Implementasi Deep Learning dan TPACK Berbasis Wordwall dalam Evaluasi Pembelajaran Biologi Implementation of Deep Learning and Wordwall-Based TPACK in Biology Learning Evaluation
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2978-2995
Digital Object Identifier:
10.58578/yasin.v6i3.10192
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Authors:Thoif Marsam1*, Hendro Prasetyono2
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Main Article Content
Abstract
The development of 21st-century education demands a paradigm shift in learning evaluation, particularly through the development of digital-based evaluation instruments that are able to promote students’ higher-order thinking skills. This study aims to develop Biology learning evaluation questions based on deep learning and Technological Pedagogical Content Knowledge (TPACK) using the Wordwall platform to improve the Higher Order Thinking Skills (HOTS) of Grade XI students at Madrasah Aliyah Mathlaul Falah Lempuyang. This study used a Research and Development (R&D) approach with a qualitative descriptive design. The research subjects consisted of 30–36 students and a Biology teacher. Data were collected through observation, semi-structured interviews, and documentation. The research stages included needs analysis, question design, expert validation, product revision, trials, and field implementation. The evaluation instrument was developed based on deep learning principles that emphasize conceptual understanding, analysis, problem-solving, and the connection between Biology material and real life, and was integrated with the TPACK framework through the use of Wordwall. The results show that the developed product obtained a highly feasible category based on validation by material, construction, and media experts. The implementation of Wordwall-based evaluation received positive responses from students because it was able to create an interactive, engaging, and enjoyable evaluation atmosphere through game features, leaderboards, and immediate feedback. The use of this evaluation instrument also improved students’ learning outcomes, as reflected in the increase in post-test scores compared with pre-test scores. In addition, students became more active, focused, motivated, and able to understand Biology concepts more deeply. The conclusion of this study emphasizes that Biology learning evaluation based on deep learning and TPACK using Wordwall is feasible for use as an interactive digital evaluation instrument oriented toward HOTS. The implications of this study provide a practical basis for Biology teachers in designing learning evaluations that are innovative, contextual, and aligned with the needs of 21st-century learning.
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