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All Journal International Journal Education and Computer Studies International Journal of Science and Society (IJSOC) Journal of Mathematics Instruction, Social Research and Opinion Journal of Artificial Intelligence and Digital Business TOFEDU: The Future of Education Journal Journal Mobile Technologies (JMS) Dauliyah Journal of Islamic and International Affairs
Muhammad Gibran Alif Prasetya
Universitas Negeri Semarang
Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Social Sciences Other

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A Systematic Review of Artificial Intelligence-Based Computer Adaptive Testing (CAT) and Item Response Theory for Enhancing the Effectiveness of Science Learning Assessment Prasetya, Muhammad Gibran Alif; Widiyatmoko, Arif; Rusilowati, Ani
International Journal of Science and Society Vol 7 No 4 (2025): International Journal of Science and Society (IJSOC)
Publisher : GoAcademica Research & Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54783/ijsoc.v7i4.1581

Abstract

The advancement of technology has accelerated the adoption of Computerized Adaptive Testing (CAT) in educational assessment due to its ability to dynamically adjust item difficulty levels, thereby producing more precise, efficient, and valid measurements compared to conventional tests. While Item Response Theory (IRT) serves as the primary psychometric foundation of CAT, traditional IRT implementation faces computational challenges because ability estimation requires lengthy iterative processes, resulting in reduced system responsiveness. To address this issue, Artificial Intelligence (AI), particularly Fuzzy Logic, offers a promising solution through rapid inference mechanisms and monotonic reasoning that can adaptively map students’ cognitive abilities to corresponding item difficulty levels. This study aims to develop a hybrid CAT system that integrates Fuzzy Logic for fast inference with IRT as a robust and valid psychometric framework in the context of science learning. The research employs a systematic literature review using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, encompassing the stages of Identification, Screening, and Inclusion of relevant studies. The findings indicate that the integration of AI/ML with IRT in CAT consistently enhances assessment accuracy and efficiency. Algorithms such as Maximum Information (MI) and Expected a Posteriori (EAP) effectively reduce test length without compromising reliability, while Fast Adaptive Cognitive Diagnosis (FACD) improves early-stage ability prediction. Furthermore, Fuzzy Logic demonstrates strong effectiveness in selecting adaptive test items aligned with students’ ability levels. The study concludes that developing CAT systems based on AI and IRT yields adaptive, personalized, efficient, and diagnostic evaluation mechanisms that support personalized science learning.
Systematic Literature Review on the Integration and Role of Artificial Intelligence in the Development of Computer Adaptive Testing (CAT) Prasetya, Muhammad Gibran Alif; Widiyatmoko, Arif
The Future of Education Journal Vol 4 No 9 (2025): #1
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Yayasan Pendidikan Tumpuan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61445/tofedu.v4i9.1331

Abstract

The integration of Artificial Intelligence (AI) has sparked a fundamental transformation in assessment systems, shifting from static methods to dynamic and personalized paradigms through Computer Adaptive Testing (CAT). This study aims to map the state-of-the-art AI integration in CAT, identify technological evolution trends, and analyze the contributions of dominant algorithms in optimizing the core components of tests. A Systematic Literature Review (SLR) following the PRISMA guidelines was used to synthesize data from Scopus, WoS, IEEE, ERIC, and Google Scholar databases from 2020 to 2025. Macro analysis was performed with VOSviewer, and micro synthesis with NVivo. The results indicate an evolution trend from basic machine learning integration in 2020 towards automation systems based on Reinforcement Learning and Generative AI by 2025. Algorithms such as Deep Learning and Multi-Objective Optimization have been shown to improve the precision of ability estimation, while empirical findings demonstrate that the use of Model Trees (M5P) can reduce item counts by 85%–93% on clinical instruments without compromising score accuracy. In conclusion, AI is transforming CAT into a smart, efficient, and personalized assessment ecosystem, with challenges in transparency (explainability) and algorithmic bias as key priorities for the future development of evaluation systems.
Comprehensive Analysis of the Role of Mobile Application Gamification in Science Education for Motivation and Knowledge Retention Prasetya, Muhammad Gibran Alif; Yasin, Ahmad Alfian Risydan
Journal Mobile Technologies (JMS) Vol. 4 No. 1 (2026): February
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/jms.v4i1.709

Abstract

Low student motivation and knowledge retention in abstract science concepts remain significant challenges in modern science education. This study aims to comprehensively analyze the role of mobile application gamification in enhancing student engagement and strengthening long-term memory. The method employed is a Systematic Literature Review (SLR) following the PRISMA 2020 protocol, involving a rigorous selection of 10 reputable international journal articles (Scopus Q1-Q4) published between 2020 and 2026. Findings indicate that competitive elements, such as leaderboards, significantly trigger intrinsic motivation, while interactive visualizations through AR and simulations effectively improve knowledge retention by simplifying complex cognitive concepts. Despite a identified research gap regarding long-term sustainability in resource-limited environments, this study concludes that a balanced integration of visual aesthetics and pedagogical depth fosters sustainable mastery of science concepts. These results provide strategic contributions for educators in designing evidence-based, inclusive, and adaptive learning media.
The Analysis Needs Mapping for the Development of an Artificial Intelligence-Item Response Theory (AI-IRT)-Based CAT Web System for Adaptive Science Assessment Muhammad Gibran Alif Prasetya; Arif Widiyatmoko; Sudarmin Sudarmin; Novi Ratna Dewi
Journal of Mathematics Instruction, Social Research and Opinion Vol. 5 No. 1 (2026): March
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v5i1.1256

Abstract

Assessment of science learning outcomes in junior high school science education is still largely dominated by conventional tests that do not adequately accommodate differences in students’ abilities and provide limited diagnostic feedback. This limitation highlights the need for a more adaptive and data-driven assessment system. This study aims to map the needs for developing a web-based Computerized Adaptive Test (CAT) system integrating Artificial Intelligence and Item Response Theory (AI-IRT) for science assessment at the junior high school level. The study employed a descriptive qualitative approach at the Analysis stage of the ADDIE development model. Data were collected through semi-structured interviews with one junior high school science teacher and five students, and analyzed using NVivo through open coding, axial coding, and selective coding. The findings reveal six key needs: adaptive assessment systems, measurement fairness and precision, diagnostic feedback, efficiency and automation, infrastructure readiness, and user-friendly interface design. These findings demonstrate the potential of integrating AI and IRT to support more accurate, personalized, and efficient science assessment. The results provide a conceptual and operational foundation for developing an AI-IRT-based CAT web system tailored to junior high school science learning.
Conceptual Model of Computer Utilization in 21st Century Science Learning: Grounded Theory-Informed Literature Review Lathif, Yuniar Fahmi; Prasetya, Muhammad Gibran Alif; Yasin, Ahmad Alfian Risydan
International Journal Education and Computer Studies (IJECS) Vol. 6 No. 1 (2026): MARCH
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijecs.v6i1.6410

Abstract

The use of computers in science education continues to be dominated by technocentric approaches that treat technology as an end in itself rather than a means of learning. This research aims to deconstruct prevailing research trends and construct a new conceptual model explaining how computers can be used effectively in 21st-century science learning. Using a Systematic Literature Review (SLR) design with the PRISMA 2020 protocol, this study selects and analyzes high-quality articles from reputable databases. Data analysis followed a Grounded Theory-Informed approach to extract recurring patterns and build theoretical propositions inductively. Three fundamental dimensions emerged to form the new conceptual model: (1) Teacher Agency and Ecosystem Readiness as determinant input variables that precede hardware availability; (2) Hybrid Pedagogy and Distributed Scaffolding as the core process mechanism that bridges physical and digital learning experiences; and (3) Methodological Adaptability as a moderator variable that adjusts instructional strategies to the complexity level of the subject matter. This study concludes that technology effectiveness is not deterministic — it depends on an adaptive pedagogical ecosystem built around teacher capacity and contextual design. These findings carry strategic implications for curriculum developers and policymakers: prioritize discipline-specific teacher professional development, and design learning environments that pair virtual simulations with real-world experiments.
Dari Alat Teknis ke Mitra Belajar: Studi Literatur tentang Transformasi Peran Artificial Intelligence dalam Pembelajaran di Kelas Muhammad Gibran Alif Prasetya
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 2 (2026): Mei-Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i2.8702

Abstract

Integrasi Kecerdasan Buatan (AI) dalam pendidikan telah mengalami pergeseran paradigma yang signifikan seiring pesatnya inovasi teknologi mutakhir. Penelitian Systematic Literature Review (SLR) ini bertujuan untuk memetakan dan menganalisis secara kritis evolusi peran AI, dari sekadar alat otomasi administratif menjadi mitra belajar kognitif dalam ekosistem pembelajaran di kelas. Penelitian ini menerapkan metode tinjauan literatur sistematis dengan pendekatan deskriptif-kualitatif. Sumber data difokuskan pada penelusuran 12 artikel jurnal internasional bereputasi yang terindeks Scopus, diterbitkan pada rentang tahun 2020 hingga 2025. Kriteria inklusi secara ketat mencakup studi empiris maupun konseptual yang mengeksplorasi interaksi pedagogis human-AI dan adopsi AI di ruang kelas. Melalui teknik analisis tematik, hasil sintesis menunjukkan adanya lintasan transformasi peran AI yang berjenjang. Pada mulanya, AI difungsikan secara terbatas sebagai alat bantu teknis untuk otomasi tugas administratif dan sistem asesmen objektif. Seiring waktu, fungsi tersebut berkembang menjadikan AI sebagai asisten pengajaran dan tutor cerdas yang adaptif. Pada perkembangannya saat ini, kemunculan model AI generatif telah mentransformasi AI menjadi mitra belajar kolaboratif. Dalam kapasitas ini, AI proaktif mendukung personalisasi pembelajaran secara mendalam, memfasilitasi dialog diskursif tingkat tinggi, serta memberikan scaffolding yang dinamis guna membangun kemandirian peserta didik. Sebagai simpulan, AI tidak lagi bertindak sebagai instrumen pasif, melainkan telah berevolusi menjadi agen pedagogis interaktif. Tinjauan ini memberikan implikasi bahwa pendidik dituntut untuk mengkalibrasi ulang strategi instruksional guna memaksimalkan potensi AI sebagai kolaborator esensial yang bermakna.
Digital Transnational Salafi Da'wah and Indonesia’s Hijrah Movement: An International Relations Perspective Muhammad Gibran Alif Prasetya
Dauliyah Journal of Islamic and International Affairs Vol. 11 No. 1 (2026): Dauliyah Journal of Islamic and International Affairs
Publisher : UNIDA Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/dauliyah.v11i1.12

Abstract

The phenomenon of the Hijrah movement among the Indonesian Muslim middle class marks a shift in religious authority towards transnational Salafism which is massively facilitated by digital technology. This study aims to analyze the strategic role of social media in facilitating da'wah transnationalism and measure its determinants of migration decisions in the perspective of International Relations. This study applies a mixed-methods design with a concurrent embedded strategy. Data was collected through an online survey of 100 respondents participating in the Hijrah movement and digital content analysis. Quantitative analysis used Multiple Linear Regression to test the influence of access duration, frequency of interaction, and content preferences, while qualitative data was used to validate ideological narratives. The results of the study showed that social media activities had a significant positive influence on the decision to emigrate with a determination coefficient of 66.5%. Specifically, the frequency of participatory interaction and exposure to transnational ideological narratives were the strongest predictors, outperforming demographic factors. This study concludes that social media functions effectively as an instrument of "digital public diplomacy" for non-state actors in diffusing the norm of "Global Solidarity of Ummah" that transcends the boundaries of nation-states. These findings provide theoretical contributions regarding the digital soft power mechanisms of non-state actors and practical implications for policymakers in formulating critical digital literacy strategies to maintain the stability of national integration.  
Co-Authors Ani Rusilowati Arif Widiyatmoko, Arif Dewi, Novi Ratna Sudarmin Sudarmin Yasin, Ahmad Alfian Risydan Yuniar Fahmi Lathif