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Hesti Putri
Department of Informatics Science, CMHC Research Center, Palembang, Indonesia

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Frugal Innovation in Education: Designing and Evaluating Low-Bandwidth, Asynchronous Learning Systems for Remote Indonesian Schools Hesti Putri; Maya Enderson; Jasmila Tanjung; Matilda Munoz; Sarah Armalia; Jovanka Andina; Kevin Setiawan; Sudarto Sudarto; Khalil Jibran; Jasmine Alieva
Enigma in Education Vol. 3 No. 1 (2025): Enigma in Education
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/edu.v3i1.95

Abstract

The promise of educational technology (EdTech) to democratize learning in Indonesia is consistently undermined by a profound digital divide, particularly in remote and archipelagic regions where internet connectivity is poor and infrastructure is limited. This study explores the application of frugal innovation principles as a direct and context-aware strategy to address this challenge. A multi-phase, mixed-methods Design-Based Research (DBR) methodology was employed over 18 months. The study involved the collaborative design, development, and implementation of "Lentera," a low-bandwidth, asynchronous, and offline-first learning system, in six remote primary schools in the Maluku Islands. A quasi-experimental design compared three intervention schools with three control schools over one academic year. Data collection was extensive, including pre- and post-intervention literacy and numeracy assessments, System Usability Scale (SUS) surveys, system usage logs, semi-structured interviews with 18 teachers, and over 80 hours of classroom observation. Data were analyzed using a two-level Hierarchical Linear Model (HLM) to account for the clustered nature of students within schools. The Lentera system demonstrated high feasibility and positive user adoption, with offline peer-to-peer sharing proving to be a critical feature for content distribution. Quantitative analysis revealed a statistically significant and substantial improvement in learning outcomes for the intervention group in both literacy (γ = 11.85, p < 0.001) and numeracy (γ = 12.91, p < 0.001) compared to the control group, after controlling for pre-test scores. The mean System Usability Scale (SUS) score was 78.5, indicating well-above-average usability. Qualitative findings, drawn from a wide range of teacher interviews and classroom observations, highlighted the system's effectiveness in supporting student-centered, differentiated instruction and fostering teacher collaboration, aligning with the core principles of Indonesia's Kurikulum Merdeka. The study provides compelling evidence that frugal innovation, embodied in a context-aware learning system, presents a viable, effective, and scalable pathway to enhancing educational quality and equity in resource-constrained environments.
Evaluating Generative AI as a Pedagogical Tool for Creative Problem-Solving in University Classrooms Hesti Putri; Khalil Jibran
Enigma in Education Vol. 3 No. 2 (2025): Enigma in Education
Publisher : Enigma Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61996/edu.v3i2.117

Abstract

This study investigated the effectiveness of generative artificial intelligence (AI) as a pedagogical tool for enhancing creative problem-solving (CPS) skills and divergent thinking (DT) among undergraduate students. A quasi-experimental pretest-posttest control group design was employed with 120 education students at a private university in Palembang, Indonesia. Participants were assigned to an experimental group (n = 60) that engaged in a 12-week AI-assisted learning intervention within an Educational Psychology course, and a control group (n = 60) receiving conventional instruction. Creative problem-solving was measured using the Creative Problem-Solving Performance Inventory (CPSPI, α = 0.89), while divergent thinking was assessed through an adapted Torrance Tests of Creative Thinking (TTCT, ICC = 0.91). Results from mixed ANOVA revealed a significant interaction effect for CPS, F(1,118) = 89.34, p < .001, partial η² = 0.431. MANOVA confirmed significant multivariate differences across all outcome measures, Pillai’s V = 0.482, F(5,114) = 21.24, p < .001. Large effect sizes were observed for CPS (Hedges’ g = 1.66) and DT (Hedges’ g = 1.18). These findings suggest that structured integration of generative AI into university pedagogy can substantially improve students’ creative problem-solving and divergent thinking capacities.