Diversity of Online Behaviours Associated with Physical Attendance in Lectures
DOI:
https://doi.org/10.18608/jla.2019.61.3Keywords:
Attendance, online engagement, online behaviour metrics, learning analyticsAbstract
A common use of technology in higher education is the provision of online course materials, invoking an investigation of the ways in which students engage with online course content, and how their participation changes over time. This is particularly necessary in the context of high absenteeism from lectures, where online access may be the only way in which particular students are engaging with the course. In this study, we examine large-scale patterns of attendance in class, as well as four types of access to online materials. We define two online behavioural metrics — richness and evenness — to capture the distribution of online behaviours within 255 courses, and examine how these change over time. We find that both physical and online attendance decrease throughout the semester, but the fraction of students present online is considerably higher than the fraction present in lectures. Students adapt their online behaviour, and rare behaviours disappear over time. It is important to consider how we provide content, both face-to-face and online, in order to ensure that as many students as possible are accessing this content in ways that we intend.
References
Amershi, S., & Conati, C. (2010). Automatic recognition of learner types in exploratory learning environments. In C. Romero, S. Ventura, M. Pechenizkiy, & R. S. J. d. Baker (Eds.), Handbook of Educational Data Mining (pp. 213–230). Boca Raton, FL: CRC Press. http://doi.org/10.1201/b10274-24
Anderson, A., Huttenlocher, D., Kleinberg, J., & Leskovec, J. (2014). Engaging with massive online courses. Proceedings of the 23rd International Conference on World Wide Web (WWW ’14), 7–11 April 2014, Seoul, Republic of Korea (pp. 687–698). New York: ACM. http://doi.org/10.1145/2566486.2568042
Azab, E., Saksena, Y., Alghanem, T., Midle, J. B., Molgaard, K., Albright, S., & Karimbux, N. (2016). Relationship among dental students’ class lecture attendance, use of online resources, and performance. Journal of Dental Education, 80(4), 452–458.
Babb, K. A., & Ross, C. (2009). The timing of online lecture slide availability and its effect on attendance, participation, and exam performance. Computers & Education, 52(4), 868–881. http://doi.org/10.1016/j.compedu.2008.12.009
Bakia, M., Means, B., & Murphy, R. (2014). Learning online: What research tells us about whether, when and how. London: Routledge.
Barker, L., Hovey, C. L., Subhlok, J., & Tuna, T. (2014). Student perceptions of indexed, searchable videos of faculty lectures. Proceedings of the 2014 IEEE Frontiers in Education Conference (FIE 2014), 22–25 October 2014, Madrid, Spain (pp. 1–8). IEEE Computer Society. http://doi.org/10.1109/FIE.2014.7044189
Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. Journal of Computing in Higher Education, 26(1), 87–122. http://doi.org/10.1007/s12528-013-9077-3
Brennan, A., Peace, C., & Munguia, P. (2018). Classroom size, activity and attendance: Scaling up drivers of learning space occupation. Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK ’18), 5–9 March 2018, Sydney, NSW, Australia (pp. 255–259). New York: ACM. http://doi.org/10.1145/3170358.3170401
Cohn, E., & Johnson, E. (2006). Class attendance and performance in principles of economics. Education Economics, 14(2), 211–233. http://doi.org/10.1080/09645290600622954
Dixson, M. D. (2012). Creating effective student engagement in online courses: What do students find engaging? Journal of the Scholarship of Teaching and Learning, 10(2), 1–13.
Dolnicar, S., Kaiser, S., Matus, K., & Vialle, W. (2009). Can Australian universities take measures to increase the lecture attendance of marketing students? Journal of Marketing Education, 31(3), 203–211. http://doi.org/10.1177/0273475309345202
Dutt, A., Aghabozrgi, S., Ismail, M. A. B., & Mahroeian, H. (2015). Clustering algorithms applied in educational data mining. International Journal of Information and Electronics Engineering, 5(2), 112. http://doi.org/10.7763/IJIEE.2015.V5.513
Ferguson, R., Clow, D., Beale, R., Cooper, A. J., Morris, N., Bayne, S., & Woodgate, A. (2015). Moving through MOOCs: Pedagogy, learning design and patterns of engagement. In G. Conole, T. Klobučar, C. Rensing, J. Konert, E. Lavoué (Eds.), Design for Teaching and Learning in a Networked World. Lecture Notes in Computer Science, vol. 9307 (pp. 70–84). Springer, Cham. http://doi.org/10.1007/978-3-319-24258-3_6
Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. http://doi.org/10.1073/pnas.1319030111
Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice. Abingdon, UK: Taylor & Francis.
George-Walker, L. D., & Keeffe, M. (2010). Self‐determined blended learning: A case study of blended learning design. Higher Education Research & Development, 29(1), 1–13. http://doi.org/10.1080/07294360903277380
Grabe, M. (2005). Voluntary use of online lecture notes: Correlates of note use and note use as an alternative to class attendance. Computers & Education, 44(4), 409–421. http://doi.org/10.1016/j.compedu.2004.04.005
Grabe, M., & Christopherson, K. (2005). Evaluating the advantages and disadvantages of providing lecture notes: The role of internet technology as a delivery system and research tool. The Internet and Higher Education, 8(4), 291–298. http://doi.org/10.1016/j.iheduc.2005.09.002
Grabe, M., Christopherson, K., & Douglas, J. (2005). Providing introductory psychology students access to online lecture notes: The relationship of note use to performance and class attendance. Journal of Educational Technology Systems, 33(3), 295–308. http://doi.org/10.2190/G5RF-DMWG-WV1G-TMGG
Gump, S. E. (2006). Guess who’s (not) coming to class: Student attitudes as indicators of attendance. Educational Studies, 32(1), 39–46. http://doi.org/10.1080/03055690500415936
Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos. Proceedings of the 1st ACM Conference on Learning @ Scale (L@S 2014), 4–5 March 2014, Atlanta, Georgia, USA (pp. 41–50). New York: ACM. http://doi.org/10.1145/2556325.2566239
Hughes-Warrington, M. (2015, July 6). That sinking feeling: Counting the cost of live lectures. Tumblr post. https://missunitwocents.tumblr.com/post/123364615920/that-sinking-feeling-counting-the-cost-of-live
Kelly, G. E. (2012). Lecture attendance rates at university and related factors. Journal of Further and Higher Education, 36(1), 17–40. http://doi.org/10.1080/0309877X.2011.596196
Kinash, S., Knight, D., & McLean, M. (2015). Does digital scholarship through online lectures affect student learning? Journal of Educational Technology & Society, 18(2), 129–139.
Kizilcec, R. F., Piech, C., & Schneider, E. (2013). Deconstructing disengagement: Analyzing learner subpopulations in massive open online courses. Proceedings of the 3rd International Conference on Learning Analytics and Knowledge (LAK ’13), 8–12 April 2013, Leuven, Belgium (pp. 170–179). New York: ACM. http://doi.org/10.1145/2460296.2460330
Khong, R. W., Dunn, J. S., Lim, C. M., & Yap, W. S. (2016). Why do students attend lectures? Exploring justifications for attendance among undergraduate students from a British university in Asia. The Journal of Developing Areas, 50(5), 497–506. http://doi.org/10.1353/jda.2016.0059
Kloft, M., Stiehler, F., Zheng, Z., & Pinkwart, N. (2014). Predicting MOOC dropout over weeks using machine learning methods. Proceedings of the Workshop on Modeling Large Scale Social Interaction in MOOCs at the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), 25 October 2014, Doha, Qatar (pp. 60–65). Association for Computational Linguistics.
Magurran, A. E. (1988). Why diversity? Ecological diversity and its measurement (pp. 1–5). Springer, Dordrecht. http://doi.org/10.1007/978-94-015-7358-0_1
McGee, P., & Reis, A. (2012). Blended course design: A synthesis of best practices. Journal of Asynchronous Learning Networks, 16(4), 7–22.
Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010, September). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. U.S. Department of Education, Office of Planning, Evaluation, and Policy Development. https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf
Mukala, P., Buijs, J. C. A. M., & Van Der Aalst, W. M. P. (2015). Exploring students’ learning behaviour in MOOCs using process mining techniques. BPM reports, Vol. 1510. Department of Mathematics and Computer Science, University of Technology, Eindhoven, The Netherlands. https://research.tue.nl/en/publications/exploring-students-learning-behaviour-in-moocs-using-process-mini
Nagel, L., & Kotzé, T. G. (2010). Supersizing e-learning: What a CoI survey reveals about teaching presence in a large online class. The Internet and Higher Education, 13(1–2), 45–51. http://doi.org/10.1016/j.iheduc.2009.12.001
O’Donovan, S., Gain, J., & Marais, P. (2013). A case study in the gamification of a university-level games development course. Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference (SAICSIT ’13), 7–9 October 2013, East London, South Africa (pp. 242–251) New York: ACM. http://doi.org/10.1145/2513456.2513469
Peckham, T., & McCalla, G. (2012). Mining student behavior patterns in reading comprehension tasks. In K. Yacef, O. Zaiane, A. Hershkovitz, M. Yudelson, & J. Stamper (Eds.), Proceedings of the 5th International Conference on Educational Data Mining (EDM2012), 19–21 June 2012, Chania, Greece (pp. 87–94). International Educational Data Mining Society. http://educationaldatamining.org/EDM2012/uploads/procs/EDM_2012_proceedings.pdf
Ramsden, P. (2003). Learning to teach in higher education. London: Routledge.
Revere, L., & Kovach, J. V. (2011). Online technologies for engaged learning: A meaningful synthesis for educators. Quarterly Review of Distance Education, 12(2), 113–124. http://doi.org/10.1080/15236803.2018.1429817
Rienties, B., Lewis, T., McFarlane, R., Nguyen, Q., & Toetenel, L. (2018). Analytics in online and offline language learning environments: The role of learning design to understand student online engagement. Computer Assisted Language Learning, 31(3), 273–293. http://doi.org/10.1080/09588221.2017.1401548
Salmon, G. (2004). E-moderating: The key to teaching and learning online. London: Psychology Press.
Seary, K., James, T., & Conradie, H. (2014). Designing practical strategies to increase STEPS students’ attendance at face-to-face, on campus classes: Preliminary findings. Paper presented to the FABENZ: Challenges and Innovation Conference, 4–5 December 2014, Tauranga, New Zealand. https://www.academia.edu/19639837/Designing_practical_strategies_to_increase_STEPS_students_attendance_at_face-to-face_on_campus_classes_Preliminary_findings
Stewart, M., Stott, T., & Nuttall, A. M. (2011). Student engagement patterns over the duration of level 1 and level 3 geography modules: Influences on student attendance, performance and use of online resources. Journal of Geography in Higher Education, 35(1), 47–65. http://doi.org/10.1080/03098265.2010.498880
Traphagan, T., Kucsera, J. V., & Kishi, K. (2010). Impact of class lecture webcasting on attendance and learning. Educational Technology Research and Development, 58(1), 19–37. http://doi.org/10.1007/s11423-009-9128-7
Tseng, S. F., Tsao, Y. W., Yu, L. C., Chan, C. L., & Lai, K. R. (2016). Who will pass? Analyzing learner behaviors in MOOCs. Research and Practice in Technology Enhanced Learning, 11(8). http://doi.org/10.1186/s41039-016-0033-5
Vai, M., & Sosulski, K. (2015). Essentials of online course design: A standards-based guide. London: Routledge.
Van Blerkom, M. L. (1992). Class attendance in undergraduate courses. The Journal of Psychology, 126(5), 487–494. http://doi.org/10.1080/00223980.1992.10543382
Weatherley, J. N., Grabe, M., & Arthur, E. I. (2003). Providing introductory psychology students access to lecture slides via Blackboard 5: A negative impact on performance. Journal of Educational Technology Systems, 31, 463–474. http://doi.org/10.2190/KRW7-QHFY-AY3M-FFJC
Wei, C. W., & Chen, N. S. (2012). A model for social presence in online classrooms. Educational Technology Research and Development, 60(3), 529–545. http://doi.org/10.1007/s11423-012-9234-9
Worthington, D. L., & Levasseur, D. G. (2015). To provide or not to provide course PowerPoint slides? The impact of instructor-provided slides upon student attendance and performance. Computers & Education, 85, 14–22. http://doi.org/10.1016/j.compedu.2015.02.002
Yuan, L., & Powell, S. (2013). MOOCs and disruptive innovation: Implications for higher education. eLearning Papers, In-depth, 33(2), 1–7.
Downloads
Published
How to Cite
Issue
Section
License
TEST
