Abstract
Online learning provides flexibility and accessibility, however, lack of interaction and support leads to decreased satisfaction and brings feelings of loneliness. Studies explored ways to promote social interaction and collaboration among learners, but there remain challenges in addressing the issues of relying on asynchronous communication in online learning. In this study, we explored which pattern of scrolling comments is beneficial and effective for online learning support. Based on the i-Comments model, we design an experiment, in which three groups of subjects are randomly assigned to view the video only, the video with i-Comments pattern I and video with i-Comments patternII. During the learning process, the subjects’ concentration is detected by an eye-tracking device, while their peaceful level is monitored through the emWave system. After viewing the videos, the subjects are requested to take a quiz to test their comprehension, and a questionnaire is used to investigate cognitive load, fatigue, loneliness, and satisfaction. The results showed that i-Comments with more relevant knowledge, larger quantity, and appearance when viewing the third and last video were found to significantly improve learning comprehension, enhance learning satisfaction, keep a peaceful state, and alleviate the sense of loneliness in online learning.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Institute of heartmath. https://www.heartmathbenelux.com/doc/HeartCloud
NHK high school lecture Japanese history website. https://www.nhk.or.jp/kokokoza/tv/nihonshi/index.html
Aranberri-Ruiz, A., Aritzeta, A., Olarza, A., Soroa, G., Mindeguia, R.: Reducing anxiety and social stress in primary education: a breath-focused heart rate variability biofeedback intervention. Int. J. Environ. Res. Public Health 19(16), 10181 (2022)
Baddeley, A.: Working memory. Science 255(5044), 556–559 (1992)
Chang, S.H.H., Smith, R.A.: Effectiveness of personal interaction in a learner-centered paradigm distance education class based on student satisfaction. J. Res. Technol. Educ. 40(4), 407–426 (2008)
Chen, Y., Gao, Q., Rau, P.-L.P.: Understanding gratifications of watching danmaku videos – videos with overlaid comments. In: Rau, P.L.P. (ed.) CCD 2015. LNCS, vol. 9180, pp. 153–163. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-20907-4_14
Godijn, R., Theeuwes, J.: The relationship between exogenous and endogenous saccades and attention. Mind’s Eye 3–26 (2003)
Haga, S., Mizukami, N.: Japanese version of NASA task load index sensitivity of its workload score to difficulty of three different laboratory tasks. Jpn. J. Ergon. 32(2), 71–79 (1996)
Hu, Q., Schaufeli, W.B.: The factorial validity of the maslach burnout inventory-student survey in china. Psychol. Rep. 105(2), 394–408 (2009)
Johnson, D.: Polyphonic/pseudo-synchronic: animated writing in the comment feed of nicovideo. Jpn. Stud. 33(3), 297–313 (2013)
Keržič, D., et al.: Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: evidence across ten countries. PLoS ONE 16(10), e0258807 (2021)
Kurucay, M., Inan, F.A.: Examining the effects of learner-learner interactions on satisfaction and learning in an online undergraduate course. Comput. Educ. 115, 20–37 (2017)
Masuda, Y., Tadaka, E., Dai, Y.: Reliability and validity of the Japanese version of the UCLA loneliness scale version 3 among the older population. J. Japan Acad. Commun. Health Nurs. 15(1), 25–32 (2012)
Razami, H.H., Ibrahim, R.: Distance education during COVID-19 pandemic: the perceptions and preference of university students in Malaysia towards online learning. Int. J. Adv. Comput. Sci. Appl. 12(4) (2021)
Sha’ari, N.S., Amin, M.: Resilience building among university students: a heart rate variability biofeedback study. In: IOP Conference Series: Materials Science and Engineering, vol. 1051, p. 012015. IOP Publishing (2021)
Teigen, K.H.: Yerkes-dodson: a law for all seasons. Theory Psychol. 4(4), 525–547 (1994)
Wang, J., Chen, J., Jin, Q.: i-comments: on-screen individualized comments for online learning support. In: 2022 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), pp. 1–5. IEEE (2022)
Wang, J.Z., Kowler, E.: Micropursuit and the control of attention and eye movements in dynamic environments. J. Vis. 21(8), 6–6 (2021)
Wang, J.: Research on the emergency education model of liberal arts in universities and its quality assurance. In: International Conference on Education Studies: Experience and Innovation (ICESEI 2020), pp. 462–467. Atlantis Press (2020)
Xavier, M., Meneses, J.: Persistence and time challenges in an open online university: a case study of the experiences of first-year learners. Int. J. Educ. Technol. High. Educ. 19(1), 1–17 (2022)
Zhang, Y., Qian, A., Pi, Z., Yang, J.: Danmaku related to video content facilitates learning. J. Educ. Technol. Syst. 47(3), 359–372 (2019)
Acknowledgements
This work was in part supported by JST SPRING (Grant No. JPMJSP2128).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, J., Chen, J., Jin, Q. (2023). Experimental Design and Validation of i-Comments for Online Learning Support. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14040. Springer, Cham. https://doi.org/10.1007/978-3-031-34411-4_15
Download citation
DOI: https://doi.org/10.1007/978-3-031-34411-4_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-34410-7
Online ISBN: 978-3-031-34411-4
eBook Packages: Computer ScienceComputer Science (R0)