Deep Learning-Based Electronic Module and Motivation Levels to Enhance Students' HOTS-based Science Literacy

Yuni Arliyana Togatorop; Retno Dwi Suyanti; Murniaty Simorangkir

Authors

Yuni Arliyana Togatorop Universitas Negeri Medan
Retno
Murniaty

Keywords:

Deep Learning, Electronic module, HOTS-based science literacy, Motivation level, Inquiry-based learning

Abstract

The goals of this study were to determine: 1) feasibility and practicality of deep learning-based electronic module, and 2) effectiveness of the deep learning-based electronic module and the role of motivation levels in enhancing students' HOTS-based Science Literacy ability. Type of this study is Research and Development (R&D) and use the ADDIE development model. The study involved 42 students from SMA Negeri 16 Medan as the research sample. Two-Way ANOVA was used for hypothesis testing. The yields of feasibility and practicality test indicate that the deep learning-based electronic module is feasible and practical as teaching material. Feasibility were assessted by matter and media experts. Score for matter feasibility was 3.55 (categorized as very good) and for media feasibility was 3.79 (categorized as very good). Practicality assessments were based on student and teacher responses; the scores obtained were 84.27% (very good) for teachers and 75.27% (good) for students from the experimental class. The N-gain score for the experimental class was 0.75, while the N-gain score for the control class was 0.24. Two-Way ANOVA results show a significant difference in HOTS-based Science Literacy ability, with the experimental class outperforming the control class (Sig <.001). Significant differences were also observed in HOTS-based Science Literacy ability based on students' motivation levels (Sig.<.001). However, there was no interaction between teaching material and motivation levels (Sig.<.218). Instead of playing as a moderate variabel, motivation levels also play as independent variable that give direct effects (main effects) on the dependent variable.

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