Abstract
The pandemic has caused a drastic shift to online teaching and learning. However, online teaching and learning still face similar problems to traditional teaching and learning, and one example is the “one-size-fits-all” approach. The ineffectiveness of such an approach is particularly pronounced in interdisciplinary teaching and learning. For example, non-engineering students entering engineering-related courses (e.g., engineering project management and facilities management) have diverse math, physics, and chemistry knowledge backgrounds. Correspondingly, students face different challenges in obtaining the necessary background knowledge for engineering-related courses. One solution to overcome the challenges is adaptive learning, an intelligent approach to providing personalised educational paths for each learner to learn more effectively and efficiently. This study proposes a preliminary framework for implementing adaptive learning for teaching structural systems, a subject in structural engineering, to students with diverse backgrounds. The framework consists of five modules: adaptation, content, learners, instructors, and feedback. The paper discusses a case study of a Structural Systems course for non-engineering students, which utilised the framework to implement adaptive learning in 2021. Preliminary findings show that students are generally satisfied with the adaptive learning approach. Furthermore, the preliminary framework can be adapted and applied to other interdisciplinary teaching and learning settings.
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This study is funded by the Singapore Ministry of Education Tertiary Education Research Fund MOE2019-TRF-001.
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Hu, X., Goh, Y.M., Lin, A., Liu, Q. (2023). Preliminary Implementation of Adaptive Learning for Teaching Structural Systems to Non-engineering Students. In: Geng, G., Qian, X., Poh, L.H., Pang, S.D. (eds) Proceedings of The 17th East Asian-Pacific Conference on Structural Engineering and Construction, 2022. Lecture Notes in Civil Engineering, vol 302. Springer, Singapore. https://doi.org/10.1007/978-981-19-7331-4_31
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