.1016/j.jesp.2004.04.005

33. Sträfling N, Fleischer I, Polzer C, Leutner D, Krämer N C. Teaching learning strategies with a pedagogical agent. Journal of Media Psychology, 2010, 22(2): 73–83 DOI:10.1027/1864-1105/a000010

34. Bian Y L, Zhou C, Chen Y Q, Zhao Y S, Liu J, Yang C L. The role of the field dependence-independence construct on the flow-performance link in virtual reality. In: Symposium on Interactive 3D Graphics and Games. San Francisco CA USA, New York, NY, USA, ACM, 2020, 1–9 DOI:10.1145/3384382.3384529

35. Shi B, Hu Y G, Shi F A. Study on the appraisal criteria of university students' 24-stroke Taiji. Journal of Nanyang Teachers’ College (Natural Sciences Edition), 2003, 2(3): 3–5

36. Pintrich P R, de Groot E V. Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 1990, 82(1): 33–40 DOI:10.1037/0022-0663.82.1.33

37. Hung C Y, Sun J C Y, Yu P T. The benefits of a challenge: student motivation and flow experience in tablet-PC-game-based learning. Interactive Learning Environments, 2015, 23(2): 172–190 DOI:10.1080/10494820.2014.997248

38. Guay F, Vallerand R J, Blanchard C. On the assessment of situational intrinsic and extrinsic motivation: the situational motivation scale (SIMS). Motivation and Emotion, 2000, 24(3): 175–213 DOI:10.1023/a:1005614228250

39. Meehan M, Insko B, Whitton M, Brooks F P. Physiological measures of presence in stressful virtual environments. ACM Transactions on Graphics, 2002, 21(3): 645–652 DOI:10.1145/566654.566630

40. Li J Y, Zhou M X, Yang H H, Mark G. Confiding in and listening to virtual agents: the effect of personality. In: Proceedings of the 22nd International Conference on Intelligent User Interfaces. Limassol Cyprus, New York, NY, USA, ACM, 2017, 275–286 DOI:10.1145/3025171.3025206

41. Reeves B, Nass C. The media equation: How people treat computers, television, and new media like real people. Cambridge, United Kingdom: Cambridge university press, 1996

42. Borjigin A, Miao C Y, Lim S F, Li S Y, Shen Z Q. Teachable agents with intrinsic motivation. In: Lecture Notes in Computer Science. Cham: Springer International Publishing, 2015, 34–43 DOI:10.1007/978-3-319-19773-9_4

43. Jung J H, Schneider C, Valacich J. Enhancing the motivational affordance of information systems: the effects of real-time performance feedback and goal setting in group collaboration environments. Management Science, 2010, 56(4): 724–742 DOI:10.1287/mnsc.1090.1129

44. Landers R N, Bauer K N, Callan R C. Gamification of task performance with leaderboards: a goal setting experiment. Computers in Human Behavior, 2017, 71: 508–515 DOI:10.1016/j.chb.2015.08.008

45. Oinas-Kukkonen H. A foundation for the study of behavior change support systems. Personal and Ubiquitous Computing, 2013, 17(6): 1223–1235 DOI:10.1007/s00779-012-0591-5

46. Santhanam R, Liu D, Shen W C M. Research note—gamification of technology-mediated training: not all competitions are the same. Information Systems Research, 2016, 27(2): 453–465 DOI:10.1287/isre.2016.0630

47. Orji R, Vassileva J, Mandryk R L. Modeling the efficacy of persuasive strategies for different gamer types in serious games for health. User Modeling and User-Adapted Interaction, 2014, 24(5): 453–498 DOI:10.1007/s11257-014-9149-8

48. Deterding S. The lens of intrinsic skill atoms: a method for gameful design. Human-Computer Interaction, 2015, 30(3/4): 294–335 DOI:10.1080/07370024.2014.993471

49. Morschheuser B, Riar M, Hamari J, Maedche A. How games induce cooperation? A study on the relationship between game features and we-intentions in an augmented reality game. Computers in Human Behavior, 2017, 77: 169–183 DOI:10.1016/j.chb.2017.08.026

50. Sundar S S, Bellur S, Jia H Y. Motivational technologies: a theoretical framework for designing preventive health applications. Persuasive Technology. Design for Health and Safety, 2012, 112–122 DOI:10.1007/978-3-642-31037-9_10

51. Page R E, Kray C. Ethics and persuasive technology: An exploratory study in the context of healthy living. NIMD2010, 2010

52. Halko S, Kientz J A. Personality and persuasive technology: an exploratory study on health-promoting mobile applications. Persuasive Technology, 2010, 150–161 DOI:10.1007/978-3-642-13226-1_16

53. Shute V J. Focus on formative feedback. Review of Educational Research, 2008, 78(1): 153–189 DOI:10.3102/0034654307313795


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