Development of an E-LKM Supported by Liveworksheets Using a Deep Learning Approach: A Literature Review
DOI:
https://doi.org/10.33477/al-alam.v5i1.15611Keywords:
deep learning, e-LKM, liveworksheetsAbstract
Biology teaching requires teaching resources that can help pupils gain a deeper understanding of abstract and complex concepts. One possible solution is to develop e-LKM supported by Liveworksheets using a deep learning approach. This article aims to review findings from previous studies egarding e-LKM development, the implementation of Liveworksheets, and the application of the deep learning approach in learning. The study employed a literature review method, examining relevant journal articles published between 2022 and 2026. The findings show that the application of a deep learning approach in the development supports active, meaningful and student-centred learning while contributing to better conceptual understanding and critical thinking skills. Furthermore, Livewroksheets facilitates the creation of interactive, practical and easily accessible e-LKM through multimedia features and digital assessment tools, thereby enhancing student engagement in learning. In Biology lessons, combining Liveworksheets with the deep learning approach can help present abstract and complex concepts in a more concrete manner. Consequently, e-LKM developed with the support of Liveworksheets and a deep learning approach can serve as an innovative alternative for promoting Biology learning that is more effective, interactive and meaningful.
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Copyright (c) 2026 Salsa Nabilla, Rahmawati Darussyamsu

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