Understanding Feedback to Improve Online Course Design

Abstract

Online learning is on the rise as universities look to reduce cost and scale their offerings (Stacey, 2013). Another trend is that some instructors have shifted to a “blended approach” which mixes brick and mortar university teaching with supplemental online lectures (Horn, 2013). While e-learning can follow a more structured approach where students embark on a fully-curated e-learning journey, online video portals can simply offer a la carte lectures that supplement in class learning. Khan Academy is an example of an online portal that has made learning accessible to anyone on a per-lecture basis (Khan, 2012). Online learning allows students on-demand access to information, but direct and real-time feedback was previously a barrier to gage student engagement and understanding (Pappas, 2016). Instructors now have access to web analytics which offer an in-depth look into students’ viewing habits. Online viewing data has the potential to be implemented and interpreted as feedback in teaching and course offering, as in a design cycle, this feedback can be used as an input in the next iteration of the online course design. For this paper, we will complete a literature review of the techniques researchers have used to analyze online and e-learning watch data and propose a novel framework for online course design using this feedback data that addresses a number of the CDIO Standards (“THE CDIO STANDARDS v 2.0,” 2010), including: (2) How online assessment and feedback can be used to evaluate learning progression; (3) Suggest pathways for integration of multiple online courses; (7) Integrate personal and interpersonal skills, products, processes and system building into the assessment framework; (8) Examine how experiential learning has previously been integrated with online learning, and examine potential ways to expand on this; (10) Demonstrate how enhanced feedback pathways will enhance faculty competence and student learning experience; (12) Findings can be taken into account for further iterations of courses, which results in stronger programs.

Bibliography Horn, M. (2013). The transformational potential of flipped classrooms. Education Next. Retrieved from http://search.proquest.com/openview/14d9ce81070d171cfdc4a27d67fb0a70/1?pq-origs ite=gscholar&cbl=1766362 Khan, S. (2012). The one world schoolhouse: Education reimagined. Retrieved from https://books.google.ca/books?hl=en&lr=&id=xz-gkDYm4UUC&oi=fnd&pg=PT151&dq=One+ world+schoolhouse+khan&ots=Q76yOHkfhQ&sig=H-PWt-51T2KPIo-GsBVHpuc7TBo Pappas, C. (2016, November 6). Top 8 eLearning Barriers That Inhibit Online Learners Engagement With eLearning Content - eLearning Industry. Retrieved January 1, 2016, from https://elearningindustry.com/top-elearning-barriers-that-inhibit-online-learne rs-engagement-elearning-content Stacey, P. (2013). The Pedagogy of MOOCs. Retrieved November 7, 2016, from https://edtechfrontier.com/2013/05/11/the-pedagogy-of-moocs/ THE CDIO STANDARDS v 2.0. (2010).

Proceedings of the 13th International CDIO Conference in Calgary, Canada, June 18-22 2017

Authors
Alexandra Meikleham and Ron Hugo
Document
119_Final_PDF.pdf (2.55 MB)
Document type
I Agree
On
Pages
11
Reference Text
Proceedings of the 13th International CDIO Conference in Calgary, Canada, June 18-22 2017
Year
2017