The Effect of Blooket-Assisted Deep Learning Approach on Elementary School Students’ Critical Thinking Skills
Abstract
Critical thinking skills are an important 21st century competency that needs to be integrated into the elementary school curriculum, but the reality on the ground shows the dominance of conventional approaches that limit students' high-level cognitive development. This research seeks to examine how the use of a Deep Learning method, supported by Blooket gamification tools, influences students' abilities in critical thinking regarding the subject of transformations in the states of matter. Using a quantitative method with a quasi-experimental design of the nonequivalent control group design type, this study involved 54 fourth-grade students of Keboananom Elementary School as subjects. Data was collected through a critical thinking ability test instrument in the form of descriptive questions that measure indicators of analysis, evaluation, and decision-making which were given through a pretest and posttest. The data analysis technique was carried out using parametric statistics using an independent sample t-test to compare the scores obtained between the experimental group and the control group. The results of the study showed a significant difference with a significance value of 0.000 (p < 0.05), where the class that implemented Deep Learning showed a higher increase in critical thinking skills. In conclusion, the integration of Blooket-assisted Deep Learning approach is effective in strengthening students' reflective cognitive processes. This research provides practical contributions for educators in implementing innovative learning technologies to create active and challenging learning environments in elementary schools
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