Implementasi Artificial Intelligence (AI) dalam Penilaian Formatif: Studi Literatur tentang Peningkatan Akurasi Evaluasi Pembelajaran

Authors

  • Dewi Agustina Solihin Politeknik PGRI Banten
  • Heny Fitriani Politeknik PGRI Banten
  • R. Dewi Mutia Farida Politeknik PGRI Banten
  • Ahmad Sofan Ansor Politeknik PGRI Banten
  • Rosdiana Politeknik PGRI Banten

DOI:

https://doi.org/10.31004/joecy.v6i1.8536

Keywords:

Artificial intelligence, Penilaian formatif, Automated feedback, Akurasi evaluasi, Systematic literature review (SLR)

Abstract

Penelitian ini bertujuan mensintesis bukti ilmiah mengenai implementasi Artificial Intelligence (AI) dalam penilaian formatif dan kontribusinya terhadap peningkatan akurasi evaluasi pembelajaran. Metode yang digunakan adalah studi literatur dengan desain Systematic Literature Review (SLR) pada rentang publikasi 2015–2025. Proses seleksi mengikuti tahapan identifikasi, penyaringan, penilaian kelayakan, dan inklusi, dengan fokus pada studi yang membahas AI untuk penilaian formatif serta menyertakan bukti kualitas evaluasi seperti validitas, reliabilitas/konsistensi, agreement AI–penilai manusia, dan/atau kegunaan umpan balik. Sintesis kualitatif dilakukan terhadap 10 studi kunci yang merepresentasikan spektrum implementasi, termasuk automated writing evaluation/automated essay scoring, intelligent tutoring system, pendekatan deep learning, serta large language models untuk umpan balik dan penilaian. Hasil menunjukkan bahwa AI dapat meningkatkan akurasi evaluasi melalui: (1) penguatan validitas ketika output AI selaras dengan konstruk dan rubrik, (2) peningkatan konsistensi penilaian serta efisiensi pemberian umpan balik, dan (3) dukungan diagnosis kesalahan yang membantu tindakan perbaikan belajar. Namun, efektivitas AI sangat dipengaruhi moderator implementasi, terutama kejelasan rubrik, desain siklus revisi, kualitas dan representativitas data, literasi umpan balik siswa, serta peran guru dalam human-in-the-loop. Studi juga menyoroti risiko yang dapat menurunkan akurasi, seperti bias/fairness, rendahnya transparansi, overreliance, dan isu tata kelola data. Kesimpulannya, AI paling efektif meningkatkan akurasi evaluasi pembelajaran bila diterapkan sebagai pendukung asesmen formatif yang terintegrasi pedagogis dan dikendalikan melalui verifikasi guru serta standar evaluasi yang jelas.

References

Chen, J., et al. (2021). Interactive test dashboard: A tool supporting reliable and diagnostic

computer-based formative assessments. Computers and Education: Artificial Intelligence, 2, 100015. https://doi.org/10.1016/j.caeai.2021.100015 (ScienceDirect)

Correnti, R., et al. (2022). Building a validity argument for an automated writing evaluation system

designed to provide formative feedback to students. Computers and Education Open, 3, 100084. https://doi.org/10.1016/j.caeo.2022.100084

Deeva, E., Bogdanova, D., & Sokolov, H. (2021). A review of automated feedback systems for

learners: Classification framework, challenges and opportunities. Computers & Education, 163, 104094. https://doi.org/10.1016/j.compedu.2020.104094 (ScienceDirect)

Fleckenstein, J., et al. (2023). Automated feedback and writing: A multi-level meta-analysis of the

effect of automated writing evaluation. Frontiers in Artificial Intelligence, 6, 1162454. https://doi.org/10.3389/frai.2023.1162454 (callej.org)

Mao, L., Liu, O., Roohr, K. R., & Belur, V. (2018). Validation of automated scoring for a formative

assessment that employs scientific argumentation. Educational Assessment, 23(2), 121–138. https://doi.org/10.1080/10627197.2018.1427570 (ScienceDirect)

Misgna, G. M., et al. (2024). A survey on deep learning-based automated essay scoring and feedback

generation. Artificial Intelligence Review. https://doi.org/10.1007/s10462-024-11017-5 (Springer)

Osaka, A., et al. (2025). Cultivating effective feedback with generative AI: Implications for students’

trust and learning. Interactive Learning Environments. https://doi.org/10.1080/10494820.2025.2452005 (Springer)

Pack, A., et al. (2024). Large language models and automated essay scoring: Validity and reliability of

automated scores and feedback. Computers and Education: Artificial Intelligence, 6, 100234. https://doi.org/10.1016/j.caeai.2024.100234 (ScienceDirect)

Perikos, I., Grivokostopoulou, F., & Hatzilygeroudis, I. (2017). Assistance and feedback mechanism

in an intelligent tutoring system for teaching conversion of natural language into logic. International Journal of Artificial Intelligence in Education, 27, 475–514. https://doi.org/10.1007/s40593-017-0139-y (Springer)

Ranalli, J., Link, S., & Chukharev-Hudilainen, E. (2017). Automated writing evaluation for formative

assessment of second language writing: Investigating the accuracy and usefulness of feedback as part of argument-based validation. Educational Psychology. https://doi.org/10.1080/01443410.2015.1136407 (Taylor & Francis Online)

Shi, H., & Aryadoust, V. (2024). A systematic review of AI-based automated written feedback

research. ReCALL, 36(2), 187–209. https://doi.org/10.1017/S0958344023000265 (Cambridge University Press & Assessment)

Tian, L., & Zhou, Y. (2020). Learner engagement with automated feedback, peer feedback and

teacher feedback in an online EFL writing context. System, 91, 102247. https://doi.org/10.1016/j.system.2020.102247 (ScienceDirect)

Usher, M., et al. (2025). Generative AI and assessment: Comparing AI-generated, instructor, and

peer assessments in authentic assessment settings. Assessment & Evaluation in Higher Education. https://doi.org/10.1080/02602938.2025.2487495 (Taylor & Francis Online)

Venter, M., et al. (2024). Exploring the use of artificial intelligence in the delivery of effective

feedback in higher education. Assessment & Evaluation in Higher Education. https://doi.org/10.1080/02602938.2024.2415649 (Taylor & Francis Online)

Zhai, X., & Ma, X. (2023). Automated writing evaluation and feedback in EFL/ESL writing: A

meta-analysis. Journal of Educational Computing Research, 61(4), 875–900. https://doi.org/10.1177/07356331221127300 (SAGE Journals)

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Published

19-02-2026

How to Cite

Dewi Agustina Solihin, Heny Fitriani, R. Dewi Mutia Farida, Ahmad Sofan Ansor, & Rosdiana. (2026). Implementasi Artificial Intelligence (AI) dalam Penilaian Formatif: Studi Literatur tentang Peningkatan Akurasi Evaluasi Pembelajaran. Journal of Innovative and Creativity, 6(1), 12507–12529. https://doi.org/10.31004/joecy.v6i1.8536

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