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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Penelitian Pendidikan IPA (JPPIPA) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Minda Baharu Ideguru: Jurnal Karya Ilmiah Guru Jurnal Pengabdian Ibnu Sina PPSDP International Journal of Education JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi
Edi, Firman
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Artificial Intelligence as a Science Teacher Assistant: An Analysis of Machine Learning Utilization in Diagnosing Student Misconceptions: A Review Purnama, Iwan; Wijaya, Rian Farta; Harahap, Aziddin; Edi, Firman
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.13089

Abstract

Diagnosing these misconceptions in a crowded classroom context is very difficult, time-consuming, and subjective when using conventional methods, which often leads to ineffective teaching interventions. To address the urgent need for accurate and objective diagnosis, this article proposes and analyzes the role of Artificial Intelligence (AI), specifically Machine Learning (ML) technologies such as natural language processing (NLP). ML models can analyze student response data (essays) quickly and consistently, acting as science teacher assistants to strengthen diagnostic capabilities. This study uses a systematic literature review method to analyze and synthesize existing research findings regarding Artificial Intelligence as a Science Teacher's Assistant: An Analysis of the Utilization of Machine Learning in Diagnosing Student Misconceptions. This research aims to analyze and explain Artificial Intelligence as a Science Teacher's Assistant: An Analysis of the Utilization of Machine Learning in Diagnosing Student Misconceptions. The brief objectives of this study are as follows: to analyze the utilization of Machine Learning (ML) models in objectively diagnosing, categorizing, and predicting students' misconceptions in science. The findings of this review study indicate that student misconceptions are a persistent barrier to learning, and conventional (manual, paper-based) diagnostic methods have proven inefficient and subjective for crowded classrooms. This validates the urgent need for technological solutions.
Co-Authors Agustin, Risnawati Alwin Fau Andri, Ronny Ansarullah Lawi Desi, Efani Dona Budi Kharisma, Dona Budi Harahap, Aziddin Hondro, Rivalry Kristianto Hts, Dedek Indra Gunawan Indriani, Ulfa Indriani, Ulfah Iwan Purnama M. Ansyar Bora Megahati S, Ruth Rize Paas Muhammad Fachrurrozi Nasution munir, Zainul Munir nasution, fitri pranita Nuridin Widya Pranoto Nurul Anriani Oktawanto, Rian Ririt Dwiputri Permatasari S, Ruth Rize Paas Megahati Siregar, Sri Wahyuni Siti Aliyah Sondra Wijaya, I Made Sudadio Sudadio Sudirman Sudirman Syahrul Tambunan, Frinto Tiok Wijanarko Wijaya, Rian Farta