Deep Learning Approach and Mechanics KIT on the Shift in Conceptions of Junior High School Students on the Material of Vibrations and Waves

Misconceptions in vibration and wave topics remain a common problem in junior high school science learning, particularly due to the abstract nature of the concepts and their limited direct observability. This study aimed to analyze students' conceptual shifts on vibration and wave concepts through the implementation of a Deep Learning approach supported by a Mechanical KIT. The study employed a one-group pretest–posttest experimental design involving three classes, comprising one experimental class and two replication classes, with a total of 69 eighth-grade students serving as research participants. A three-tier diagnostic test consisting of ten multiple-choice items was used to identify students' conceptual categories, including guessing, lack of conceptual understanding, misconception, and sound conceptual understanding. The data were analyzed descriptively using SPSS to examine the direction and quality of students' conceptual shifts before and after the intervention. The results indicated that the Deep Learning approach, assisted by the Mechanical KIT, effectively facilitated positive conceptual shifts, as evidenced by a dominant transition from misconceptions, a lack of understanding, and guessing toward sound conceptual understanding across all classes. The most substantial conceptual improvements were observed in indicators related to the relationships among frequency, period, and amplitude, while relatively lower shifts occurred in concepts requiring higher levels of mathematical reasoning. These findings suggest that integrating a Deep Learning approach with concrete instructional media, such as a Mechanical KIT, is effective in promoting meaningful conceptual reconstruction and reducing misconceptions in vibration and wave learning.