doi: 10.18178/ijiet.2025.15.7.2342
Effectiveness of AI-Driven Assessments in Enhancing Learning Evaluation through Predictive Technology in Vocational Secondary School
Ridho Dedy Arief Budiman1,3,*
,
Herman Dwi Surjono1 ,
Wagiran1 ,
Muhamad Firdaus2 ,
Tuti Kurniati3 ,
Vindo Feladi2 ,
Dini Oktarika2 ,
Muhammad Hakiki4 ,
Arisman Sabir5 ,
Tri Wiyoko6 ,
Abdul Kadir7 ,
Mustofa Abi Hamid8 ,
Radinal Fadli9
- 1Department of Technology and Vocational Education, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
- 2Faculty of Mathematics, Science and Technology, Universitas PGRI Pontianak, Pontianak, Indonesia
- 3Faculty of Teacher Training and Education, Universitas Muhammadiyah Pontianak, Pontianak, Indonesia
- 4Faculty of Engineering, Universitas Negeri Surabaya, Surabaya, Indonesia
- 5Department of Civic Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
- 6Department of Education, Universitas Jambi, Jambi, Indonesia
- 7Faculty of Education and Psychology, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
- 8Faculty of Teacher Training and Education, Universitas Sultan Ageng Tirtayasa, Banten, Indonesia
- 9Department of Information Technology Education, Universitas Lampung, Lampung, Indonesia
- Manuscript receivedNovember 21, 2024
- revisedDecember 25, 2024
- acceptedFebruary 18, 2025
- publishedJuly 14, 2025
Abstract
This study evaluates the effectiveness of Artificial Intelligence (AI)-driven assessments in enhancing learning evaluation through predictive technology in vocational secondary schools. Using a quasi-experimental design, the study involved two groups: an experimental group (n = 100) that used AI-driven assessments and a control group (n = 100) with traditional methods. Both groups took pre-tests and post-tests to measure knowledge changes, along with surveys and observations to assess engagement and satisfaction. The experimental group showed significantly higher post-test scores (85.6% vs. 76.4%), indicating improved performance. Additionally, 89.25% of students in the experimental group re-ported greater engagement. 90.20% of the students expressed high satisfaction with the assessment process, rating their experience as very satisfying. Observational data confirmed a more active learning environment in the experimental group. The findings suggest that AI-driven assessments provide more efficient and adaptive evaluations, enhancing both learning outcomes and student engagement, with real-time feedback supporting continuous improvement.
Keywords
- Artificial Intelligence (AI)-driven assessments
- predictive technology
- vocational education
- learning evaluation
How to Cite
Ridho Dedy Arief Budiman, Herman Dwi Surjono, Wagiran, Muhamad Firdaus, Tuti Kurniati, Vindo Feladi, Dini Oktarika, Muhammad Hakiki, Arisman Sabir, Tri Wiyoko, Abdul Kadir, Mustofa Abi Hamid, and Radinal Fadli, "Effectiveness of AI-Driven Assessments in Enhancing Learning Evaluation through Predictive Technology in Vocational Secondary School," International Journal of Information and Education Technology, vol. 15, no. 7, pp. 1410-1417, 2025. https://doi.org/10.18178/ijiet.2025.15.7.2342
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).