Ramaniza Adinda Maharani
Universitas Pendidikan Indonesia

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Relationships and differences in learning outcomes based on self-esteem and learning motivation among eleventh-grade students Ramaniza Adinda Maharani; Bill Chairy Rizki Bustaren; Cici Utami Salamah; Irene Feby Putri; Natasha Dwi Fitria; Mohd Afifi Bahurudin Setambah
UNION : Jurnal Ilmiah Pendidikan Matematika Vol 14 No 3 (2026)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/union.v14i3.22908

Abstract

This ex post facto quantitative study examined the relationships of self-esteem and learning motivation with students’ mathematics achievement and compared these variables across classes. The sample included all eleventh-grade students from three classes (N = 87) at a private senior high school in Bandung, Indonesia. Data were collected via adapted questionnaires based on Rosenberg’s global self-esteem theory and Uno’s learning motivation theory (content validity confirmed through expert review, with Cronbach’s alpha coefficients of  = .850 and .628, respectively), while achievement was represented by students’ midterm examination and daily test scores. Spearman’s rho analysis conducted in Google Colab revealed significant but weak positive correlations between achievement and both self-esteem ( = .280, p = .009) and motivation ( = .377, p < .001). The weak coefficients indicate that these affective variables explain only a small share of the variation in achievement. Furthermore, the Kruskal-Wallis test showed significant differences across classes; Class XI.4 consistently exhibited the lowest academic and affective scores. Theoretically, the findings therefore offer only limited confirmation of the assumed link between affective characteristics and mathematics achievement. Practically, teachers should consider classroom-level psychological profiles when designing adaptive, differentiated mathematics instruction. This study contributes by demonstrating that class-level affective profiling can reveal meaningful psychological heterogeneity that may be obscured by cohort-level analysis, thereby providing a more context-sensitive basis for differentiated mathematics instruction.