DliLearn: LMS-Assisted PBL for Critical Thinking in Algorithms and Programming: One-Group Pretest–Posttest Study

Fadli Ridwansyah; Andini Setya Arianti; Munir Munir

doi:10.17509/edsence.v8i1.100891

DliLearn: LMS-Assisted PBL for Critical Thinking in Algorithms and Programming: One-Group Pretest–Posttest Study

Fadli Ridwansyah, Andini Setya Arianti, Munir Munir

Abstract

Low student participation and weak critical thinking skills in algorithm and programming learning motivated this study. Teacher-centered learning and limited learning media often hinder students from understanding programming logic and concepts. Therefore, this study implemented a Problem-Based Learning (PBL) model combined with a Deep Learning supported by a Learning Management System (LMS) called DliLearn. This study employed Research and Development (R&D) employing the ADDIE framework model and a one-group pretest-posttest design. The participants were 25 students of class XI-3 at SMAN 1 Katapang. Data were acquired through observation, interviews, questionnaires, pretests, and posttests, and were analyzed using the Shapiro-Wilk normality test, the Wilcoxon Signed Rank Test, and N-Gain calculation. The Wilcoxon test revealed a significance level of p < .001), suggesting the existence of a statistically significant difference between pretest and posttest scores after implementation. The average N-Gain score was 0.708, slightly above the high-criteria threshold, with 14 students in the high criteria, 11 in the moderate criteria, and none in the low criteria. These findings indicate improved critical thinking skills after implementation, although causal claims should be made cautiously.

Keywords

Problem-Based Learning, Deep Learning Approach, Learning Management System, Critical Thinking Skills, Algorithm and Programming, One-Group Pretest–Posttest Design

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DOI: https://doi.org/10.17509/edsence.v8i1.100891