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Abstrak
Penelitian tentang kecerdasan buatan (AI) dalam pendidikan telah berkembang dengan kecepatan yang belum pernah terjadi sebelumnya, namun perkembangannya tetap terfragmentasi, didorong oleh sensasi, dan tersebar secara tidak merata di berbagai disiplin ilmu dan wilayah. Makalah ini menyajikan salah satu pemetaan paling komprehensif hingga saat ini, dengan menganalisis 16.564 publikasi (1990–2025) yang diidentifikasi melalui Web of Science dan disaring menjadi 4.626 kontribusi inti menggunakan metode hibrida yang menggabungkan pemodelan topik komputasional, penyaringan berbantuan AI, dan validasi manusia. Untuk melengkapi pemetaan tingkat makro ini, kami melakukan tinjauan kualitatif terhadap makalah-makalah yang paling sering dikutip dalam setiap topik penelitian utama, memberikan kedalaman interpretatif mengenai bagaimana karya-karya berpengaruh tersebut telah membentuk perdebatan seputar adopsi, keterlibatan, personalisasi, chatbot, evaluasi, risiko, pemantauan, tinjauan, dan pengajaran AI. Temuan ini mengungkapkan pertumbuhan eksponensial sejak tahun 2020, dengan lonjakan besar selama pandemi COVID-19 dan setelah peluncuran ChatGPT, namun juga menunjukkan fragmentasi yang terus berlanjut, penurunan studi evaluasi, serta kejenuhan survei sikap. Bidang-bidang yang menjanjikan seperti personalisasi, pengajaran AI, dan keterlibatan telah kehilangan visibilitas meskipun memiliki pentingnya jangka panjang, sementara risiko dan isu etika tetap kurang dieksplorasi dan kurang terhubung dengan penelitian teknis. Pola kutipan juga menunjukkan ketidakseimbangan sistemik, di mana makalah pendidikan dikutip secara tidak proporsional sementara hasil penelitian teknik kurang diakui. Kami menyimpulkan dengan rekomendasi untuk memperkuat interdisipliner, menangani bidang-bidang yang terabaikan, memasukkan perspektif historis, serta mengatasi tantangan sistemik guna mendorong bidang yang lebih kumulatif, integratif, dan kritis.
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Author Contributions
Constance de Saint Laurent: Conceptualization; Methodology; Investigation; Data Collection; Data Curation; Writing – Original Draft Preparation. Vlad Glaveanu: Theoretical Framework Development; Writing – Review & Editing. Ioana Literat: Theoretical Framework Development; Writing – Review & Editing. Ingunn Ness: Theoretical Framework Development; Writing – Review & Editing. All authors have read and approved the final version of the manuscript. All authors have read and approved the final version of the manuscript.
Acknowledgments
The authors would like to thank Natalie Robinson for her help formatting the final version of the paper.
View statement in PDF · PDF page 22Ethics Approval
This study was conducted in accordance with ethical standards.
View statement in PDF · PDF page 22Informed Consent
The study did not involve collecting empirical data from human participants.
View statement in PDF · PDF page 22Funding
The authors declare that this research did not receive specific funding from any public, commercial, or not-for-profit agencies.
View statement in PDF · PDF page 22Data Availability
The data supporting this study’s findings are not publicly available. Summary data are included in the manuscript, and more detailed information can be requested from the corresponding author under strict confidentiality agreements.
View statement in PDF · PDF page 22Competing Interests
The authors declare that they have no competing interests related to the content of this article.
View statement in PDF · PDF page 22Generative AI Disclosure
During the preparation of this manuscript, the authors used AI (ChatGPT 4.0) to assist as part of the methodology of summarizing data, as explained in the manuscript. Whenever AI was used, the authors carefully reviewed and edited the content to ensure accuracy and integrity, and they take full responsibility for the published work.
View statement in PDF · PDF page 22Referensi
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Hak Cipta (c) 2026 Constance de Saint Laurent, Vlad Glaveanu, Ioana Literat, Ingunn Ness