Weekly short assessment and individual feedback: a strategy for deeper learning in blended learning environment
PDF

Keywords

deep learning
assessment
surface learning
feedback
constructive alignment

How to Cite

Weekly short assessment and individual feedback: a strategy for deeper learning in blended learning environment. (2024). UK and Ireland Engineering Education Research Network Conference Proceedings 2023. https://doi.org/10.31273/10.31273/9781911675167/1620

How to Cite

Weekly short assessment and individual feedback: a strategy for deeper learning in blended learning environment. (2024). UK and Ireland Engineering Education Research Network Conference Proceedings 2023. https://doi.org/10.31273/10.31273/9781911675167/1620

Abstract

Assessment and feedback methods have important role in motivating students to take deep or surface approaches in their learning. Designing assessments with clear link to the teaching content and intended learning outcomes (ILOs), supports students’ approach toward deep learning. This study explored impact of the weekly short assessments with individual feedback in blended classes, on motivating students to take a deep learning approach in their studies. Constructive alignment framework was used to prepare the teaching content, in-class learning activities and assessment tasks. Series of short formative questions prepared with each question evolving around one teaching topic and its ILOs. Students’ responses to each question were followed by individual feedback and an opportunity to reflect on the received feedback to improve their work. Students’ perception towards the short formative assessment with individual feedback was collected using the Revised Study Process Questionnaire (R-SPQ-2F). Using quantitative methodology responses of the 90 Year 2 chemical and environmental engineering students were analysed. Results showed that there are significantly higher deep approach scores (Mean=2.92, SD=1.14) compared to surface approach (Mean=2.41, SD=1.15), with p-value=0.001. Students’ motives and strategies in taking either deep or surface approach is also explored. While factors of “self-satisfaction” and “interest in the course content” were the main motives for students to take deep learning approach, surface strategies such as “learning the examinable content” were remaining high. This research aims to contribute to development of an assessment method in engineering education to foster students’ deep learning, by developing their critical thinking and problem-solving skills.

PDF
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Copyright (c) 2024 Maryam Mohammad Zadeh