Research Article
Implementation of Differentiated Learning Based on Computational Projects to Improve Student Skills Data Analysis and Digital Literacy on Economics Faculty, Universitas Negeri Medan
@INPROCEEDINGS{10.4108/eai.16-9-2025.2361111, author={Andi Taufiq Umar and Jabal Ahsan and Lucky Satria Pratama}, title={Implementation of Differentiated Learning Based on Computational Projects to Improve Student Skills Data Analysis and Digital Literacy on Economics Faculty, Universitas Negeri Medan}, proceedings={Proceedings of the 7th International Conference on Innovation in Education, Science, and Culture, ICIESC 2025, 16 September 2025, Medan, Indonesia}, publisher={EAI}, proceedings_a={ICIESC}, year={2026}, month={3}, keywords={differentiated learning computational projects data analysis digital literacy}, doi={10.4108/eai.16-9-2025.2361111} }- Andi Taufiq Umar
Jabal Ahsan
Lucky Satria Pratama
Year: 2026
Implementation of Differentiated Learning Based on Computational Projects to Improve Student Skills Data Analysis and Digital Literacy on Economics Faculty, Universitas Negeri Medan
ICIESC
EAI
DOI: 10.4108/eai.16-9-2025.2361111
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. 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. The findings with Analysis of covariance (ANCOVA) revealed statistically significant differences between students engaged in the differentiated learning based on computational project those in direct learning, with controlling student prior knowledge. 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.
