Development and Implementation of Android-Based Coleega Application with Representation Learning Cycle Model: An Effort to Improve Representation Competence in Colligative Properties of Solution - Herunata Herunata; Ridwad Joharmawan; Ilma Kanzu Iklima (Universitas Negeri Surabaya, 2026)
This study investigates the effectiveness of Coleega, an Android-based application integrated with the Representation Learning Cycle (RLC) model, in enhancing students’ representational competence on colligative properties of solutions. The RLC model, adapted from Problem-Based Science, structures learning into six phases: orientation, questioning, planning, execution, analysis, and presentation. Conducted at a senior high school in East Java with 68 students selected via cluster random sampling, the study employed pretests and posttests to measure conceptual understanding and representational skills. Validation confirmed feasibility (Aiken’s V = 0.74) and readability (92%). Effectiveness was demonstrated by independent t-test (p < 0.001), showing significantly higher posttest scores in the experimental group (M = 87.94) compared to the control (M = 80.94). Findings highlight the novelty of embedding RLC into mobile technology, demonstrating that Coleega is both feasible and effective in strengthening representational competence in chemistry learning.