Needs Analysis of Electronic Student Worksheets Work and Energy Based on Deep Learning and Local Wisdom Assisted by Canva AI to Facilitate Student’s Critical Thinking Skills

Abstract

The pressing necessity to include a deep learning strategy into physics education in order to improve students' critical thinking skills served as the motivation for this research. Observations from the real world show that student engagement is still low, which is made worse by the widespread use of conventional teaching resources that have not yet fully incorporated deep learning techniques and technology-based local knowledge. With the aid of Canva AI, this project seeks to create interactive, Deep Learning-based E-Worksheets for the theme of Work and Energy that incorporate local knowledge. The first stage of the research process was a thorough needs analysis and context analysis using Plomp's Design Research approach. A thorough assessment of the instructional materials utilized, the alignment of learning objectives, and the degree of integration between Deep Learning concepts and local wisdom values were all part of the needs analysis. In the meantime, the contextual analysis concentrated on mapping the learning styles of the students and evaluating their critical thinking abilities. Critical thinking test, student needs surveys, and teacher interviews were used to gather data, which was then subjected to descriptive analysis. According to the research findings, pupils' critical thinking skills are classified as "enough." Furthermore, there is a big disconnect between what Deep Learning principles require and what is currently available in terms of teaching resources. However, students showed a great deal of excitement for interactive digital media. E-Worksheets that can integrate local wisdom values as pertinent contextual aids in physics education while also matching students' expectations with Facione's critical thinking indicators.