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Endang Supiani
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PERSEPSI DOSEN TERHADAP PEMANFAATAN CHATGPT SEBAGAI ASISTEN AKADEMIK DALAM MENDUKUNG PEMBELAJARAN BERBASIS OUTCOME-BASED LEARNING (OBE) Aeni Latifah; Dede Ridwan; Eki Agustin; Amelia Putri; Endang Supiani
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 01 (2026): Volume 11 No. 01, Maret 2026 Release
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i01.41439

Abstract

The digital era has brought a significant transformation to higher education through the integration of artificial intelligence (AI) technologies as instructional support tools. ChatGPT is a generative AI application with the potential to support the implementation of Outcome-Based Learning (OBE), a learning model that emphasizes the achievement of competencies and measurable learning outcomes. This study aims to examine lecturers’ perceptions of the utilization of ChatGPT as an academic assistant in the context of OBE implementation in higher education institutions. The study is conducted through a literature review of empirical studies and contemporary analyses addressing the accelerated adoption of AI in education. The findings indicate that lecturers’ perceptions tend to be diverse; while many lecturers acknowledge the potential benefits of ChatGPT in enhancing the efficiency of instructional material development and providing formative learning support, concerns remain regarding academic integrity and pedagogical readiness for the effective use of this technology. Keywords: ChatGPT, Lecturers’ Perceptions, Outcome-Based Learning, Academic Assistant, Artificial Intelligence.
MANAJEMEN PEMBELAJARAN BERBASIS DATA DAN KECERDASAN BUATAN DALAM MENDUKUNG OUTCOME-BASED EDUCATION DI PERGURUAN TINGGI Aeni Latifah; Yulistiana; Amelia Putri; Linda Hindriana; Endang Supiani
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 01 (2026): Volume 11 No. 01, Maret 2026 Release
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i01.41444

Abstract

This study examines data-driven and artificial intelligence (AI)–based learning management as a strategic approach to supporting Outcome-Based Education (OBE) in higher education. The main problem addressed is the limited ability of conventional learning management practices to systematically monitor, evaluate, and improve student learning outcomes in alignment with OBE principles. The purpose of this research is to analyze how the integration of data analytics and AI can enhance planning, implementation, monitoring, and evaluation of learning processes to ensure the achievement of intended learning outcomes. This study employs a qualitative descriptive approach through literature review and analysis of relevant models and practices of data-driven learning management and AI applications in higher education. The findings indicate that data-driven learning management supported by AI enables more accurate measurement of student performance, personalized learning pathways, early identification of learning difficulties, and evidence-based decision-making for continuous improvement. Furthermore, AI-based systems contribute to adaptive feedback, predictive analytics, and automated assessment, which strengthen the alignment between learning activities, assessment, and expected outcomes. The study concludes that the adoption of data-driven and AI-enabled learning management plays a significant role in reinforcing the effectiveness and sustainability of Outcome-Based Education in higher education institutions.
Co-Authors Aeni Latifah Amelia Putri Dede Ridwan Eki Agustin linda hindriana Yulistiana