AI-Based Digitalization of Teaching Materials to Detect and Analyze Conceptual Errors in Science Learning

Wahyu Azhar Ritonga; Riszki Fadillah; Juli Yani; Ridho Alfauzan Harahap; Icha Rivani

doi:10.55227/ijhess.v5i3.2013

Authors

Wahyu Azhar Ritonga Teknik Informatika, Fakultas Ilmu Komputer, Universitas Al Washliyah Labuhanbatu, Indonesia
Riszki Fadillah Sistem Informasi, Fakultas Ilmu Komputer, Institut Teknologi dan Kesehatan Ika Bina Labuhanbatu
Juli Yani Pendidikan Bahasa dan Sastra Indonesia, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Al Washliyah Labuhanbatu, Indonesia
Ridho Alfauzan Harahap Teknik Informatika, Fakultas Ilmu Komputer, Universitas Al Washliyah Labuhanbatu, Indonesia
Icha Rivani Pendidikan Bahasa Inggris, Madrasah Ibtidaiyah Negeri 2 Labuhanbatu, Indonesia

DOI:

https://doi.org/10.55227/ijhess.v5i3.2013

Keywords:

Digitalization; Artificial Intelligence; Technology; Learning; Science.

Abstract

The digitalization of artificial intelligence (AI)-based teaching materials aims to improve the quality of science learning by detecting and analyzing conceptual errors made by students. AI technology can be used to identify common mistakes students make in understanding complex science concepts and provide faster and more accurate feedback. Using machine learning algorithms and data analysis, AI-based systems can analyze students' answers, recognize error patterns, and provide explanations or additional materials to help improve their understanding. This approach not only simplifies the evaluation process but also enables more personalized and tailored instruction. Another advantage of digitalizing teaching materials is its ability to provide more interactive and engaging learning and help teachers identify areas that need more attention in the learning process. The aim of this research is to develop a system that can help students and teachers identify and correct conceptual errors in science learning materials. This approach utilizes artificial intelligence (AI) to analyze student interactions with digital teaching materials, such as practice problems or simulations, to detect potential common conceptual errors. This research method uses a mixed method that utilizes interviews, observations, and student analysis results with the interaction of an AI-based system with Natural Language Processing (NLP) and Machine Learning technology used to analyze student answers and detect conceptual errors. The results of this study indicate that of the 40 teacher respondents and 90 students, the use of interactive media using AI greatly facilitates the material being taught. Thus, the use of AI in science education can play a significant role in improving the effectiveness of teaching and students' understanding of the subject matter.

References

Almarashdeh, I., & Al-Shatanawi, M. (2020). The impact of artificial intelligence on education and its role in enhancing educational opportunities. International Journal of Advanced Computer Science and Applications, 11(10), 112-119. Doi: https://doi.org/10.14569/IJACSA.2020.0111015

Chen, X., & Xie, H. (2020). A Review of AI-based Adaptive Learning Systems: Benefits and Challenges. Journal of Educational Technology Development and Exchange, 13(1), 30-45. Doi: https://doi.org/10.18785/jetde.1301.04

Chen, L., & Wang, S. (2018). AI-Based Learning Systems and Their Role in Solving Educational Problems. Journal of Educational Computing Research, 56(3), 424-440. Doi: https://doi.org/10.1177/0735633117738252

Chen, C. M., & Tsai, C. C. (2019). The Effect of Virtual Reality on Students' Learning Performance and Learning Motivation: A Review of the Literature. Computers in Human Behavior, 99, 202-210. Doi: https://doi.org/10.1016/j.chb.2019.05.001Dian, E.Y., Wahyu, A.R.,dkk 2025. Sistem Digital. Sumatera Barat: CV Hei Publishing Indonesia. Link: https://heipublishing.id/kontributor/buku/sistem-digital

Guszcza, J., & Mahoney, S. (2018). Artificial Intelligence in Education: Current Trends and Future Directions. International Journal of Artificial Intelligence in Education, 28(1), 43-67. Doi: https://doi.org/10.1007/s40593-018-0153-z

Huang, R. H., & Spector, J. M. (2019). Emerging Technologies and Innovations in Education: Educational Applications of AI and Big Data. Springer. Doi: https://doi.org/10.1007/978-3-030-11510-7

He, J., & Li, T. (2020). Advances in Recommender Systems: Algorithms and Applications for Personalized Learning. Springer. Doi: https://doi.org/10.1007/978-3-030-13964-7.

Kaplan, A. M., & Haenlein, M. (2019). Artificial Intelligence in Education: A Systematic Review. Journal of Educational Psychology, 111(2), 183-196 Doi: https://doi.org/10.1037/edu0000350

Li, L., & Wang, W. (2021). Artificial Intelligence in Education: A Critical Review and Future Prospects. Smart Learning Environments, 8(1), 1-15 Doi: https://doi.org/10.1186/s40561-021-00129-3

Liu, T., & Wang, Z. (2019). Educational Application of Artificial Intelligence: New Trends in Personalized Learning. International Journal of Educational Technology in Higher Education, 16(1), 7. https://doi.org/10.1186/s41239-019-0164-8Sharma, S., & Singh, H. (2020). AI-based Personalized Learning Systems for Education: A Systematic Review. Education and Information Technologies, 25(1), 1-25 Doi: https://doi.org/10.1007/s10639-019-03324-6

Perry, B., & Dede, C. (2018). Learning in Virtual and Augmented Reality Environments: Opportunities and Challenges for Education. International Journal of Artificial Intelligence in Education, 28(4), 723-742. Doi: https://doi.org/10.1007/s40593-018-0179-7

Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A Survey of Augmented Reality in Education: The Impact of AR on Learning Performance and Learning Experience. Computers & Education, 146, 103778. Doi: https://doi.org/10.1016/j.compedu.2019.103778

Sharma, S., & Singh, H. (2020). AI-based Personalized Learning Systems for Education: A Systematic Review. Education and Information Technologies, 25(1), 1-25. Doi: https://doi.org/10.1007/s10639-019-03324-6

Van der Meijden, A., & Molenaar, I. (2019). Evaluating Learning Management Systems Using User Feedback: An Educational Technology Approach. British Journal of Educational Technology, 50(6), 3201-3215. Doi: https://doi.org/10.1111/bjet.12739

Wahyu A.R. dkk. 2025. Media dan Teknologi Pendidikan. Puwekerto: CV. TataKata Grafika. Link:https://tatakatagrafika.com/2025/03/10/media-dan-teknologi-pendidikan/

Yang, Y., & Li, X. (2021). AI in Education: A Critical Review and Future Prospects. Smart Learning Environments, 8 (1), 1-15. Doi: https://doi.org/10.1186/s40561-021-00129-3