TPACK-Based Teaching Approaches in Mobile Learning for Biology Education: Insights from NGT & ISM Approaches

Cik Jamaliah Abd Manaf, Shakinaz Desa, Muhammad Ikhwan Mat Saad and Muhammad Nidzam Yaakob
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Cik Jamaliah Abd Manaf: Department of Biology, Faculty of Science & Mathematics, Universiti Pendidikan Sultan Idris, Malaysia
Shakinaz Desa: Department of Biology, Faculty of Science & Mathematics, Universiti Pendidikan Sultan Idris, Malaysia
Muhammad Ikhwan Mat Saad: Department of Biology, Faculty of Science & Mathematics, Universiti Pendidikan Sultan Idris, Malaysia
Muhammad Nidzam Yaakob: Institute of Teacher Education, Darulaman Campus, Malaysia

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 6, 1372-1384

Abstract: Integrating mobile learning in Biology education necessitates adopting practical teaching approaches that align with technological advancements. However, there remains a lack of structured guidelines for selecting and implementing appropriate teaching methods that maximize the potential of mobile learning in Biology education. Existing studies often focus on digital tools rather than pedagogical strategies that effectively integrate technology, pedagogy, and content knowledge (TPACK). This study addresses this gap by employing the Nominal Group Technique (NGT) and Interpretive Structural Modelling (ISM) to identify and prioritize teaching methods suitable for mobile learning environments. Findings indicate that field-based learning, problem-based learning, and simulation are the most highly ranked approaches, followed by mastery learning, animation, collaborative learning, virtual Reality, flipped classrooms, and inquiry-based learning. Self-directed learning, gamification, and adaptive learning are also recognized as effective strategies. Augmented Reality was not widely accepted, as it did not meet the minimum threshold of voter consensus required for inclusion. By applying the TPACK framework, this study explores how these approaches enhance student engagement, knowledge retention, and active learning in Biology education. The results provide a structured model to guide educators, policymakers, and researchers in optimizing mobile-based instructional strategies for Biology learning.

Date: 2025
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