Al Arefi, S.M.S. (2022) Blended Learning for Remote Software Simulation Laboratory of a Solar Power System. In: 2021 IEEE 8th International Conference on e-Learning in Industrial Electronics (ICELIE). 2021 IEEE 8th International Conference on e-Learning in Industrial Electronics (ICELIE), 13-16 Oct 2021, Toronto, ON, Canada. IEEE. ISBN: 978-1-6654-1421-0.
Abstract
Since 2020, hybrid learning has become the new convention of teaching and learning, whereby learning materials are delivered through a blend of synchronous and asynchronous sessions. In engineering education, this has led to the migration of laboratory teaching to the remote and virtual world. While immersive learning based virtual laboratory has been a great alternative for teaching hardware-based laboratory activities, this has however posed great challenge to software-based laboratory learning. Review of the literature on engineering education suggests an evident gap in pedogeological research to inform the application of blended laboratory learning. This paper thus presents a study case on the pedagogy of introducing blended learning adopted in the remote teaching of an electrical power engineering laboratory. The approaches integrated to facilitate the pedagogy and their implications are detailed in this work. Using Bloom's taxonomy, the paper examines the role of blended learning in enhancing student learning experience in respect to learning autonomy and engagement.
Metadata
| Item Type: | Proceedings Paper |
|---|---|
| Authors/Creators: |
|
| Keywords: | blended learning, electrical power engineering education, Bloom's taxonomy, software laboratory, student learning experience |
| Dates: |
|
| Institution: | The University of Leeds |
| Academic Units: | ?? Leeds.SR-ELTE ?? |
| Date Deposited: | 04 Nov 2026 13:34 |
| Last Modified: | 04 Nov 2026 13:34 |
| Published Version: | https://ieeexplore.ieee.org/document/9765548 |
| Status: | Published |
| Publisher: | IEEE |
| Identification Number: | 10.1109/icelie53900.2021.9765548 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:247290 |
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)