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Implementation of Differentiated Learning Based on Computational Projects to Improve Student Skills Data Analysis and Digital Literacy on Economics Faculty, Medan State University a) Universitas Negeri Medan Abstract This research investigates the differences in students data analysis and digital literacy skills by controlling students prior knowledge through differentiated learning based on computational projects. Differentiated learning was implemented to accommodate students varying readiness levels, learning preferences, and interests. Simultaneously, project-based computational activities were designed to immerse students in hands-on, contextual learning using digital tools for data analysis. Employing a quantitative, posttest-only control group design, the subjects of this study consisted of two classes from the economics education study program. Data were collected by observations, test of data analysis competence, and digital literacy questionnaire. Analysis of covariance (ANCOVA) was used to analize and interpret the results. The findings revealed statistically significant differences between students engaged in the differentiated learning based on computational project those in conventional learning, with controlling student prior knowledge. Notably, students with lower digital literacy demonstrated marked improvement in analytical skills under the project-based differentiated model. Conversely, students with high digital literacy performed well under both instructional strategies. These outcomes suggest that combining differentiation with computational projects offers a promising pedagogical framework, particularly beneficial for supporting learners with diverse digital competencies. This approach aligns with current educational goals to foster digital transformation in higher education environments Keywords: differentiated learning- computational projects- data analysis- digital literacy Topic: Management and Educational Technology Innovation |
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