Development of Google Sites-based Multiple Representations Learning Media on Benzene and Its Derivatives Topic

Abstract

COVID-19 pandemic accelerated the transformation of education and forced the digitalization of education to create effective learning. The understanding of complex chemical structures and reactions holds great significance in the realm of chemistry education. Benzene and its derivatives are particularly challenging topics that require a robust representation approach. The research aims to develop and assess the feasibility of Google Sites-based multiple representations learning media on benzene and its derivatives material. The research utilized the Research and Development (R&D) approach, adhering to the ADDIE (analysis, design, development, implementation, and evaluation) development model. The research was carried out until the development stage. The developed learning media effectively integrated three levels of chemical representation for benzene and its derivatives, utilizing various features such as text, animation, video, 3D molecular simulation, and images. The validation conducted by content and media experts indicated that the learning media is valid with scores of 95.8% and 92.5%, respectively, with excellent category. Furthermore, the product quality assessment conducted by experts and students' responses showed that media could be used practically, with percentages of 95% and 95% as excellent categories. These findings confirm the suitability of the developed learning media for facilitating students' understanding of benzene and its derivatives during the learning process.