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p-Index From 2021 - 2026
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All Journal Indonesian Journal of Applied Science and Engineering
Aisha Juma Mussa
The Open University of Tanzania

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Mapping the Evolution of Educational Evaluation and E-Learning Research in Indonesia Post-COVID-19: A Bibliometric Analysis (2020–2024) Asma Khoirunnisa; Heri Retnawati; Risky Setiawan; Samsul Hadi; Auliasari Marjan; Sitti Aminah; Hanifah Mar'atush Shalihah; Israel Amatepey; Aisha Juma Mussa; Alaa Abdelkader
Indonesian Journal of Applied Science and Engineering Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v4i1.154

Abstract

The rapid shift to online and technology-mediated learning during the COVID-19 pandemic significantly transformed Indonesia’s educational practices and intensified attention to how learning processes and outcomes are evaluated. This study maps the evolution of educational evaluation and e-learning research in Indonesia after the pandemic by examining publication trends, thematic patterns, and intellectual structures from 2020 to 2024. A total of 133 publications published between 2020 and 2024 were retrieved from Scopus using a structured search query construction procedure and analyzed through Biblioshiny. The analysis included annual scientific production, average citation trends, cumulative growth modelling, keyword co-occurrence mapping, thematic mapping, and conceptual structure analysis. Data quality was strengthened through duplicate checking, keyword standardization, metadata consistency checks, and verification of Indonesian institutional affiliations. The findings reveal five major clusters: e-learning as a central theme connecting evaluation and digital pedagogy; learning assessment and student performance; educational technology and AI-supported learning tools; learning systems and platform-based instructional models; and emerging topics such as digital literacy, local wisdom, metaverse-related learning, and instrument development. These results indicate a post-pandemic shift toward technology-supported evaluation practices while also exposing gaps in validated digital assessment instruments, longitudinal evaluation, AI-integrated assessment frameworks, and equity-sensitive studies across diverse Indonesian educational contexts.
Questioning “Boy Math” and “Girl Math”: A Measurement-Based Test of Gendered Financial Behaviour Profiles Among Indonesian Students Asma Khoirunnisa; Heri Retnawati; Risky Setiawan; Samsul Hadi; Hanifah Mar'atush Shalihah; Zhansaya K. Markhmadova; Alaa Abdelkader; Aisha Juma Mussa
Indonesian Journal of Applied Science and Engineering Vol. 3 No. 2 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v3i2.168

Abstract

The popular phrases “Boy Math” and “Girl Math” have transformed humorous spending explanations into a wider discussion about gender and money. This study uses the discourse as a cultural entry point rather than as a construct directly measured by PISA 2018, which predates the trend and does not assess meme-specific post-hoc spending rationalisations. Using complete-case data from 5,833 Indonesian students, the study examined financial autonomy, careful price behaviour, bank confidence, digital confidence, financial behaviour, and financial attitude through ordinal confirmatory factor analysis, gender measurement invariance, latent factor scores, k-means clustering, and a secondary Random Forest diagnostic. The measurement model showed acceptable fit (CFI = 0.992, TLI = 0.991, RMSEA = 0.063, SRMR = 0.059), and invariance was supported up to the strict level. The two-cluster solution separated students consistently across all six dimensions, indicating higher and lower financial engagement levels rather than qualitatively distinct reasoning styles. The unadjusted association between gender and cluster membership was not significant, χ²(1) = 2.135, p = 0.144, Cramer’s V = 0.019. In adjusted logistic regression using conventional standard errors, male students had slightly lower odds of belonging to the higher-engagement group after grade was controlled (OR = 0.864, p = 0.006). School-clustered standard errors were not reported in the supplied output, so the adjusted inferential result remains provisional. Given the gender-balanced profiles, negligible unadjusted effect size, and odds ratio close to one, the relationship is substantively small. Random Forest reconstructed the internally generated cluster labels with 97.27% out-of-bag accuracy; this represents classification fidelity rather than external predictive validity. The findings do not support treating “Boy Math” and “Girl Math” as clear empirical gender categories.
Co-Authors Alaa Abdelkader Asma Khoirunnisa Auliasari Marjan Hanifah Mar'atush Shalihah Heri Retnawati Israel Amatepey Risky Setiawan SAMSUL HADI Sitti Aminah Zhansaya K. Markhmadova