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Elna Mar'atussholihah
Universitas Singaperbangsa Karawang

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Validity and Reliability of the Mathematics Academic Self-Concept (MASC) Scale Through Confirmatory Factor Analysis (CFA) Elna Mar'atussholihah; Asya Khaula Aziza; Rafiq Zulkarnaen
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 11 No 2 (2026): October
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v11i2.8183

Abstract

This study aims to adapt and examine the validity and reliability of the Academic Self-Concept instrument originally developed by Liu and Wang (2005) within the context of mathematics, resulting in the development of the Mathematics Academic Self-Concept (MASC) scale. The instrument consists of 20 items encompassing two main dimensions, namely Mathematics Academic Confidence and Mathematics Academic Effort. A total of 252 senior high school students participated as respondents. The analyses employed in this study included Item Fit Analysis, Confirmatory Factor Analysis (CFA), and reliability testing. The item fit results indicate that all items contribute significantly to the construct, with estimation values ranging from 0.299 to 0.616, thereby confirming that all items are suitable for retention. The KMO value of 0.818 and a significant Bartlett’s test (p < 0.001) further demonstrate the adequacy of the data for factor analysis. Although certain model fit indices, such as GFI (0.935), suggest good model fit, the RMSEA (0.154) and CFI (0.852) values indicate that model refinement is still required. The factor loadings for all items fall within moderate to high ranges, supporting adequate construct validity. Reliability testing yielded α = 0.778 for the confidence subscale, α = 0.756 for the effort subscale, and an overall reliability of α = 0.853, indicating strong internal consistency. Therefore, the MASC instrument is deemed valid and reliable for measuring mathematics academic self-concept, although further model adjustments are needed to achieve optimal fit.