Comprehensive Literature Review: Use of E-Modules Based on Artificial Intelligence in Science Subjects and its Implications on Teaching and Learning
DOI:
https://doi.org/10.37134/bitara.vol17.2.7.2024Keywords:
e-module, digital based learning, artificial intelligence, science subject, TnLAbstract
According to the Ministry of Science, Technology, and Innovation (MOSTI), the trend of students taking Additional Mathematics and Pure Sciences, Physics, Chemistry, and Biology, is declining, with candidates taking the Malaysian Certificate of Education (SPM) in 2023 recording a decrease of 3.33% for Additional Mathematics, Physics (1.42%), Chemistry (1.42%), and Biology (2.2%). However, the results of SPM 2023 for all these subjects have increased compared to the previous year. Previous studies have shown that the use of digital technology like e-modul is seen as very helpful in improving student performance during Teaching and Learning sessions (TnL). Furthermore, the use of various technologies during TnL sessions has grown since the spread of COVID-19 making TnL sessions more flexible, easy to access and attracts students' interest in Science when they can interact directly with materials from global sources. This development has created a variety of digital teaching mediums and applications such as the use of Artificial Intelligence (AI) that is capable of performing tasks and functions similar to human thinking to create a systematic TnL sessions. For example, the use of ChatGPT helps teachers efficiently prepare Daily Lesson Plans (DLP). The increased use of AI has also attracted the interest of major company like Google, which invested RM9.4 billion in Malaysia as an effort to enhance AI literacy programs for the benefit of teachers and students. Hence, this study is being conducted to identify the usage and impact of AI-based e-modules for Science subjects. Next, by conducting a systematic review analysis of 30 journal articles and books related to the use of AI in TnL sessions published between 2017 and 2024, an overview of the development of AI-based digital education in TnL sessions can be seen. The results of past studies found a positive increase where the use of AI in TnL sessions enhances understanding, motivation, student engagement and stimulates critical thinking among students. In conclusion, the findings from the literature review show that the application of AI in TnL helps students improve their achievement in Science. This is because the use of AI can personalize learning, provide automatic guidance and create interactive educational content, which directly increases students' interest and understanding. In line with the nation's commitment to enhancing dynamic STEM education, the realization of cultivating a highly knowledgeable and critical-thinking generation to confront the digital economy era will be achieved.
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