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All Journal Jurnal Da'wah: Risalah Merintis, Da'wah Melanjutkan Journal of Educational Technology and Learning Creativity Journal of Informatics and Vocational Education
Muhamad Akda Fathul Barri
Universitas Pendidikan Indonesia
Religion Computer Science & IT Education Social Sciences

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FENOMENA KONSUMSI KONTEN DAKWAH DIGITAL PADA KALANGAN MAHASISWA: SYSTEMATIC LITERATURE REVIEW Muhamad Akda Fathul Barri; Fikriansyah Haikal Ramadhan; Muhammad Ariestama Putra; Daniel Satresna; Hisny Fajrussalam
Jurnal Da'wah: Risalah Merintis, Da'wah Melanjutkan Vol. 8 No. 1 (2025): Jurnal Da'wah: Risalah Merintis, Da'wah Melanjutkan
Publisher : Program Studi Komunikasi Penyiaran Islam STID Mohammad Natsir

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38214/jurnaldawahstidnatsir.v8i1.332

Abstract

Perkembangan teknologi digital telah mengubah cara penyebaran dan konsumsi konten dakwah Islam di kalangan generasi muda, khususnya mahasiswa. Penelitian ini bertujuan untuk menganalisis fenomena konsumsi konten dakwah digital di kalangan mahasiswa melalui pendekatan Systematic Literature Review (SLR). Dengan mengikuti pedoman PRISMA, penelitian ini mengidentifikasi, menyaring, dan menganalisis 9 artikel ilmiah yang relevan dengan topik konsumsi konten dakwah digital di kalangan mahasiswa. Hasil penelitian menunjukkan bahwa media sosial menjadi platform utama dalam konsumsi konten dakwah digital oleh mahasiswa, dengan preferensi terhadap konten yang singkat, visual, dan interaktif. Faktor-faktor yang memengaruhi pola konsumsi konten dakwah digital antara lain kredibilitas dai digital, relevansi konten dengan kehidupan mahasiswa, dan kemudahan akses. Sementara itu, dampak positif konsumsi konten dakwah digital meliputi peningkatan literasi keagamaan, pembentukan identitas Muslim, dan penguatan pemahaman nilai-nilai keislaman. Namun, terdapat juga tantangan berupa potensi paparan konten ekstremisme, polarisasi pandangan keagamaan, dan kurangnya verifikasi sumber. Untuk mengoptimalkan pemanfaatan dakwah digital, diperlukan pendekatan literasi digital keagamaan yang lebih komprehensif bagi mahasiswa, peningkatan kualitas konten dakwah digital, serta kolaborasi antara institusi pendidikan, organisasi keagamaan, dan platform digital. Dengan strategi yang tepat, konten dakwah digital dapat menjadi instrumen efektif dalam penguatan pemahaman dan pengamalan nilai-nilai keislaman di kalangan mahasiswa.
Human–GenAI Score Alignment in Rubric-Constrained Essay Assessment: Procedural Convergence Without Pedagogical Equivalence Muhamad Akda Fathul Barri; Rizki Hikmawan
Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i2.3338

Abstract

The increasing availability of Generative Artificial Intelligence (GenAI) systems has raised critical questions regarding their role in educational assessment, particularly in evaluating open-ended student responses that traditionally rely on professional teacher judgment. This study investigates the extent to which GenAI-generated scores align with teacher assessments when both are guided by an explicit and standardized rubric framework. Using a parallel scoring design, written responses from junior secondary school students were independently evaluated by an Informatics teacher and a GenAI system (ChatGPT) based on an identical rubric encompassing progressively increasing cognitive demands from lower-order to higher-order thinking skills. To examine scoring alignment, an Intraclass Correlation Coefficient (ICC) analysis with a two-way mixed-effects model and absolute agreement approach was employed. The results indicate a meaningful level of score alignment between teacher and GenAI assessments, suggesting that GenAI can apply rubric-based evaluative criteria in a procedurally consistent manner. However, qualitative analysis of written feedback reveals substantive differences in pedagogical depth. While GenAI feedback demonstrates high structural consistency and transparent rubric justification, teacher feedback exhibits greater contextual sensitivity, incorporating instructional intent, student misconceptions, and classroom dynamics. These findings suggest that GenAI systems hold potential as assessment support tools capable of enhancing scoring consistency and efficiency in formative assessment contexts. Nevertheless, score alignment should not be interpreted as pedagogical equivalence. The study concludes that GenAI is best positioned as an augmentative decision-support system operating under teacher supervision, rather than as an autonomous assessor. This research contributes empirical evidence to ongoing discussions on Human–AI score alignment and highlights the critical role of rubric design in mediating responsible GenAI integration within educational assessment practices.
Integrating Artificial Intelligence and Science Education to Support Computational Thinking: A Multi-Model Benchmarking Study in Primary Numeracy Suprih Widodo; Muhamad Akda Fathul Barri; Ayu Permata Sari; Hapizah Hapizah; Intan Sari Rufiana; Sumarni Sumarni; Zuriani Mustaffa
Journal of Educational Technology and Learning Creativity Vol. 4 No. 1 (2026): June
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jetlc.v4i1.3397

Abstract

Purpose of the study: This study investigates the multidisciplinary integration of artificial intelligence, learning analytics, cognitive psychology, and science education to evaluate three Large Language Model (LLM) configurations. It aims to optimize an adaptive digital scaffolding framework for primary computational thinking (CT) and scientific reasoning under tight latency constraints. Methodology: Deployed via Python 3.11 within an automated benchmarking ecosystem, OpenAI gpt-5-mini, Google gemini-3.5-flash, and Meta llama-3.3-70b-versatile (Groq LPU) were evaluated across 15 Bebras tasks (135 structured API interactions). The multidisciplinary validation applied content and psycholinguistic triage to analyze the interface between technical inference latency and the continuity of students' scientific inquiry processes. Main Findings: Meta Llama-3.3-70b achieved optimal performance with a 0.2687s latency, maximizing the Student Waiting Threshold (SWT) compliance margin to support uninterrupted scientific schema construction. OpenAI GPT-5 Mini exhibited superior Socratic instruction adherence (6.9% failure) but introduced a 2.3764s latency overhead. Gemini 3.5 Flash truncated crucial pedagogical contexts due to its constrained 3-token output distribution. Novelty/Originality of this study: This work introduces a multidisciplinary engineering blueprint that bridges hardware-level computing optimization with technology-enhanced science education. By formalizing a latency-constrained routing protocol, it establishes a theoretical model demonstrating how infrastructure responsiveness directly safeguards the cognitive sustainability of scientific reasoning and problem-solving sequences in primary STEM learning contexts.
Co-Authors Ayu Permata Sari Daniel Satresna Fikriansyah Haikal Ramadhan Hapizah Hikmawan, Rizki Hisny Fajrussalam Intan Sari Rufiana Muhammad Ariestama Putra Sumarni Sumarni Zuriani Mustaffa