Students’ Mathematics Anxiety After Participating in a Deep Learning-Oriented Teams-Games Tournament Supported by Wordwall - Erna Emiliana; Imam Kusmaryono (Jurnal Didactical Mathematics, 2026)
Mathematics anxiety remains a persistent challenge in mathematics education because it can reduce students' engagement, confidence, and academic performance. This study investigated the effect of a deep learning-oriented Teams-Games Tournament (TGT) model supported by Wordwall on students' mathematics anxiety during integer learning. A quantitative pre-experimental study employing a one-group pretest–posttest design was conducted with 32 seventh-grade students from SMP Negeri 1 Trangkil, Indonesia, selected through cluster random sampling. Data were collected using a validated mathematics anxiety questionnaire and analyzed using a paired-samples t-test. The findings revealed a statistically significant reduction in students' mathematics anxiety following the intervention (p < .001). The mean anxiety score decreased from 74.48 to 52.73, with a very large effect size (Cohen's d = 2.40). These findings suggest that integrating deep learning principles, cooperative learning, and Wordwall-based gamification can create more engaging and emotionally supportive mathematics learning experiences that help reduce students' mathematics anxiety. This study contributes empirical evidence supporting the integration of technology-enhanced cooperative learning to promote positive affective outcomes in mathematics education.