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All Journal Proceeding of International Conference on Biology Education, Natural Science, and Technology
Edward Harefa
Beijing Normal University
Biochemistry, Genetics & Molecular Biology Chemistry Education Physics

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From STEM Knowledge to Technology Integration: The Mediating Role of Intrinsic Motivation and Growth Mindset Among Elementary Teachers Edward Harefa; Darmawan Harefa; Murnihati Sarumaha; Daindo Milla; Rebeka Filda Hawali; Mikaus Gombo; Adam Smith; Yushun Li; Jian Xu
Proceeding of International Conference on Biology Education, Natural Science, and Technology 2026: Proceeding of International Conference on Biology Education, Natural Science, and Technology
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

Despite national policy mandates for STEM and technology integration in Indonesian elementary education, teachers continue to struggle with implementation due to unresolved questions about the cognitive and psychological mechanisms driving adoption behavior. This study examined whether STEM knowledge predicts technology integration through the parallel mediation of intrinsic motivation and growth mindset. Using a quantitative cross-sectional design, data were collected from 267 elementary teachers and analyzed through covariance-based structural equation modeling. The findings revealed that STEM knowledge had a significant direct effect on technology integration (β = 0.296, p < 0.001). The parallel mediation model was supported with intrinsic motivation (β = 0.170, p < 0.001) and growth mindset (β = 0.155, p < 0.001), both of which significantly mediated the relationship. The study concludes that STEM knowledge functions as a foundational cognitive resource that simultaneously activates motivational and mindset mechanisms. These findings imply that teacher preparation programs should integrate STEM content and technology training, while schools should cultivate autonomy-supportive climates and growth-oriented professional cultures to create self-reinforcing developmental ecologies for sustained technology integration.
Does Prior Life Science Knowledge Matter? A Moderated Mediation Model of AI-Supported Learning, Self-Regulated Learning, and Life Science Achievement in Elementary Education Edward Harefa; Muhammad Yatim; Sumangeli Gulo; Novelina Andriani Zega; Eka Periaman Zai; Otilina Gulo; Devi Chrisman Lase; Hosianna Rodearni Damanik; Dernius Hura; Indah Wijaya Lase
Proceeding of International Conference on Biology Education, Natural Science, and Technology 2026: Proceeding of International Conference on Biology Education, Natural Science, and Technology
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

This study addresses the critical gap between the widespread adoption of AI-powered educational technologies and the persistently low life science achievement among Indonesian elementary students. The objective is to uncover the mechanisms and boundary conditions shaping this relationship by testing a moderated mediation model in which self-regulated learning mediates the effect of perceived AI-supported learning on life science achievement, and prior life science knowledge serves as a critical moderator. A quantitative cross-sectional survey was conducted with 253 elementary students. Using partial least squares structural equation modeling, the findings reveal that self-regulated learning fully mediates the relationship between perceived AI-supported learning and life science achievement (β = 0.134, p < 0.001), while the direct effect remains non-significant (β = −0.058, p = 0.361). Prior life science knowledge significantly moderates both pathways (β = 0.172, p = 0.004; β = 0.158, p = 0.004). AI tools enhance achievement primarily by fostering self-regulatory capacities, with significant benefits restricted to students whose prior life science knowledge exceeds 1.71 standard deviations above the mean. These results advance a conditional, mediated theoretical framework for technology-enhanced life science learning and highlight the practical necessity of differentiated AI implementation paired with explicit metacognitive instruction.
Co-Authors Adam Smith Daindo Milla Darmawan Harefa Dernius Hura Devi Chrisman Lase Hosianna Rodearni Damanik Indah Wijaya Lase Jian Xu Mikaus Gombo Muhammad Yatim Murnihati Sarumaha Novelina Andriani Zega Otilina Gulo Rebeka Filda Hawali Sumangeli Gulo Yushun Li ZAI, EKA PERIAMAN