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Evaluation of the Use of Artificial Intelligence in Teaching Learning Evaluation Courses Fadliansyah, Muhamad Raffi; Dwiyanto, Rian; Nur Syamsiyah, Nur Syamsiyah
Jurnal Evaluasi dan Pembelajaran Vol 6 No 2 (2024)
Publisher : STKIP Al Islam Tunas Bangsa dan HEPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52647/jep.v6i2.238

Abstract

This study aims to evaluate the use of Artificial Intelligence (AI) in teaching the Learning Evaluation course for students. By utilizing AI technology, such as chatbots, learning recommendation systems, and data analysis tools, teaching this course is expected to increase the effectiveness, efficiency, and engagement of students in the learning process. The study used a descriptive quantitative approach with a questionnaire-based survey on 37 5th-semester students of UIN Syarif Hidayatullah Jakarta. The results showed that AI supported material understanding by up to 85%, increased the average exam score by 15%, and increased student engagement by up to 78%. However, challenges such as technical gaps and adaptation to new technologies remain obstacles, experienced by 30% of respondents. The level of student satisfaction with AI-based learning is in the high category (4-5 out of a maximum score of 5). This study provides important implications for the development of technology-based teaching methods in the field of education, with recommendations for strengthening technology infrastructure and technology adaptation training for lecturers and students.
Evaluation of the Use of Artificial Intelligence in Teaching Learning Evaluation Courses Fadliansyah, Muhamad Raffi; Dwiyanto, Rian; Nur Syamsiyah, Nur Syamsiyah
Jurnal Evaluasi dan Pembelajaran Vol 6 No 2 (2024)
Publisher : STKIP Al Islam Tunas Bangsa dan HEPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52647/jep.v6i2.238

Abstract

This study aims to evaluate the use of Artificial Intelligence (AI) in teaching the Learning Evaluation course for students. By utilizing AI technology, such as chatbots, learning recommendation systems, and data analysis tools, teaching this course is expected to increase the effectiveness, efficiency, and engagement of students in the learning process. The study used a descriptive quantitative approach with a questionnaire-based survey on 37 5th-semester students of UIN Syarif Hidayatullah Jakarta. The results showed that AI supported material understanding by up to 85%, increased the average exam score by 15%, and increased student engagement by up to 78%. However, challenges such as technical gaps and adaptation to new technologies remain obstacles, experienced by 30% of respondents. The level of student satisfaction with AI-based learning is in the high category (4-5 out of a maximum score of 5). This study provides important implications for the development of technology-based teaching methods in the field of education, with recommendations for strengthening technology infrastructure and technology adaptation training for lecturers and students.