Abstract
Since blended learning has become one of the promising approaches to teaching and learning, the integration of traditional learning with novel innovations should be taken into account. Novel innovations can raise the level of smart learning environments as well as the construction of wisdom classrooms. There are many ways to create these innovations. One of those is to apply the deep learning tool for teaching and learning activities, that can offer the learners to have profound and thorough knowledge experience. This work proposes a novel deep learning tool, which can support teaching and learning activities especially in a topic of scheduling. A computational intelligence algorithm called Teaching Learning-based Optimization (TLBO) was embedded within the tool for solving production scheduling problem. TLBO is a nature-inspired metaheuristic algorithm. It mimics the influential effect of teacher on learners or among learners. The tool was developed and tested upon four case studies.
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Acknowledgements
The first author would like to acknowledge Naresuan University Graduate School for providing his Ph.D. scholarship. This work was also part of research project supported by the Thailand Research Fund (TRF) and Office of the Higher Education Commission (OHEC) under grant number MRG6080066.
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Sooncharoen, S., Thepphakorn, T., Pongcharoen, P. (2020). A Deep Learning Tool Using Teaching Learning-Based Optimization for Supporting Smart Learning Environment. In: Cheung, S., Li, R., Phusavat, K., Paoprasert, N., Kwok, L. (eds) Blended Learning. Education in a Smart Learning Environment. ICBL 2020. Lecture Notes in Computer Science(), vol 12218. Springer, Cham. https://doi.org/10.1007/978-3-030-51968-1_32
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