Profiling Students’ Performance Across Deep-Learning-Oriented Item Groups Through Global-Issue-Based Chemical Nomenclature Assessment

Abstrak

Chemical nomenclature assessments often emphasize final-answer accuracy and provide limited diagnostic information about students’ performance across different task orientations. This study examined performance, mastery patterns, and learner profiles across Mindful Learning-oriented, Meaningful Learning-oriented, and Joyful Learning-oriented item groups using a global-issue-based chemical nomenclature assessment. A quantitative descriptive design involved 101 Grade X students from a senior high school in Semarang, Indonesia. The instrument consisted of ten constructed-response items scored using a five-level analytic rubric. Data were analyzed using descriptive statistics, mastery classification with a threshold of 70, rule-based learner profiling, pairwise score mapping, and repeated-measures analysis of variance. Mean scores were 54.82, 60.22, and 58.12 for the Mindful, Meaningful, and Joyful item groups, respectively. The overall difference was statistically significant but small, F(1.85, 184.74) = 3.36, p = .041, partial η² = .032. Non-mastery was most frequent in the Mindful group. Learner profiling identified 29 Advanced, 30 Emerging, and 42 Developing learners. Lower performance was concentrated in tasks requiring careful symbolic interpretation and systematic application of nomenclature rules.

Kata kunci

• Bottlenecks
• Chemistry Education
• Deep Learning
• chemical nomenclature
• diagnostic assessment
• learner profiling
• mastery patterns