Deep Learning Engagement as a Predictor of Academic Self-Efficacy and Language Performance
DOI:
https://doi.org/10.15408/tjems.v12i1.46710Keywords:
deep learning engagement, latent profile analysis, academic self-efficacy, self-regulated learning, keterlibatan pembelajaran mendalam, analisis profil laten, efikasi diri akademik, pembelajaran yang diatur sendiriAbstract
Abstract
This study investigates how deep learning engagement influences academic self-efficacy and language performance among English majors in Indonesia. Deep learning is an active and reflective process that involves critical thinking, conceptual integration, and self-regulated learning. Using a person-centred quantitative design, data were collected from 300 English majors across three universities and analysed through Latent Profile Analysis (LPA). This study applies LPA in English as Foreign Language (EFL) higher education and examines how learner diversity can be observed in a Muslim-majority population. The analysis identified three distinct learner profiles: reflective analysts, strategic learners, and passive processors. Reflective Analysts achieved the highest levels of academic self-efficacy and language performance, as measured by GPA in writing and speaking. In contrast, Passive Processors recorded the lowest scores. Profile membership was significantly influenced by academic year with clear developmental trend, whereas gender had no effect. Overall, the findings confirm that deep learning engagement is a strong predictor of EFL achievement. Theoretically, the study advances understanding of learner diversity of deep learning within Southeast Asian higher education. Practically, The study underscores the need for differentiated instruction (e.g., reflective writing and scaffolding) to help less engaged learners strengthen their critical reflection and self-regulation.
Abstrak
Penelitian ini bertujuan mengungkapkan bagaimana keterlibatan dalam pembelajaran mendalam memengaruhi efikasi diri akademik dan kinerja bahasa di kalangan mahasiswa jurusan Bahasa Inggris di Indonesia. Pembelajaran mendalam merupakan proses aktif dan reflektif yang melibatkan berpikir kritis, integrasi konseptual, dan pembelajaran yang diatur sendiri. Dengan menggunakan desain kuantitatif berpusat pada individu, data dikumpulkan dari 300 mahasiswa jurusan Bahasa Inggris di tiga universitas dan dianalisis melalui Latent Profile Analysis (LPA). Studi ini menerapkan LPA dalam konteks pendidikan tinggi Bahasa Inggris sebagai bahasa asing (EFL) dan menelaah bagaimana keragaman pembelajar dapat diamati pada populasi mayoritas Muslim. Analisis mengidentifikasi tiga profil pembelajar yang berbeda: reflective analysts, strategic learners, dan passive processors. Reflective Analysts mencapai tingkat efikasi diri akademik dan kinerja bahasa tertinggi, diukur berdasarkan IPK dalam keterampilan menulis dan berbicara. Sebaliknya, Passive Processors mencatat skor terendah. Keanggotaan profil dipengaruhi secara signifikan oleh tahun akademik dengan tren perkembangan yang jelas, sedangkan jenis kelamin tidak berpengaruh. Secara keseluruhan, temuan ini menegaskan bahwa keterlibatan dalam pembelajaran mendalam merupakan prediktor kuat terhadap pencapaian EFL. Secara teoretis, penelitian ini memperluas pemahaman tentang keragaman pembelajar dalam konteks pembelajaran mendalam di pendidikan tinggi Asia Tenggara. Secara praktis, penelitian ini menekankan perlunya pembelajaran berdiferensiasi (misalnya, penulisan reflektif dan scaffolding) untuk membantu pembelajar yang kurang terlibat dalam memperkuat refleksi kritis dan pengaturan diri mereka.
How to Cite: Istiara, F., Sutrisno, J., Tama, O. H., Mahrunnisya, D., Ajeng, G. D., Adijaya, N., Saputra, D. W., & Hadi, M. S. (2025). Deep Learning Engagement as a Predictor of Academic Self-Efficacy and Language Performance. TARBIYA: Journal of Education in Muslim Society, 12(1), 115-126. doi:10.15408/tjems.v12i1.46710.
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Copyright (c) 2025 Febriyantina Istiara, Joko Sutrisno AB, Ozi hendra Tama, Dyanti Mahrunnisya, Galuh Dwi Ajeng, Nuryansyah Adijaya, Dendi Wijaya Saputra, Muhammad Sofian Hadi
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