Identifikasi Extranous Cognitive Load Siswa Dalam Mengembangkan Computational Thinking Skill Melalui Pembelajaran Jaring-Jaring Makanan Berbasis Snap!

Abstract

Food webs learning using the Snap! is one of the learning strategies that are expected to help improve students' computational thinking. For students, this learning strategy were something new and can cause Extraneous Cognitive Load (ECL). The purpose of this study was to identify students' ECL in food web learning using the Snap! to develop computational thinking skills. The research method used in this study was a pre-experimental design with a modified research design from an iterative action design. The sampling technique was purposive sampling. The sample in this study consisted of 30 seventh grade students at SMPN 2 Bandung. The research instrument used in this study was a student mental effort questionnaire to measure ECL, field notes, and a computational thinking test. Based on the results of the study, students' ECL was relatively low and increased at each meeting, except for the second meeting. Students experience an increase in their computational thinking skills after participating in food web learning using the Snap! computational model. The results of the N-Gain analysis also show that the improvement of students' computational thinking is in the moderate category and is quite effective.