360-degree video in education: An overview and a comparative social media data analysis of the last decade

Γεώργιος Λαμπρόπουλος1, Vassilis Barkoukis2, Kevin Burden3, Theofylaktos Anastasiadis2
1Department of Information and Electronic Engineering, International Hellenic University, Thessaloniki, Greece
2Department of Physical Education and Sport Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
3Faculty of Arts, Cultures and Education, University of Hull, Hull, United Kingdom

Tóm tắt

Abstract

Due to its immersive and interactive nature, 360-degree video is becoming ever more popular. However, little is known about the public’s viewpoints and attitudes regarding the use of this emerging technology in educational contexts. This study reviews the research evidence for 360° video, virtual learning environments and social media and presents related studies. Moreover, the methodology, the tools and the analysis process used to comparatively analyze social media data are presented and the results that arose are showcased. The use of 360° video in education is discussed and directions for future research are given. Based on the data from the last 10 years, the main findings of the study show that 360° video and its use in educational settings are recognized positively by the public who mostly express anticipation, trust and joy when referring to it. Nonetheless, teachers are unfamiliar with 360° video and do not have the necessary technical skills to develop educational material using it or incorporating it into teaching activities. Finally, 360° video is proven to be an effective educational tool which satisfies the emerging educational needs, enriches the teaching and learning process and promotes students’ motivation, active participation and engagement, rendering, thus, learning more effective.

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Tài liệu tham khảo

Ahuja, S., & Dubey, G. (2017). Clustering and sentiment analysis on twitter data (pp. 1–5). https://doi.org/10.1109/TEL-NET.2017.8343568

Alexander, B., Ashford-Rowe, K., Barajas-Murph, N., Dobbin, G., Knott, J., McCormack, M., Pomerantz, J., Seilhamer, R., Weber, N. (2019). Horizon report 2019 higher education edition. Technical report, EDUCAUSE. Accessed 22 Feb 2021.

Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the student engagement instrument. Journal of School Psychology, 44(5), 427–445. https://doi.org/10.1002/pits.20303.

Barreda-Ángeles, M., Aleix-Guillaume, S., Pereda-Baños, A. (2020). Virtual reality storytelling as a double-edged sword: Immersive presentation of nonfiction 360-video is associated with impaired cognitive information processing. In Communication monographs (pp. 1–20). https://doi.org/10.1080/03637751.2020.1803496.

Berns, A., Mota, J. M., Ruiz-Rube, I., & Dodero, J. M. (2018). Exploring the potential of a 360 video application for foreign language learning. In Proceedings of the sixth international conference on technological ecosystems for enhancing multiculturality (pp. 776–780). https://doi.org/10.1145/3284179.3284309.

Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230. https://doi.org/10.1111/j.1083-6101.2007.00393.x

Bruns, A., Highfield, T., & Lind, R. A. (2012). Blogs, twitter, and breaking news: The produsage of citizen journalism. Produsing Theory in a Digital World: The Intersection of Audiences and Production in Contemporary Theory, 80, 15–32.

Chou, S. W., & Liu, C. H. (2005). Learning effectiveness in a web-based virtual learning environment: A learner control perspective. Journal of Computer Assisted Learning, 21(1), 65–76. https://doi.org/10.1111/j.1365-2729.2005.00114.x.

Coller, B. D., & Shernoff, D. J. (2009). Video game-based education in mechanical engineering: A look at student engagement. International Journal of Engineering Education, 25(2), 308.

Corazza, M., Menini, S., Cabrio, E., Tonelli, S., & Villata, S. (2020). A multilingual evaluation for online hate speech detection. ACM Transactions on Internet Technology (TOIT), 20(2), 1–22. https://doi.org/10.1145/3377323

Dede, C. (2009). Immersive interfaces for engagement and learning. Science, 323(5910), 66–69. https://doi.org/10.1126/science.1167311.

DiLullo, C., McGee, P., & Kriebel, R. M. (2011). Demystifying the millennial student: A reassessment in measures of character and engagement in professional education. Anatomical Sciences Education, 4(4), 214–226. https://doi.org/10.1002/ase.240.

Dooley, K. (2017). Storytelling with virtual reality in 360-degrees: A new screen grammar. Studies in Australasian Cinema, 11(3), 161–171. https://doi.org/10.1080/17503175.2017.1387357.

Dunaway, J., & Soroka, S. (2021). Smartphone-size screens constrain cognitive access to video news stories. Information, Communication & Society, 24(1), 69–84. https://doi.org/10.1080/1369118X.2019.1631367

Dwyer, C., Hiltz, S., & Passerini, K. (2007). Trust and privacy concern within social networking sites: A comparison of Facebook and myspace. In AMCIS 2007 proceedings (p. 339). https://aisel.aisnet.org/amcis2007/339/.

Elbagir, S., & Yang, J. (2019). Twitter sentiment analysis using natural language toolkit and vader sentiment. In Proceedings of the international multiconference of engineers and computer scientists (Vol. 122, p. 16).

Fernandez, M. (2017). Augmented virtual reality: How to improve education systems. Higher Learning Research Communications, 7(1), 1–15. https://doi.org/10.18870/hlrc.v7i1.373.

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.1089/cyber.2017.0295.

Gaebel, M., Kupriyanova, V., Morais, R., & Colucci, E. (2014). E-learning in European higher education institutions. European University Association.

Gil de Zúñiga, H., Diehl, T., Huber, B., & Liu, J. (2017). Personality traits and social media use in 20 countries: How personality relates to frequency of social media use, social media news use, and social media use for social interaction. Cyberpsychology, Behavior, and Social Networking, 20(9), 540–552. https://doi.org/10.1089/cyber.2017.0295

Harrington, C. M., Kavanagh, D. O., Ballester, G. W., Ballester, A. W., Dicker, P., Traynor, O., et al. (2018). 360 operative videos: A randomised cross-over study evaluating attentiveness and information retention. Journal of Surgical Education, 75(4), 993–1000. https://doi.org/10.1016/j.jsurg.2017.10.010.

Henard, F., & Roseveare, D. (2012). Fostering quality teaching in higher education: Policies and practices. An IMHE Guide for Higher Education Institutions (pp. 7–11). http://learningavenue.fr/assets/pdf/QT%20policies%20and%20practices.pdf.

Hew, K. F. (2016). Promoting engagement in online courses: What strategies can we learn from three highly rated MOOCS. British Journal of Educational Technology, 47(2), 320–341. https://doi.org/10.1111/bjet.12235.

Hodgson, P., Lee, V. W., Chan, J. C., Fong, A., Tang, C. S., Chan, L., & Wong, C. (2019). Immersive virtual reality (IVR) in higher education: Development and implementation. In Augmented reality and virtual reality (pp. 161–173). Springer. https://doi.org/10.1007/978-3-030-06246-0_12.

Howe, J. (2006). The rise of crowdsourcing. Wired Magazine, 14(6), 1–4.

Huang, H. M., Rauch, U., & Liaw, S. S. (2010). Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Computers & Education, 55(3), 1171–1182. https://doi.org/10.1016/j.compedu.2010.05.014.

Hunter, J. (2007). Matplotlib: A 2D graphics environment. Computing in Science Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55.

Hutchins, E. (1995). Cognition in the wild. MIT Press. https://doi.org/10.7551/mitpress/1881.001.0001.

Hutto, C., & Gilbert, E. (2014). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Proceedings of the international AAAI conference on web and social media (vol. 8).

Java, A., Song, X., Finin, T., & Tseng, B. (2007). Why we twitter: Understanding microblogging usage and communities. In Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis (pp. 56–65). https://doi.org/10.1145/1348549.1348556.

Kaplan, A., & Haenlein, M. (2009). Consumer use and business potential of virtual worlds: The case of second life. The International Journal on Media Management, 11(3–4), 93–101. https://doi.org/10.1080/14241270903047008.

Kilteni, K., Groten, R., & Slater, M. (2012). The sense of embodiment in virtual reality. Presence: Teleoperators and Virtual Environments, 21(4), 373–387. https://doi.org/10.1162/PRES_a_00124

Lampropoulos, G., Keramopoulos, E., & Diamantaras, K. (2020). Enhancing the functionality of augmented reality using deep learning, semantic web and knowledge graphs: A review. Visual Informatics, 4(1), 32–42. https://doi.org/10.1016/j.visinf.2020.01.001

Liu, D., Bhagat, K. K., Gao, Y., Chang, T. W., & Huang, R. (2017). The potentials and trends of virtual reality in education. In Virtual, augmented, and mixed realities in education (pp. 105–130). Springer. https://doi.org/10.1007/978-981-10-5490-7_1.

Liu, I. F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. H. (2010). Extending the tam model to explore the factors that affect intention to use an online learning community. Computers & Education, 54(2), 600–610. https://doi.org/10.1016/j.compedu.2009.09.009.

Loria, S., Keen, P., Honnibal, M., Yankovsky, R., Karesh, D., Dempsey, E., et al. (2014). Textblob: Simplified text processing. In Secondary TextBlob: simplified text processing, 3. https://textblob.readthedocs.io/en/dev/.

Makkonen, P., Lampropoulos, G., & Siakas, K. (2019). Security and privacy issues and concerns about the use of social networking services. In E-Learn: World conference on e-learning in corporate, government, healthcare, and higher education, association for the advancement of computing in education (AACE) (pp. 457–466). https://www.learntechlib.org/primary/p/211113/.

Manguri, K. H., Ramadhan, R. N., & Amin, P. R. M. (2020). Twitter sentiment analysis on worldwide COVID-19 outbreaks. Kurdistan Journal of Applied Research. https://doi.org/10.24017/covid.8.

Mathur, A., Kubde, P., & Vaidya, S. (2020). Emotional analysis using twitter data during pandemic situation: COVID-19. In 5th International conference on communication and electronics systems (ICCES) (pp. 845–848). IEEE. https://doi.org/10.1109/ICCES48766.2020.9138079.

McKenzie, S., Rough, J., Spence, A., & Patterson, N. (2019). Virtually there: the potential, process and problems of using 360 video in the classroom. Issues in Informing Science and Information Technology, 16, 211–219. https://doi.org/10.28945/4318.

Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). Effectiveness of virtual reality-based instruction on students’ learning outcomes in k-12 and higher education: A meta-analysis. Computers & Education, 70, 29–40. https://doi.org/10.1016/j.compedu.2013.07.033.

Mikropoulos, T. A., & Natsis, A. (2011). Educational virtual environments: A ten-year review of empirical research (1999–2009). Computers & Education, 56(3), 769–780. https://doi.org/10.1016/j.compedu.2010.10.020

Mohammad, S. M. (2020). NRC word-emotion association lexicon. http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm. Accessed 07 Jan 2021.

Mohammad, S., & Turney, P. (2010). Emotions evoked by common words and phrases: Using mechanical turk to create an emotion lexicon. In Proceedings of the NAACL HLT 2010 workshop on computational approaches to analysis and generation of emotion in text (pp. 26–34). https://www.aclweb.org/anthology/W10-0204/.

Mohammad, S. M., & Turney, P. D. (2013). Crowdsourcing a word-emotion association lexicon. Computational Intelligence, 29(3), 436–465. https://doi.org/10.1111/j.1467-8640.2012.00460.x.

Olmos, E., Cavalcanti, J. F., Soler, J. L., Contero, M., & Alcañiz, M. (2018). Mobile virtual reality: A promising technology to change the way we learn and teach. In Mobile and ubiquitous learning (pp. 95–106). Springer. https://doi.org/10.1007/978-981-10-6144-8_6.

Özgüven, N., & Mucan, B. (2013). The relationship between personality traits and social media use. Social Behavior and Personality: An International Journal, 41(3), 517–528. https://doi.org/10.2224/sbp.2013.41.3.517.

Pallis, G., Zeinalipour-Yazti, D., & Dikaiakos, M. D. (2011). Online social networks: Status and trends. New Directions in Web Data Management, 1, 213–234. https://doi.org/10.1007/978-3-642-17551-0_8.

Park, C. W., & Seo, D. R. (2018). Sentiment analysis of twitter corpus related to artificial intelligence assistants. In 5th International conference on industrial engineering and applications (ICIEA) (pp. 495–498). IEEE. https://doi.org/10.1109/IEA.2018.8387151.

Phuvipadawat, S., & Murata, T. (2010). Breaking news detection and tracking in twitter. In IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology (Vol. 3, pp. 120–123). IEEE. https://doi.org/10.1109/WI-IAT.2010.205.

Plutchik, R. (1984). Emotions: A general psychoevolutionary theory. In Approaches to emotion (pp. 197–219).

Plutchik, R., & Kellerman, H. (1980). Emotion, Theory, Research, and Experience. Academic Press. https://doi.org/10.1016/B978-0-12-558701-3.50007-7.

Preece, J., Sharp, H., & Rogers, Y. (2015). Interaction design: Beyond human–computer interaction. Wiley.

Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816.

Ramteke, J., Shah, S., Godhia, D., & Shaikh, A. (2016). Election result prediction using twitter sentiment analysis. In International conference on inventive computation technologies (ICICT) (Vol. 1, pp. 1–5). IEEE. https://doi.org/10.1109/INVENTIVE.2016.7823280.

Ranieri, M., Bruni, I., & Luzzi, D. (2020). Introducing 360-degree video in higher education: An overview of the literature. Human and Artificial Intelligence for the Society of the Future. https://doi.org/10.38069/edenconf-2020-ac0032.

Riva, G., Mantovani, F., Capideville, C. S., Preziosa, A., Morganti, F., Villani, D., et al. (2007). Affective interactions using virtual reality: The link between presence and emotions. CyberPsychology & Behavior, 10(1), 45–56. https://doi.org/10.1089/cpb.2006.9993.

Roche, L., & Gal-Petitfaux, N. (2017). Using 360 video in physical education teacher education. In Society for information technology & teacher education international conference, Association for the Advancement of Computing in Education (AACE) (pp. 3420–3425). https://www.learntechlib.org/primary/p/178219/.

Roorda, D. L., Koomen, H. M., Spilt, J. L., & Oort, F. J. (2011). The influence of affective teacher-student relationships on students’ school engagement and achievement: A meta-analytic approach. Review of Educational Research, 81(4), 493–529. https://doi.org/10.3102/0034654311421793.

Rupp, M. A., Kozachuk, J., Michaelis, J. R., Odette, K. L., Smither, J. A., & McConnell, D. S. (2016). The effects of immersiveness and future VR expectations on subjective-experiences during an educational 360 video. In Proceedings of the human factors and ergonomics society annual meeting (Vol. 60, pp. 2108–2112). SAGE Publications. https://doi.org/10.1177/1541931213601477.

Saha, S., Yadav, J., & Ranjan, P. (2017). Proposed approach for sarcasm detection in twitter. Indian Journal of Science and Technology, 10(25), 1–8. https://doi.org/10.17485/ijst/2017/v10i25/114443

Sherman, W. R., & Craig, A. B. (2018). Chapter 10: Virtual reality: Past, present, future. In W. R. Sherman & A. B. Craig (Eds.), Understanding virtual reality. The Morgan Kaufmann series in computer graphics (2nd ed., pp. 780–821). Morgan Kaufmann. https://doi.org/10.1016/B978-0-12-800965-9.00010-6.

Shernoff, D. J., Csikszentmihalyi, M., Schneider, B., & Shernoff, E. S. (2014). Student engagement in high school classrooms from the perspective of flow theory. In Applications of flow in human development and education (pp. 475–494). Springer. https://doi.org/10.1007/978-94-017-9094-9_24.

Slater, M. (2003). A note on presence terminology. Presence Connect, 3(3), 1–5.

Slater, M. (2018). Immersion and the illusion of presence in virtual reality. British Journal of Psychology, 109(3), 431–433.

Slater, M., Usoh, M., & Steed, A. (1994). Depth of presence in virtual environments. Presence: Teleoperators & Virtual Environments, 3(2), 130–144. https://doi.org/10.1162/pres.1994.3.2.130

Snelson, C., & Hsu, Y. C. (2020). Educational 360-degree videos in virtual reality: A scoping review of the emerging research. TechTrends, 64, 404–412. https://doi.org/10.1007/s11528-019-00474-3

Suchman, L. A. (1987). Plans and situated actions: The problem of human-machine communication. Cambridge University Press.

Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations. Doubleday & Co.

Theureau, J. (2003). Course-of-action analysis and course-of-action centered design. In Handbook of cognitive task design (pp. 55–81). CRC Press. https://doi.org/10.1201/9781410607775.

Ulrich, F., Helms, N. H., Frandsen, U. P., & Rafn, A. V. (2021). Learning effectiveness of 360 video: Experiences from a controlled experiment in healthcare education. Interactive Learning Environments, 29(1), 98–111. https://doi.org/10.1080/10494820.2019.1579234.

van den Broek-Altenburg, E. M., & Atherly, A. J. (2019). Using social media to identify consumers’ sentiments towards attributes of health insurance during enrollment season. Applied Sciences, 9(10), 2035. https://doi.org/10.3390/app9102035.

Violante, M. G., Vezzetti, E., & Piazzolla, P. (2019). Interactive virtual technologies in engineering education: Why not 360° videos? International Journal on Interactive Design and Manufacturing (IJIDeM), 13(2), 729–742. https://doi.org/10.1007/s12008-019-00553-y

Wang, M. T., & Fredricks, J. A. (2014). The reciprocal links between school engagement, youth problem behaviors, and school dropout during adolescence. Child Development, 85(2), 722–737. https://doi.org/10.1111/cdev.12138.

Wang, M. T., & Holcombe, R. (2010). Adolescents’ perceptions of school environment, engagement, and academic achievement in middle school. American Educational Research Journal, 47(3), 633–662. https://doi.org/10.3102/0002831209361209.

Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2013). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107. https://doi.org/10.1109/TKDE.2013.109

Zhang, D., Zhou, L., Briggs, R. O., & Nunamaker, J. F., Jr. (2006). Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness. Information & Management, 43(1), 15–27. https://doi.org/10.1016/j.im.2005.01.004.

Zolkepli, I. A., & Kamarulzaman, Y. (2015). Social media adoption: The role of media needs and innovation characteristics. Computers in Human Behavior, 43, 189–209. https://doi.org/10.1016/j.chb.2014.10.050.