An ADDIE-Based Development and Evaluation of a Mobile Learning Environment for Enhancing Biology Students’ Self-Regulation, Motivation, and Achievement in Benthic Macrofauna Identification
Abstract
Purpose of the study: This study examines the design, development, implementation, and evaluation of a Mobile Learning Environment (MLE) and its impact on biology students’ self-regulation, motivation, and achievement, based on Self-Determination Theory.
Methodology: Guided by the ADDIE model, the study employs a developmental research design using a researcher-developed MLE (Android-based) for species identification. A paired sample t-test was used to analyze significant differences in students' self-regulation, motivation, and achievement. Scope reviews were conducted to identify gaps and solutions through in-depth focus group discussions among biology students.
Main Findings: Results showed significant improvements across all measures (all p < .001). Self-regulation increased (autonomous: d ≈ 1.87; controlled: d ≈ 1.43). Motivation improved across dimensions: attention (3.62–4.70, d ≈ 1.51), relevance (3.91–4.79, d ≈ 1.41), confidence (3.76–4.58, d ≈ 1.31), and satisfaction (3.75–4.72, d ≈ 1.48). Achievement showed large gains (common names: d ≈ 1.60; scientific names: d ≈ 2.20). The MLE was highly rated in engagement (M = 4.76), functionality (M = 4.50), and information quality (M = 4.72). Psychological need satisfaction was also high (autonomy: M = 6.51; competence: M = 6.60; relatedness: M = 5.96).
Novelty/Originality of this study: The development of a context-specific MLE for species identification of benthic macrofauna integrated in enhanced Teaching–Learning Sequences advances existing knowledge by providing an empirically validated, learner-centered digital tool for species identification with engaging features and contents, addressing gaps in both traditional and mobile-assisted taxonomy learning at the tertiary level.
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