Building Smart Learners: AI-Deep Learning, Digital Literacy, and Self-Regulation as Predictors of IPAS Outcomes

Anang Subiantoro; K Kadeni; Muhammad Anasrulloh; Hikmah Eva Trisnantari

doi:10.58905/saga.v3i3.569

Authors

Anang Subiantoro Universitas Bhinneka PGRI, Tulungagung, Indonesia
Kadeni Universitas Bhinneka PGRI, Tulungagung, Indonesia
Muhammad Anasrulloh Universitas Bhinneka PGRI, Tulungagung, Indonesia
Hikmah Eva Trisnantari Universitas Bhinneka PGRI, Tulungagung, Indonesia

DOI:

https://doi.org/10.58905/saga.v3i3.569

Keywords:

AI-based learning, deep learning, digital literacy, learning independence, IPAS, PLS-SEM

Abstract

The rapid advancement of digital technology has made it imperative to adopt innovative instructional approaches in elementary-level IPAS (Natural and Social Science) education in Indonesia. Baseline data from Cluster 2, Pule District revealed that only 40.19% of Grade VI students met the minimum mastery criterion (KKM) in 2024/2025. This study examines the effects of AI-based IPAS learning through deep learning (X1), digital literacy (X2), and learning independence (X3) on student learning outcomes (Y) using a quantitative correlational non-experimental design. A proportional random sample of 129 students was drawn from 190 Grade VI students across 12 elementary schools. Data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.0. The measurement model confirmed satisfactory convergent validity (all AVE > 0.50), discriminant validity (Fornell–Larcker criterion), and composite reliability (all CR > 0.90). The structural model yielded R² = 0.784, indicating that the three variables jointly explain 78.4% of the variance in learning outcomes (GoF = 0.752, very high). All four hypotheses were accepted: AI-Deep Learning (β = 0.324, t = 4.872, p < 0.05), Digital Literacy (β = 0.287, t = 4.215, p < 0.05), Learning Independence (β = 0.412, t = 6.134, p < 0.05), and their simultaneous effect (F = 124.567, p < 0.05). Learning independence emerged as the dominant predictor (f² = 0.892). These findings advocate for an integrated digital-autonomous learning ecosystem as a systemic response to persistent IPAS underachievement in Indonesian elementary schools.

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