Comparing virtual and location-based augmented reality mobile learning: emotions and learning outcomes

  • Jason M. Harley
  • Eric G. Poitras
  • Amanda Jarrell
  • Melissa C. Duffy
  • Susanne P. Lajoie
Research Article


Research on the effectiveness of augmented reality (AR) on learning exists, but there is a paucity of empirical work that explores the role that positive emotions play in supporting learning in such settings. To address this gap, this study compared undergraduate students’ emotions and learning outcomes during a guided historical tour using mobile AR applications. Data was collected in a laboratory (Study 1; N = 13) and outdoors (Study 2; N = 18) from thirty-one undergraduate students at a large North American university. Our findings demonstrated that learners were able to effectively and enjoyably learn about historical differences between past and present historical locations by contextualizing their visual representations, and that the two mobile AR apps were effective both in and outside of the laboratory. Learners were virtually situated in the historical location in Study 1 and physically visited the location in Study 2. In comparing results between studies, findings revealed that learners were able to identify more differences outdoors and required less scaffolding to identify differences. Learners reported high levels of enjoyment throughout both studies, but more enjoyment and less boredom in the outdoor study. Eye tracking results from Study 1 indicated that learners frequently compared historical information by switching their gaze between mobile devices and a Smart Board, which virtually situated them at the historical location. Results enhance our understanding of AR applications’ effectiveness in different contexts (virtual and location-based). Design recommendations for mobile AR apps are discussed.


Mobile learning Augmented reality Virtual reality Emotions History learning 



The research presented in this paper has been supported by a Joseph-Armand Bombardier Canada Graduate Scholarship for Doctoral research from the Social Sciences and Humanities Research Council (SSHRC) and a postdoctoral fellowship from the Fonds Québécois de recherche—Société et culture (FQRSC) awarded to the first author. This research has also been supported by funding from the Social Sciences and Humanities Research Council of Canada awarded to the fifth author and a doctoral fellowship from the Fonds Québécois de recherche—Société et culture (FQRSC) awarded to the fourth author. The authors would like to thank Laura Pipe, Emilia Gonzalez, Kexin Li, Mikaela Morton, and Hasagani Tissera for assisting in running participants, coding, and transcribing data. The authors would also like to thank Kevin Kee, Reza Feyzi-Behnagh, Gregory Trevors, and Daniel Beaudin for their feedback on the paper.


  1. Arroyo, I., Burelseon, W., Tai, M., Muldner, K., & Woolf, B. P. (2013). Gender differences in the use and benefit of advanced learning technologies for mathematics. Journal of Educational Psychology, 105, 957–969.CrossRefGoogle Scholar
  2. Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001). Recent advances in augmented reality. IEEE Computer Graphics and Applications, 21(6), 34–47.CrossRefGoogle Scholar
  3. Bondareva, D., Conati, C., Feyzi-Behnagh, R., Harley, J., Azevedo, R., and Bouchet, F. (2013). Inferring learning from gaze data during interaction with an environment to support self-regulated learning. In C. H. Lane, K. Yacef, J. Mostow, and P. Pavik (Eds.), Lecture Notes in Artificial Intelligence. Artificial Intelligence in Education (Vol. 7926, pp. 229–238). Berlin: Springer.Google Scholar
  4. Bressler, D. M. (2013). Museums: Gateways to mobile learning. In Z. Berge & L. Muilenburg (Eds.), Handbook of mobile education (pp. 224–234). Abingdon: Routledge.Google Scholar
  5. Broll, W., Lindt, I., Herbst, I., Ohlenburg, J., Braun, A. K., & Wetzel, R. (2008). Toward next-gen mobile AR games. IEEE Computer Graphics and Applications, 28(4), 40–48.CrossRefGoogle Scholar
  6. Bronack, S. C. (2011). The role of immersive media in online education. Journal of Continuing Higher Education, 59(2), 113–117.CrossRefGoogle Scholar
  7. Cocciolo, A., & Rabina, R. (2013). Does place affect user engagement and understanding? Mobile learner perceptions on the streets of New York. Journal of Documentation, 69, 98–120.CrossRefGoogle Scholar
  8. DeLucia, A., Francese, R., Passero, I., & Tortora, G. (2012). A collaborative augmented campus based on location-aware mobile technology. International Journal of Distance Education Technologies, 10, 55–73.CrossRefGoogle Scholar
  9. D’Mello, S. K., Lehman, B., & Person, N. (2010). Monitoring affect states during effortful problem solving activities. International Journal of Artificial Intelligence in Education, 20(4), 361–389.Google Scholar
  10. Harley, J. M. (2015). Measuring emotions: A survey of cutting-edge methodologies used in computer-based learning environment research. In S. Tettegaha & M. Gartmeier (Eds.), Emotions, Technology, Design, and Learning (pp. 89–114). London, UK: Academic Press, Elsevier.Google Scholar
  11. Harley, J. M., Bouchet, F., Hussain, S., Azevedo, R., & Calvo, R. (2015a). A multi-componential analysis of emotions during complex learning with an intelligent multi-agent system. Computers in Human Behavior, 48, 615–625.CrossRefGoogle Scholar
  12. Harley, J. M., Carter, C. K., Papaionnou, N., Bouchet, F., Azevedo, R., Landis, R. L., & Karabachian, L. R. (in press). Examining the predictive relationship between personality and emotion traits and students’ agent-direct emotions: Towards emotionally-adaptive agent-based learning environments. User Modeling and User-Adapted Interaction. Google Scholar
  13. Harley, J. M., Lajoie, S. P., Frasson, C., and Hall, N.C. (2015b). An integrated emotion-aware framework for intelligent tutoring systems. In C. Conati & N. Heffernan (Eds.), Lectures Notes in Artificial Intelligence. Artificial Intelligence in Education (Vol. 9112, pp. 620–624). Switzerland: Springer.Google Scholar
  14. Ioannidis, Y., Vayanou, M., Iatropoulou, K., Karvounis, M., Katifori, V., Kyriakidi, M.,… and Triantafyllidi, M. L. (2011). Preferences and attitudes for personalized information provision. Data Engineering, 34, 36–41Google Scholar
  15. Jaques, N., Conati, C., Harley, J. M., and Azevedo, R. (2014). Predicting affect from gaze behavior data during interactions with an intelligent tutoring system. In S. Trausan-Matu., K. Boyer., M. Crosby., K. Panourgia (Eds.) Lecture Notes in Computer Science. Intelligent Tutoring Systems (Vol. 8474, pp. 29–38). Switzerland: Springer.Google Scholar
  16. Katifori, A., Karvounis, M., Kourtis, V., Kyriakidi, M., Roussou, M., Tsangaris, M., Vayanou, M., Ioannidis, Y., Balet, O., Prados, T., Keil, J., Engelke, T., and Pujol, L. (2014). CHESS: Personalized Storytelling Experiences in Museums. In A. Mitchell (Ed.), The Seventh International Conference on Interactive Digital Storytelling, LNCS 8832 (pp. 232–235). Switzerland: Springer International Publishing.Google Scholar
  17. Keil, J., Pujol, L., Roussou, M., Engelke, T., Schmitt, M., Bockholt, U., and Eleftheratou, S. (2013). A digital look at physical museum exhibits: Designing personalized stories with Augmented Reality in museums. In Digital Heritage International Congress (DigitalHeritage) (Vol. 2, pp. 685–688). Marseille.Google Scholar
  18. Keil, J., Zollner, M., Becker, M., Wientapper, F., Engelke, T., and Wuest H. (2011). The House of Olbrich—An augmented reality tour through architectural history. IEEE International Symposium on Mixed and Augmented Reality (pp. 15–18).Google Scholar
  19. Klopfer, E. (2008). Augmented learning: Research and design of mobile educational games. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
  20. Klopfer, E., & Squire, K. (2008). Environmental Detectives—the development of an augmented reality platform for environmental simulations. Educational Technology Research and Development, 56(2), 203–228.CrossRefGoogle Scholar
  21. Mann, S., & Robinson, A. (2009). Boredom in the lecture theatre: An investigation into the contributors, moderators and outcomes of boredom amongst university students. British Educational Research Journal, 35, 243–258.CrossRefGoogle Scholar
  22. Martin, S., Diaz, G., Sancristobal, E., Gil, R., Castro, M., & Peire, J. (2011). New technology trends in education: Seven years of forecasts and convergence. Computers and Education, 57, 1893–1906.CrossRefGoogle Scholar
  23. Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 31–48). New York: Cambridge University Press.CrossRefGoogle Scholar
  24. Mayer, R. E. (2009). Multimedia learning (2nd ed.). New York: Cambridge University Press.CrossRefGoogle Scholar
  25. Mayer, R. E. (2014a). Incorporating motivation into multimedia learning. Learning and Instruction, 29, 171–173.CrossRefGoogle Scholar
  26. Mayer, R. E. (2014b). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 43–71). Cambridge: Cambridge Press.CrossRefGoogle Scholar
  27. Milgram, P., Takemura, H., Utsumi, A., & Kishino, F. (1994). Augmented reality: a class of displays on the reality–virtuality continuum. Proceedings the SPIE: Telemanipulator and Telepresence Technologies, 2351, 282–292.CrossRefGoogle Scholar
  28. Osborne, J. W., & Overbay, A. (2004). The power of outliers (and why researchers should always check for them). Practical Assessment Research Evaluation, 9, 1–8.Google Scholar
  29. Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341.CrossRefGoogle Scholar
  30. Pekrun, R., Frenzel, A. C., Goetz, T., & Perry, R. P. (2007). The control-value theory of achievement emotions: An integrative approach to emotions in education. In P. A. Schutz & R. Pekrun (Eds.), Emotion in education (pp. 13–36). San Diego: Academic Press.CrossRefGoogle Scholar
  31. Pekrun, R., Goetz, T., Daniels, L. M., Stupnisky, R. H., & Perry, R. P. (2010). Boredom in achievement settings: Control-value antecedents and performance outcomes of a neglected emotion. Journal of Educational Psychology, 102, 531–549.CrossRefGoogle Scholar
  32. Pekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011). Measuring emotions in students’ learning and performance: The achievement emotions questionnaire (AEQ). Contemporary Educational Psychology, 36, 34–48.CrossRefGoogle Scholar
  33. Pekrun, R., Goetz, T., Titz, W., & Perry, R. (2002). Academic achievement emotions in students’ self-regulated learning and achievement: A program of quantitative and qualitative research. Educational Psychologist, 37, 91–206.CrossRefGoogle Scholar
  34. Pekrun, R., Hall, N. C., Goetz, T., & Perry, R. (2014). Boredom and academic achievement: Testing a model of reciprocal causation. Journal of Educational Psychology, 106, 696–710.CrossRefGoogle Scholar
  35. Pekrun, R., & Perry, R. P. (2014). Control-value theory of achievement emotions. In R. Pekrun & L. Linnenbrink-Garcia (Eds.), International handbook of emotions in education (pp. 120–141). New York: Routledge.Google Scholar
  36. Pujol, L., Katifori, A., Vayanou, M., Roussou, M., Karvounis, M., Kyriakidi, M., Eleftheratou, S., and Ioannidis, Y. (2013). From personalization to adaptivity—Creating immersive visits through interactive digital storytelling at the Acropolis Museum. Workshop Proceedings of the 9th International Conference on Intelligent Environments (pp. 541–554).Google Scholar
  37. Rabina, D., and Cocciolo, A. (2012). Uncovering lost histories through GeoStoryteller: A digital GeoHumanities project. Digital Humanities, Hamburg, Germany.Google Scholar
  38. Rennick-Egglestone, S. J., Roussou, M., Brundell, P., Chaffardon, C., Kourtis, V., Koleva, B., and Benford, S. (2013). Indoors and outdoors: Designing mobile experiences for Cite de l’Espace. In NODEM (Network of Design and Digital Heritage) 2013 Conference: Beyond ControlThe Collaborative Museum and its Challenges (pp. 89–97). Stockholm, SwedenGoogle Scholar
  39. Rosenbaum, E., Klopfer, E., & Perry, J. (2007). On location learning: authentic applied science with networked augmented realities. Journal of Science Education and Technology, 16, 31–45.CrossRefGoogle Scholar
  40. Rothfarb, R. (2011). Mixing realities to connect people, places, and exhibits using mobile augmented-reality applications. Paper presented at the Meeting of Museums and the Web, Philadelphia, PA.Google Scholar
  41. Rouet, J. F., Britt, M. A., Mason, R. A., & Perfetti, C. A. (1996). Using multiple sources of evidence to reason about history. Journal of Educational Psychology, 88(3), 478–493.CrossRefGoogle Scholar
  42. Schreiber, W., Körber, A., Von Borries, B., Krammer, R., Leutner-Ramme, S., Mebus, S., Schöner, A., and Ziegler, B. (2006). Historisches Denken. Ein Kompetenz-Strukturmodell. [Historical Thinking. A model. A model of compentences] Ars una, Neuried, Germany.Google Scholar
  43. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Pearson Education/Allyn and Bacon.Google Scholar
  44. Tallon, L. (2013) Mobile strategy in 2013: An analysis of the annual museums and mobile survey. Pocket-Proof. Retrieved from:
  45. van Drie, J., & van Boxtel, C. (2008). Historical reasoning: Towards a framework for analyzing students’ reasoning about the past. Educational Psychology Review, 20, 87–110.CrossRefGoogle Scholar
  46. van Gog, T. (2014). The signaling (or cueing) principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 263–278). New York: Cambridge University Press.Google Scholar
  47. Vayanou, M., et al. (2014). Authoring personalized interactive museum stories. In A. Mitchell (Ed.), The Seventh International Conference on Interactive Digital Storytelling, LNCS 8832 (pp. 37–48). Switzerland: Springer International Publishing.Google Scholar
  48. Vayanou, M., Karvounis, M., Kyriakidi, M., Katifori, A., Manola, N., Roussou, M., and Ioannidis, Y. (2012). Towards Personalized Storytelling for Museum Visits. In The 6th International Workshop on Personalized Access, Profile Management, and Context Awareness in Databases (PersDB 2012). Istanbul, Turkey.Google Scholar
  49. Watt, J. D., & Vodanovich, S. J. (1999). Boredom proneness and psycho- social development. Journal of Psychology: Interdisciplinary and Ap- plied, 133, 303–314.CrossRefGoogle Scholar
  50. Wu, H., Lee, S. W., Chang, H., & Liang, J. (2013). Current status, opportunities, and challenges of augmented reality in education. Computers and Education, 62, 41–49.CrossRefGoogle Scholar
  51. Zhou, F., Duh, H. B. L., and Billinghurst, M. (2008). Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR. In Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (pp. 193–202). IEEE Computer Society.Google Scholar

Copyright information

© Association for Educational Communications and Technology 2016

Authors and Affiliations

  • Jason M. Harley
    • 1
    • 2
    • 3
  • Eric G. Poitras
    • 4
  • Amanda Jarrell
    • 2
  • Melissa C. Duffy
    • 2
  • Susanne P. Lajoie
    • 2
  1. 1.Department of Educational PsychologyUniversity of Alberta EdmontonAlbertaCanada
  2. 2.Department of Educational and Counselling PsychologyMcGill UniversityMontréalCanada
  3. 3.Department of Computer Science and Operations ResearchUniversité de MontréalMontréalCanada
  4. 4.Department of Educational PsychologyUniversity of UtahSalt Lake CityUSA

Personalised recommendations