Jasnika, Inka
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Predicting Academic Achievement Through Motivation and Self Regulated Learning Basith, Abd; Fitriyadi, Slamat; Suwanto, Insan; Mariana, Dewi; Kamaruddin; Rahman, Md. Shahinoor; Moseki, Usina Robert; Jasnika, Inka; Anriani, Putri; Mawazid, Zidni
Jurnal Pendidikan Indonesia Vol 14 No 2 (2025): June
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jpi-undiksha.v14i2.89041

Abstract

Academic achievement in Indonesia, compared to other countries in the world, is very concerning. Students tend to have low motivation and self-regulation. This certainly has an impact on students' low learning outcomes and academic achievement. This study aims to analyze motivation and self-regulated learning in determining students' academic achievement. This study uses a quantitative method with survey learning and cross-sectional design. The study population was 800 students. The research sample was taken using a random sampling formula, so the sample used was 741 students. The instruments used in data collection were MSLQ and the academic achievement index. Data were analyzed using descriptive analysis, correlation, and regression. The results showed that all motivation and self-regulation learning indicators had a significant relationship with academic achievement. However, only the value component indicator, the expectancy component, the affective component, and the resource management strategy could significantly predict academic achievement. All components of motivation and self-learning strategies had a significant positive correlation with academic achievement, except for test anxiety, which had a significant negative correlation with students' academic achievement. The implications of this research are that this research provides information regarding motivation and independent learning that must be improved in students so that it can improve students' academic achievement better so that learning objectives can be achieved optimally.