Blended Learning Program Based on Multiple Representations: Needs Analysis to Stimulate Complex Problem Solving and Reduce Learning Loss - Munadhirotul Azizah; Kartini Herlina*; Abdurrahman Abdurrahman; Nur Arviyanto Himawan (Universitas Syiah Kuala, 2023)
Various complex problems arise along with the increasingly massive development of science and technology in the 21st century. Special skills are needed to survive and adapt to a complex environment and demand various problems to be solved. This study aimed to determine the need for developing multiple representations-based blended learning programs to stimulate complex problem-solving (CPS) and reduce learning loss. This study uses a qualitative descriptive method to provide an overview of the implementation of CPS in high schools and the learning loss during lessons during the Covid-19 pandemic. This research was conducted in July 2022. The data source was obtained using a non-test technique in the form of an open questionnaire. The subjects in this study were 13 physics teachers and 25 students spread across 4th provinces in Indonesia, including Lampung, DIY, Central Java and West Java. The data analysis technique is the Milles Hubberman analysis technique carried out continuously until the data is saturated. Data analysis involves three steps, data reduction, data presentation, and concluding/verification. Study result show that CPS has yet to be fully implemented in physics learning in high schools. Learning during the Covid-19 pandemic was ineffective and maximal, which resulted in most students experiencing setbacks in learning and a decrease in academic progress (learning loss). Therefore, developing a blended learning program based on multiple representations is necessary to stimulate complex problem-solving and reduce learning loss