Advertisement

Interactive virtual technologies in engineering education: Why not 360° videos?

  • Maria Grazia ViolanteEmail author
  • Enrico Vezzetti
  • Pietro Piazzolla
Original Paper
  • 6 Downloads

Abstract

Interactive learning experiences are becoming the standard for today’s ‘tech-savvy’ generation of students and an important issue for research in instructional technology. The design and implementation of higher education, incorporating interactive technologies, can be difficult and often requires high levels of design knowledge. Our intent is to assist researchers, instructors and designers in identifying an effective methodology to design interactive learning contents that use recent interactive technologies, in particular 360° video, and encourage greater student engagement. In this study, 360° videos have been designed and implemented in an engineering program but the design methodology we suggest can be apply in any industrial or educational context. Then, 360° videos have been evaluated by the students as highly immersive and engaged environments that surround them and offer them an increased sense of presence, giving them a 360-degree view of the environment. In this type of video, viewers no longer only look at a single screen, they can point the camera lens wherever they want, allowing viewers to watch the video from multiple perspectives (active), rather than only from the director’s point of view (passive).

Keywords

360° video Student engagement Virtual reality Engineering education 

Notes

Acknowledgements

The authors wish to thank Erasmus+programme that with the project 2016-1-DK01-KA202-022320 supported this work financially

References

  1. 1.
    Appleton, J.J., Christenson, S.L., Furlong, M.J.: Student engagement with school: critical conceptual and methodological issues of the construct. Psychol. Schools 45(5), 369–386 (2008).  https://doi.org/10.1002/pits.20303 Google Scholar
  2. 2.
    Argyriou, L., Economou, D., Bouki, V. 360-degree interactive video application for Cultural Heritage Education. In: 3rd Annual International Conference of the Immersive Learning Research Network. Coimbra, Portugal 29 Jun–26 Jul 2017 Verlag der Technischen Universität Graz (2017)Google Scholar
  3. 3.
    Baddeley, A.D.: Human Memory: Theory and Practice. Psychology Press, Hove (1997)Google Scholar
  4. 4.
    Bangert-Drowns, R.L., Pyke, C.: A taxonomy of student engagement with educational software: an exploration of literate thinking with electronic text. J. Educ. Comput. Res. 24(3), 213–234 (2001)Google Scholar
  5. 5.
    Barkatsas, A., Kasimatis, K., Gialamas, V.: Learning secondary mathematics with technology: exploring the complex interrelationship between students’ attitudes, engagement, gender and achievement. Comput. Education 52(3), 562–570 (2009).  https://doi.org/10.1016/j.compedu.2008.11.001 Google Scholar
  6. 6.
    Baronio, G., Motyl, B., Paderno, D.: Technical drawing learning tool-level 2: an interactive self-learning tool for teaching manufacturing dimensioning. Comput. Appl. Eng. Educ. 24(4), 519–528 (2016).  https://doi.org/10.1002/cae.21728 Google Scholar
  7. 7.
    Boucheix, J.-M., Lowe, R.K., Putri, D.K., Groff, J.: Cueing animations: dynamic signaling aids information extraction and comprehension. Learn. Instr. 25, 71–84 (2013)Google Scholar
  8. 8.
    Chen, P.-S.D., Lambert, A.D., Guidry, K.R.: Engaging online learners: the impact of Web-based learning technology on college student engagement. Comput. Educ. 54(4), 1222–1232 (2010).  https://doi.org/10.1016/j.compedu.2009.11.008 Google Scholar
  9. 9.
    Christenson, S. L., Reschly, A. L., Wylie, C. (eds.) Handbook of research on student engagement. Springer. New York (2012)Google Scholar
  10. 10.
    Coller, B.D., Shernoff, D.J.: Video game-based education in mechanical engineering: a look at student engagement. Int. J. Eng. Educ. 25(2), 308 (2009)Google Scholar
  11. 11.
    Connell, J. P., Wellborn, J. G. Competence, autonomy, and relatedness: a motivational analysis of self-system processes. In Gunnar, M.R., Sroufe, L.A., (eds.) Minnesota Symposia on Child Psychology, Vol. 23, pp. 43–77. Lawrence Erlbaum, Hillsdale, NJ, US (1991)Google Scholar
  12. 12.
    Crowell, T.L.: Student self grading: perception vs reality. Am. J. Educ. Res. 3(4), 450–455 (2015)Google Scholar
  13. 13.
    Csikszentmihalyi, M.: Finding Flow: The Psychology of Engagement with Everyday Life. Basic Books, New York (1997)Google Scholar
  14. 14.
    Csikszentmihalyi, M., Rathunde, K., Whalen, S.: Talented Teenagers: The Roots of Success and Failure. Cambridge University Press, Cambridge (1997)Google Scholar
  15. 15.
    D’mello, S., Graesser, A.: AutoTutor and affective autotutor: learning by talking with cognitively and emotionally intelligent computers that talk back. ACM Trans. Interact. Intell. Syst. 2(4), 1–39 (2013).  https://doi.org/10.1145/2395123.2395128 Google Scholar
  16. 16.
    DeRobertis, E.M.: The Phenomenology of Learning and Becoming: Enthusiasm, Creativity, and Self-development. Springer, Berlin (2017)Google Scholar
  17. 17.
    Fischer, X., Nadeau, J.-P.: Research in Interactive Design, vol. 3. Springer, Paris (2011)Google Scholar
  18. 18.
    Fredricks, J.A., Blumenfeld, P.C., Paris, A.H.: School engagement: potential of the concept, State of the evidence. Rev. Educ. Res. 74(1), 59–109 (2004).  https://doi.org/10.3102/00346543074001059 Google Scholar
  19. 19.
    Gallini, J. K., Barron, D.: Participants’ perceptions of web-infused environments: A survey of teaching beliefs, learning approaches, and communication. J. Res. Technol Educ. 34(2), 139–156 (2001)Google Scholar
  20. 20.
    Giesbers, B., Rienties, B., Tempelaar, D., Gijselaers, W.: A dynamic analysis of the interplay between asynchronous and synchronous communication in online learning: the impact of motivation. J. Comput. Assist. Learn. 30(1), 30–50 (2014).  https://doi.org/10.1111/jcal.12020 Google Scholar
  21. 21.
    Guertin, L.A., Zappe, S.E., Kim, H.: Just-in-time teaching exercises to engage students in an introductory-level dinosaur course. J. Sci. Educ. Technol. 16(6), 507–514 (2007)Google Scholar
  22. 22.
    Sellen, A., Rogers, Y., Harper, R., & Rodden, T.: Reflecting human values in the digital age. Commun. ACM, 52(3), 58–66 (2009).  https://doi.org/10.1145/1467247.1467265 Google Scholar
  23. 23.
    Hedley, N.R., Billinghurst, M., Postner, L., May, R., Kato, H.: Explorations in the use of augmented reality for geographic visualization. Presence Teleoperators Virtual Environ. 11(2), 119–133 (2002)Google Scholar
  24. 24.
    Henrie, C.R., Halverson, L.R., Graham, C.R.: Measuring student engagement in technology-mediated learning: a review. Comput. Educ. 90, 36–53 (2015).  https://doi.org/10.1016/j.compedu.2015.09.005 Google Scholar
  25. 25.
    Hew, K.F.: Promoting engagement in online courses: what strategies can we learn from three highly rated MOOCS. Br. J. Educ. Technol. 47(2), 320–341 (2016).  https://doi.org/10.1111/bjet.12235 Google Scholar
  26. 26.
    Hidi, S.: Interest and its contribution as a mental resource for learning. Rev. Educ. Res. 60(4), 549–571 (1990)Google Scholar
  27. 27.
    Huang, T.-L., Hsu Liu, F.: Formation of augmented-reality interactive technology’s persuasive effects from the perspective of experiential value. Internet Res. 24(1), 82–109 (2014)Google Scholar
  28. 28.
    Inan, H.Z., Inan, T.: 3Hs education: examining hands-on, heads-on and hearts-on early childhood science education. Int. J. Sci. Educ. 37(12), 1974–1991 (2015).  https://doi.org/10.1080/09500693.2015.1060369 Google Scholar
  29. 29.
    Junco, R., Heiberger, G., Loken, E.: The effect of Twitter on college student engagement and grades. J. Comput. Assist. Learn. 27(2), 119–132 (2011).  https://doi.org/10.1111/j.1365-2729.2010.00387.x Google Scholar
  30. 30.
    Kay, R.: Evaluating learning, design, and engagement in web-based learning tools (WBLTs): the WBLT evaluation scale. Comput. Human Behav. 27(5), 1849–1856 (2011)Google Scholar
  31. 31.
    King, M.B., Newmann, F., Carmichael, D.: Authentic intellectual work: common standards for teaching social studies. Soc. Educ. 73(1), 43–49 (2009)Google Scholar
  32. 32.
    Newman, F.M., Wehlage, G.G. and Lamborn, S.D.: The Significance and Sources of Student Engagement. In: Newman, F.M. (eds.) Student Engagement and Achievement in American Secondary Schools, pp. 11–39. Teachers College Press, New York (1992)Google Scholar
  33. 33.
    Liang, H.-N., Sedig, K.: Can interactive visualization tools engage and support pre-university students in exploring non-trivial mathematical concepts? Comput. Educ. 54(4), 972–991 (2010).  https://doi.org/10.1016/j.compedu.2009.10.001 Google Scholar
  34. 34.
    Lim, C.P., Nonis, D., Hedberg, J.: Gaming in a 3D multiuser virtual environment: engaging students in science lessons. Br. J. Educ. Technol. 37(2), 211–231 (2006)Google Scholar
  35. 35.
    Mayer, R.E.: Applying the science of learning: evidence-based principles for the design of multimedia instruction. Am. Psychol. 63(8), 760–769 (2008).  https://doi.org/10.1037/0003-066X.63.8.760 Google Scholar
  36. 36.
    Mayer, R. E., Fiore, L. (2014). Principles for reducing extraneous processing in multimedia learning: coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In: The Cambridge Handbook of Multimedia Learning, 2nd ed. (pp. 279–315). New York, NY, US: Cambridge University PressGoogle Scholar
  37. 37.
    Mayer, R.E., Heiser, J., Lonn, S.: Cognitive constraints on multimedia learning: when presenting more material results in less understanding. J. Educ. Psychol. 93(1), 187–198 (2001).  https://doi.org/10.1037/0022-0663.93.1.187 Google Scholar
  38. 38.
    Missett, T.C., Reed, C.B., Scot, T.P., Callahan, C.M., Slade, M.: Describing learning in an advanced online case-based course in environmental science. J. Adv. Acad. 22(1), 10–50 (2010)Google Scholar
  39. 39.
    Morrison, G.M., Robertson, L., Laurie, B., Kelly, J.: Protective factors related to antisocial behavior trajectories. J. Clin. Psychol. 58(3), 277–290 (2002).  https://doi.org/10.1002/jclp.10022 Google Scholar
  40. 40.
    Neumann, D. L., Hood, M. The effects of using a wiki on student engagement and learning of report writing skills in a university statistics course. Aust. J. Educ. Technol. 25(3) (2009)Google Scholar
  41. 41.
    Paivio, A.: Mental Representations: A Dual Coding Approach. Oxford University Press, Oxford (1986)Google Scholar
  42. 42.
    Peters, L., Shmerling, S., Karren, R.: Constructivist pedagogy in asynchronous online education: examining proactive behavior and the impact on student engagement levels. Int. J. E-Learning 10(3), 311–330 (2011)Google Scholar
  43. 43.
    Pintrich, P. R., DeGroot, E. Quantitative and qualitative perspectives on student motivational beliefs and self-regulated learning. In: Paper presented at the Annual Meeting of the American Educational Research Association, Boston, MA (1990)Google Scholar
  44. 44.
    Price, L., Richardson, J. T., Jelfs, A.: Face-to-face versus online tutoring support in distance education. Stud. High. Educ. 32(1), 1–20 (2007)Google Scholar
  45. 45.
    Ryan, R.M., Deci, E.L.: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55(1), 68 (2000)Google Scholar
  46. 46.
    Schiefele, U., Krapp, A., Winteler, A. Interest as a predictor of academic achievement: a meta-analysis of research. In: The role of interest in learning and development. pp. 183–212. Lawrence Erlbaum Associates, Inc., Hillsdale, NJ, US (1992)Google Scholar
  47. 47.
    Schmidt, J. A., Shernoff, D. J., Csikszentmihalyi, M. Individual and situational factors related to the experience of flow in adolescence. Applications of Flow in Human Development and Education (pp. 379-405): Springer (2014)Google Scholar
  48. 48.
    Sharp, H., Rogers, Y., Preece, J.: Interaction Design: Beyond Human Computer Interaction. Wiley, Hoboken (2007)Google Scholar
  49. 49.
    Shernoff, D. J., Csikszentmihalyi, M.: Cultivating engaged learners and optimal learning environments. In: Furlong, M. J., Gilman, R., & Huebner, E. S. (eds.) Handbook of Positive Psychology in Schools, pp. 131–145. Taylor & Francis, Florence, KY (2009)Google Scholar
  50. 50.
    Shernoff, D. J., Csikszentmihalyi, M., Schneider, B., Shernoff, E. S.: Student engagement in high school classrooms from the perspective of flow theory.In: Applications of Flow in Human Development and Education: The Collected Works of Mihaly Csikszentmihalyi, pp. 475-494. Springer, Netherlands (2014)Google Scholar
  51. 51.
    Skinner, E. A., Kindermann, T. A., Connell, J. P., & Wellborn, J. G. Engagement and disaffection as organizational constructs in the dynamics of motivational development. In: Handbook of Motivation at School, pp. 223–245. Routledge/Taylor & Francis Group, New York, NY, US (2009)Google Scholar
  52. 52.
    Skinner, E.A., Kindermann, T.A., Furrer, C.J.: A motivational perspective on engagement and disaffection: conceptualization and assessment of children’s behavioral and emotional participation in academic activities in the classroom. Educ. Psychol. Meas. 69(3), 493–525 (2009)MathSciNetGoogle Scholar
  53. 53.
    Skinner, E. A., Pitzer, J. R. Developmental dynamics of student engagement, coping, and everyday resilience. In: Handbook of Research on Student Engagement (pp. 21–44): Springer (2012)Google Scholar
  54. 54.
    Spence, C., Gallace, A.: Multisensory design: reaching out to touch the consumer. Psychol. Mark. 28(3), 267–308 (2011)Google Scholar
  55. 55.
    Sun, J.C.Y., Rueda, R.: Situational interest, computer self-efficacy and self-regulation: their impact on student engagement in distance education. Br. J. Educ. Technol. 43(2), 191–204 (2012)Google Scholar
  56. 56.
    Thompson, J.R., Klass, P.H., Fulk, B.M.: Comparing online and face-to-face presentation of course content in an introductory special education course. Teach. Educ. Special Educ. 35(3), 228–242 (2012)Google Scholar
  57. 57.
    Vandell, D.L., Shernoff, D.J., Pierce, K.M., Bolt, D.M., Dadisman, K., Brown, B.B.: Activities, engagement, and emotion in after-school programs (and elsewhere). New Dir. Stud. Leadersh. 2005(105), 121–129 (2005)Google Scholar
  58. 58.
    Vergara, D., Rubio, M.P., Lorenzo, M.: On the design of virtual reality learning environments in engineering. Multimodal Technol. Interact. 1(2), 11 (2017)Google Scholar
  59. 59.
    Vi, C. T., Ablart, D., Gatti, E., Velasco, C., Obrist, M. Not just seeing, but also feeling art: mid-air haptic experiences integrated in a multisensory art exhibition. Int. J. Human Comput. Stud. 108, 1–14 (2017).  https://doi.org/10.1016/j.ijhcs.2017.06.004 Google Scholar
  60. 60.
    Violante, M.G., Vezzetti, E.: Implementing a new approach for the design of an e-learning platform in engineering education. Comput. Appl. Eng. Educ. 22(4), 708–727 (2014)Google Scholar
  61. 61.
    Violante, M. G., Vezzetti, E.: Design and implementation of 3D Web-based interactive medical devices for educational purposes. Int. J. Interact. Design Manuf. (IJIDeM) 11(1), 31–44 (2017).  https://doi.org/10.1007/s12008-015-0277-0 Google Scholar
  62. 62.
    Violante, M.G., Vezzetti, E.: Virtual interactive e-learning application: an evaluation of the student satisfaction. Comput. Appl. Eng. Educ. 23(1), 72–91 (2015)Google Scholar
  63. 63.
    Violante, M.G., Vezzetti, E.: Guidelines to design engineering education in the twenty-first century for supporting innovative product development. Eur. J. Eng. Educ. (2017).  https://doi.org/10.1080/03043797.2017.1293616 Google Scholar
  64. 64.
    Wang, P.-Y., Vaughn, B.K., Liu, M.: The impact of animation interactivity on novices’ learning of introductory statistics. Comput. Educ. 56(1), 300–311 (2011)Google Scholar
  65. 65.
    Wigfield, A., Eccles, J.S.: Expectancy–value theory of achievement motivation. Contemp. Educ. Psychol. 25(1), 68–81 (2000)Google Scholar
  66. 66.
    Wittrock, M.C.: Generative processes of comprehension. Educ. Psychol. 24(4), 345–376 (1989).  https://doi.org/10.1207/s15326985ep2404_2 Google Scholar
  67. 67.
    Woolf, B.P., Arroyo, I., Cooper, D., Burleson, W., Muldner, K.: Affective tutors: automatic detection of and response to student emotion. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds.) Advances in Intelligent Tutoring Systems, pp. 207–227. Springer, Berlin (2010)Google Scholar
  68. 68.
    Xu, Y.: Examining the effects of digital feedback on student engagement and achievement. J. Educ. Comput. Res. 43(3), 275–291 (2010)Google Scholar
  69. 69.
    Yang, Y.-F.: Engaging students in an online situated language learning environment. Comput. Assist. Lang. Learn. 24(2), 181–198 (2011).  https://doi.org/10.1080/09588221.2010.538700 Google Scholar
  70. 70.
    Yoon, S.-Y., Choi, Y.J., Oh, H.: User attributes in processing 3D VR-enabled showroom: gender, visual cognitive styles, and the sense of presence. Int. J. Human Comput. Stud. 82, 1–10 (2015).  https://doi.org/10.1016/j.ijhcs.2015.04.002 Google Scholar
  71. 71.
    Zhu, E.: Interaction and cognitive engagement: an analysis of four asynchronous online discussions. Instr. Sci. 34(6), 451–480 (2006)Google Scholar

Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.DIGEP-Department of Management and Production EngineeringPolitecnico di TorinoTurinItaly

Personalised recommendations