Improving Learner Autonomy and Problem-Solving Skills Through The STAD Cooperative Learning Strategy In Digital Pattern Making for Vocational Fashion Education - Nurhijrah; Syarifah Suryana (Academic Bright Collaboration, 2026)
Purpose – The rapid digital transformation of the fashion industry has increased the need for vocational students to develop not only technical competencies but also learner autonomy and problem-solving skills in software-intensive learning environments. This study aimed to investigate the effectiveness of the Student Teams Achievement Divisions (STAD) cooperative learning model integrated with digital pattern-making instruction in improving these competencies among vocational fashion students. Methods – The study employed a quasi-experimental design using a non-equivalent control group pretest–posttest approach. Participants consisted of 59 eleventh-grade students enrolled in a vocational fashion program in Indonesia, divided into an experimental group (n = 30) and a control group (n = 29). Data were collected using a learner autonomy questionnaire and a performance-based problem-solving assessment related to digital pattern-making tasks. Data analysis involved descriptive statistics, paired sample t-tests, independent sample t-tests, and Analysis of Covariance (ANCOVA). Findings – The findings indicated that students who participated in STAD-based digital pattern-making instruction demonstrated higher improvements in learner autonomy and problem-solving skills compared to students who received conventional instruction. ANCOVA results revealed statistically significant treatment effects for learner autonomy and problem-solving skills (p < 0.001). Although large effect sizes were observed, the findings should be interpreted cautiously due to the relatively small sample size, intact-class design, single-institution setting, and partial reliance on self-report measures. Therefore, the study provides preliminary quasi-experimental evidence rather than broad generalizable conclusions. The contribution of this study lies in applying the STAD cooperative learning model to software-intensive vocational fashion learning tasks, particularly digital pattern making. Research implications – The findings suggest that collaborative digital learning environments may support the development of self-regulated learning behaviors and authentic vocational problem-solving skills in fashion education contexts Originality – The contribution of this study lies in applying the STAD cooperative learning model to software-intensive vocational fashion learning tasks, particularly digital pattern making.