Skip to main content
SpringerLink
Log in

Learning Model of Recorded Lectures: Implications to Learning Analytics Theory and Practice

  • Living reference work entry
  • First Online:
Learning, Design, and Technology

Abstract

This chapter presents results of a study aimed at understanding student engagement with recorded lectures and their perceptions on the value of these materials to their learning. It also examined whether presenting students with recorded materials prior to scheduled lectures can influence class attendance. Results suggest students significantly value recorded lecture materials. It revealed that provision of recorded lectures helps students to prepare for scheduled lectures. Further analysis showed that students are more likely to use recorded materials when revising the course or studying for final exams. Participants also reported that viewing recorded lectures is unlikely to influence their willingness to attend scheduled lectures. This research contributes to the significant contribution of recorded lecture materials to student learning. It supports the growing evidence that provision of recorded lectures to students prior to scheduled classes does not automatically lead to lecture absenteeism.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  • Al Nashash, H., & Gunn, C. (2013). Lecture capture in engineering classes: Bridging gaps and enhancing learning. Journal of Educational Technology & Society, 16(1), 69–78.

    Google Scholar 

  • Allen, D., & Tanner, K. (2005). Infusing active learning into the large-enrollment biology class: Seven strategies, from the simple to complex. Cell Biology Education, 4, 262–268.

    Article  Google Scholar 

  • Baker, J. W. (2000). The “classroom flip”: Using web course management tools to become the guide by the side. In Paper presented at the 11th International Conference on College Teaching and Learning. Jacksonville, FL.

    Google Scholar 

  • Billings-Gagliardi, S., & Mazor, K. M. (2007). Student decisions about lecture attendance: Do electronic course materials matter? Academic Medicine, 82(10), S73–S76. doi:10.1097/ACM.1090b1013e31813e31651e.

    Article  Google Scholar 

  • Brooks, C., Epp, C. D., Logan, G., & Greer, J. (2011). The who, what, when, and why of lecture capture. In Proceedings of the 1st international conference on learning analytics and knowledge (pp. 86–92). ACM.

    Google Scholar 

  • Chaplin, S. (2009). Assessment of the impact of case studies on student learning gains in an introductory biology course. Journal of College Science Teaching, 39, 72–79.

    Google Scholar 

  • Craig, P., et al. (2009). Student use of web based lecture technologies in blended learning: Do these reflect study patterns? In Same places different spaces. Proceedings ascilite Auckland 2009 (pp. 158–167). http://www.ascilite.org.au/conferences/auckland09/procs/craig.pdf. Accessed 25 May 2016.

  • Clay, T., & Breslow, L. (2006). Why students don’t attend class. MIT Faculty Newsletter, 18(March/April), 6–7.

    Google Scholar 

  • Devadoss, S., & Foltz, S. (1996). Evaluation of factors influencing student class attendance and performance. American Journal of Agricultural Economics, 78, 499–507.

    Article  Google Scholar 

  • Dey, E. L., Burn, H. E., & Gerdes, D. (2009). Bringing the classroom to the web: Effects of using new technologies to capture and deliver lectures. Research in Higher Education, 50(4), 377–393.

    Article  Google Scholar 

  • Freeman, S., O’Connor, E., Parks, J. W., Cunningham, M., Hurley, D., Haak, D., … Wenderoth, M. P. (2007). Prescribed active learning increases performance in introductory biology. CBE Life Sciences Education, 6, 132–139.

    Google Scholar 

  • Gorissen, P., Van Bruggen, J., & Jochems, W. (2012). Students and recorded lectures: survey on current use and demands for higher education. Research in Learning Technology, 20, 297.

    Article  Google Scholar 

  • Gosper, M., McNeill, M., Woo, K., Phillips, R., Preston, G., & David Green. 2007. “Web-based lecture-recording technologies: Do students learn from them?” In Paper presented at Educause Australasia. Melbourne, Australia, May 29–2. Available at http://www.mq.edu.au/ltc/altc/wblt/docs/dissemination/Educause_Gosper.pdf. Accessed November 20, 2014.

  • Green, C. K. (2015). Beginning the fourth decade of the “IT Revolution” in higher education: Plus ça change. In 40 EduCause Review September/October 2015 Retrieved on November 3 2015 from http://er.educause.edu/%7E/media/files/articles/2015/8/erm1553.pdf

  • Green, K. R., Pinder-Grover, T., & Millunchick, J. M. (2012). Impact of screencast technology: Connecting the perception of usefulness and the reality of performance. Journal of Engineering Education, 101(4), 717–737.

    Article  Google Scholar 

  • Holbrook, J., & Dupont, C. (2009). Profcasts and class attendance – Does year in program matter? Bioscience Education, 13(June). Available at: www.bioscience.heacademy.ac.uk/journal/vol13/beej-13-c2.pdf. Accessed November 21, 2015.

  • Karnad, A. (2013). Student use of recorded lectures: a report reviewing recent research into the use of lecture capture technology in higher education, and its impact on teaching. eprints.lse.ac.uk.

    Google Scholar 

  • Marchand, J.-P., Pearson, M., & Albon, S. (2014). Student and faculty member perspectives on lecture capture in pharmacy education. American Journal of Pharmaceutical Education, 78(14), 74.

    Article  Google Scholar 

  • Mattick, K., Crocker, G., & Bligh, J. (2007). Medical student attendance at non-compulsory lectures. Advances in Health Science Educational Theory and Practice, 12, 201–210.

    Article  Google Scholar 

  • Moravec, M., Williams, A., Aguilar-Roca, N., & O’Dowd, D. K. (2010). Learn before lecture: A strategy that improves learning outcomes in a large introductory biology class. CBE-Life Sciences Education, 9(4), 473–481.

    Article  Google Scholar 

  • Romer, D. (1993). Do students go to class? Should they? Journal of Economic Perspectives, 7(summer), 167–174.

    Article  Google Scholar 

  • Soong, S. K. A., Chan, L. K., Cheers, C., & Hu, C. (2006). Impact of video recorded lectures among students. Sydney: Australasian Society for Computers in Learning in Tertiary Education (ASCILITE). http://www.ascilite.org.au/conferences/sydney06/proceedings/pdf_papers/p179.pdf

  • St Clair, K. L. (1999). A case against compulsory class attendance policies in higher education. Innovative Higher Education, 23, 171–180.

    Article  Google Scholar 

  • Phillips, R., et al. (2011). Learning analytics and study behaviour : A pilot study. In G. Williams, P. Statham, N. Brown, & B. Cleland (Eds.), Changing demands, changing directions. Proceedings ascilite Hobart 2011 (pp. 997–1007). http://www.ascilite.org.au/conferences/hobart11/procs/Phillips-concise.pdf

  • Thatcher, A., Fridjhon, P., & Cockcroft, K. (2007). The relationship between lecture attendance and academic performance in an undergraduate psychology class. South African Journal of Psychology, 37(3), 656–660.

    Article  Google Scholar 

  • Traphagan, T., Kucsera, J., & Kishi, K. (2010). Impact of class lecture webcasting on attendance and learning. Educational Technology Research and Development, 58, 19–37.

    Article  Google Scholar 

  • von Konsky, B. R., Ivins, J., & Gribble, S. J. (2009). Lecture attendance and web-based lecture technologies: A comparison of student perceptions and usage patterns. Australasian Journal of Educational Technology, 25(4), 581–595.

    Google Scholar 

  • Walls, S. M., Kucsera, J. V., Walker, J. D., Acee, T. W., McVaugh, N. K., & Robinson, D. H. (2010). Podcasting in education: Are students as ready and eager as we think they are? Computers & Education, 54(2), 371–378.

    Article  Google Scholar 

  • Walvoord, B. E., & Johnson, V. J. (1998). Effective grading: A tool for learning and assessment. San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Wieling, M., & Hofman, W. (2010). The impact of online video lecture recordings and automated feedback on student performance. Computers & Education, 54(4), 992–998. Retrieved on November 21, 2015 from http://dx.doi.org/10.1016/j.compedu.2009.10.002.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Educational Technology Research Group, Higher Education Development Centre, University of Otago, 65/75 Union Place West, Dunedin, 9016, New Zealand

    Ben Kei Daniel

Authors
  1. Ben Kei Daniel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ben Kei Daniel .

Editor information

Editors and Affiliations

  1. College of Info, Ste G150, Univ of North Texas, Denton, Texas, USA

    Michael J Spector

  2. School of Education, Virginia Tech, Blacksburg, Virginia, USA

    Barbara B Lockee

  3. School of Education, Baker University, Overland Park, Kansas, USA

    Marcus D. Childress

Appendix 1. Questionnaire

Appendix 1. Questionnaire

Student Learning Experiences and Engagement with the Use of Recorded Lectures

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this entry

Cite this entry

Daniel, B.K. (2016). Learning Model of Recorded Lectures: Implications to Learning Analytics Theory and Practice. In: Spector, M., Lockee, B., Childress, M. (eds) Learning, Design, and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-17727-4_2-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-17727-4_2-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Online ISBN: 978-3-319-17727-4

  • eBook Packages: Springer Reference EducationReference Module Humanities and Social SciencesReference Module Education

Publish with us

Policies and ethics

Search

Navigation