<![CDATA[This study aims to produce a feasible deep learning-based educational game learning medium assisted by Construct 3. This study was conducted at SMAN 10 Kota Jambi with the research subjects being class XI Phase 2. This study used the Lee & Owens development model, namely: analysis, design, development, implementation, and evaluation. The research instruments used were interview guidelines and questionnaires. The data analysis techniques used were qualitative data analysis (suggestions and comments) and quantitative data analysis (percentage and average answer scores). The results of this study indicate that this deep learning-based educational game assisted by Construct 3 is feasible conceptually and procedurally, with a material expert feasibility score of 98% (Very Good), a media expert score of 93% (Very Good), and a teacher assessment score of 94% (Very Good). The deep learning-based educational game assisted by Construct 3 can be used at all cognitive levels of students with a percentage of 86.6% (Very Good) and student responses have a percentage of 93.1% (Very Good). Based on the results obtained, it can be concluded that the deep learning-based educational game assisted by Construct 3 is very feasible to be used in learning to increase student motivation in reaction rate material.]]>
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