Home > Research > Publications & Outputs > Estimating student workload during the learning...

Electronic data

  • Workload_tool_ECEL_v3

    Accepted author manuscript, 305 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

  • Estimating student workload

    Final published version, 1.92 MB, PDF document

Text available via DOI:

View graph of relations

Estimating student workload during the learning design of online courses: Creating a student workload calculator

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date7/11/2019
Host publicationProceedings of the 18th European Conference on e-Learning ECEL 2019
EditorsRikke Orngreen, Mie Buhl, Bente Meyer
Place of PublicationReading
PublisherAcademic Conferences and Publishing International Limited
Pages629-638
Number of pages10
ISBN (electronic)9781912764419
ISBN (print)9781912764426
<mark>Original language</mark>English

Abstract

UK university students are expected to undertake 10 hours of work for each Credit Accumulation and Transfer Scheme (CATS) credit. With face-to-face learning, this is relatively easy to quantify as x hours of contact time and the remainder made up of independent study. For online and distance learning, this is more complex. Study materials are provided for students to work through independently, but unlike face-to-face where the class ends after an hour or two, online students could continue working indefinitely. Some students will inevitably take longer than others to complete tasks, and it is therefore more difficult to ensure student workload in online courses is proportionate to the credits awarded. This paper provides a means to calculate student workload in online courses via a workload calculator, derived from a review of the literature and available at http://bit.ly/postgradworkload. It uses Laurillard’s (2009, 2013) conversational framework activity types to categorise online course materials into task types, and provides a means of estimating the time it would take an average student to complete each task, for use in informing the design of online courses. For those task types that cannot be accurately estimated it is recommended to provide guidance on how long a student should spend on the task within the learning materials.