Data-Driven Profiling of Teachers’ Competence in Numeracy Instruction: K-Means Clustering Analysis of “Gembira” Training Participants
DOI:
https://doi.org/10.21831/jrpm.v13i1.96924Keywords:
K-means clustering, Mathematical “GEMBIRA”, Numeracy, Teacher profilingAbstract
This article aims to identify and categorize the competency profiles of teachers who participated in the mathematical “GEMBIRA” training in supporting mathematics instruction and strengthening the numeracy program in Indonesia. The study employed a quantitative survey method with a case study approach involving 2,450 teacher respondents. The research instruments were based on three key dimensions: (1) mindset, skillset, toolset, and professional attitudes; (2) implementation of “GEMBIRA” learning; and (3) understanding and implementation of the numeracy program. Data analysis was conducted in two stages. First, descriptive analysis was used to classify teacher competencies into four levels: emerging, developing, proficient, and transformative. Second, K-Means cluster analysis was applied to identify patterns and group teachers based on similarities in their characteristics and competencies. The findings revealed that most teachers were at the transformative level, followed by the proficient level, while only a very small number remained at the developing level. Furthermore, cluster analysis identified three main competency groups: high, medium, and basic. Although the majority of teachers demonstrated high competency, the presence of medium and basic groups indicates the need for targeted capacity-building efforts. Overall, the study highlights the importance of continuous professional development to optimize numeracy learning implementation.
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