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Mathematics Anxiety Profiles and Dominant Predictors of Students’ Mathematical Problem-Solving Ability for SDG 4: Quality Mathematics Education Herfa Maulina Dewi Soewardini; Yusuf Fuad; Rooselyna Ekawati
Journal of Current Studies in SDGs Vol. 3 No. 1 (2027): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.3.1.305

Abstract

Objective: The study aims to identify mathematics anxiety profiles among junior high school students and examine the dominant psychological predictors influencing students’ mathematical problem-solving ability. The study addresses the limitation of previous research that often treats mathematics anxiety as a single emotional barrier by examining variations in students’ anxiety characteristics and their associated predictors. Method: A mixed-methods sequential explanatory design was employed involving 183 seventh-grade students from two public junior high schools in West Surabaya, Indonesia. Quantitative data were collected using a mathematics anxiety questionnaire and a mathematical problem-solving ability test. Descriptive statistics and multiple regression analysis were conducted to identify anxiety profiles and determine dominant predictors within each profile. Qualitative data from interviews were analyzed to provide deeper explanations of quantitative findings. Results: The findings revealed that students demonstrated different mathematics anxiety characteristics associated with variations in problem-solving ability. Regression analysis showed that dominant predictors differed across anxiety profiles. Psychological factors emerged as the strongest predictor in Cluster 1 (B = 1.692, p < 0.001), while personality factors became the dominant predictor in Cluster 2 (B = 1.899, p = 0.021). Novelty: The study contributes to mathematics education research by demonstrating that mathematics anxiety should not be viewed as a homogeneous construct. Instead, different anxiety profiles are associated with different dominant predictors, providing implications for developing differentiated learning strategies that support inclusive and quality mathematics education aligned with Sustainable Development Goal 4.