LEVERAGING EDUCATIONAL TECHNOLOGY: STATISTICAL EVIDENCE ON AI'S ROLE IN MATHEMATICS LEARNING OUTCOMES

Authors

  • Vera Septi Andrini Universitas PGRI Mpu Sindok
  • Umi Hidayati Universitas PGRI Mpu Sindok
  • Erdyna Dwi Etika Universitas PGRI Mpu Sindok

DOI:

https://doi.org/10.31571/edukasi.v23i1.8754

Keywords:

artificial intelligence (AI), learning analytics (LA), mathematics learning outcome, adaptive learning, learning evaluation

Abstract

This study aims to analyze the role of Artificial Intelligence (AI) and Learning Analytics (LA) in improving mathematics learning outcomes in higher education. An explanatory sequential mixed-methods design was employed, beginning with quantitative data collection through pre-tests and post-tests, followed by qualitative analysis. Research instruments included a mathematics achievement test, semi-structured interview guidelines, observation sheets, and a student engagement questionnaire. The study involved 120 students and 6 mathematics lecturers. The results showed that the integration of AI (β = 0.624) and LA (β = 0.312) significantly accounted for 72.8% of the variance in students' mathematics achievement. The integrated system is capable of analyzing cognitive, affective, and psychomotor aspects with a prediction accuracy of up to 94% and identifying 89% of learning issues before examinations. These findings provide an empirical foundation for developing effective, adaptive, and flexible mathematics learning systems in higher education.

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References

Abutayeh, K. A., Kraishan, O. M., & Kraishan, E. Q. (2022). The use of virtual and augmented reality in science and math education in Arab countries: A survey of previous research studies. Frontiers in Education, 7.

Achenbach, T. M., Becker, A., Döpfner, M., Heiervang, E., Roessner, V., Steinhausen, H.-C., Rothenberger, A., Adams, D., Oliver, C., Ahlers, C. J., Schaefer, G. A., Mundt, I. A., Roll, S., Englert, H., Willich, S. N., Beier, K. M., Altemeyer, B., Hunsberger, B., Amato, P. R., … Earls, F. (2011). Motivation: A biosocial and cognitive integration of motivaiton and emotion. American Psychologist, 47(3).

Allahawiah, S., Altarawneh, H., & Almajaly, N. (2023). The Impact of Virtual Classrooms and Google Sites on Teaching Computer Skills Courses: Karak University College-Jordan. International Journal of Emerging Technologies in Learning, 18(7).

Almada, A., Yu, Q., & Patel, P. (2023). Proactive Chatbot Framework Based on the PS2CLH Model: An AI-Deep Learning Chatbot Assistant for Students. Lecture Notes in Networks and Systems, 542 LNNS.

Anderson, L. W., Krathwohl Peter W Airasian, D. R., Cruikshank, K. A., Mayer, R. E., Pintrich, P. R., Raths, J., & Wittrock, M. C. (2001). Taxonomy for_ Assessing a Revision 0F Bl00M’S Tax0N0My 0F Educati0Nal Objectives.

Anis, M., & Scholar, R. (2023). Leveraging Artificial Intelligence For Inclusive English Language Teaching: Strategies And Implications For Learner Diversity 54 Leveraging Artificial Intelligence For Inclusive English Language Teaching: Strategies And Implications For Learner Diversity. In Peer Reviewed and Refereed Journal (Issue 6).

Asudani, D. S., Nagwani, N. K., & Singh, P. (2023). Impact of word embedding models on text analytics in deep learning environment: a review. Artificial Intelligence Review, 56(9).

Chang, D. H., Lin, M. P. C., Hajian, S., & Wang, Q. Q. (2023). Educational Design Principles of Using AI Chatbot That Supports Self-Regulated Learning in Education: Goal Setting, Feedback, and Personalization. Sustainability (Switzerland), 15(17).

Charania, A. (2021). Constructivist teaching and learning with technologies in the COVID-19 lockdown in Eastern India. British Journal of Educational Technology, 52(4), 1478–1493.

Choi, E., Choi, Y., & Park, N. (2022). Blockchain-Centered Educational Program Embodies and Advances 2030 Sustainable Development Goals. Sustainability (Switzerland), 14(7).

Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability (Switzerland), 12(24), 1–22.

Creswell, J. W. (2019). Research Design Pendekatan Metode Kualitatif, Kuantitatif dan Campuran. Yogyakarta: Pustaka Pelajar. Progress in Retinal and Eye Research, 561(3).

Daher, W., Diab, H., & Rayan, A. (2023). Artificial Intelligence Generative Tools and Conceptual Knowledge in Problem Solving in Chemistry. Information (Switzerland), 14(7).

Darban, M. (2023). The future of virtual team learning: navigating the intersection of AI and education. Journal of Research on Technology in Education.

Dieterle, E., Dede, C., & Walker, M. (2024). The cyclical ethical effects of using artificial intelligence in education. AI and Society, 39(2).

Egloffstein, M., & Ifenthaler, D. (2021). Tracing Digital Transformation in Educational Organizations. In Digital Transformation of Learning Organizations.

El-Aasar, S. A., & Farghali, G. F. (2022). Predictive Study of the Factors and Challenges Affecting the Usability of E-Learning Platforms in the Light of COVID-19. International Journal of Education in Mathematics, Science and Technology, 10(3), 568–589.

Fernandes, A., & Gabriel, M. L. D. S. (2023). What Is Digital Transformation In Marketing? A Bibliometric And Scientometric Analysis Of An Evolving Topic. Revista Brasileira de Marketing, 22(4).

Fiialka, S., Kornieva, Z., & Honcharuk, T. (2023). ChatGPT in Ukrainian Education: Problems and Prospects. International Journal of Emerging Technologies in Learning, 18(17).

Findeisen, S., & Wild, S. (2022). General digital competences of beginning trainees in commercial vocational education and training. Empirical Research in Vocational Education and Training, 14(1).

Gkinko, L., & Elbanna, A. (2023). The appropriation of conversational AI in the workplace: A taxonomy of AI chatbot users. International Journal of Information Management, 69.

Govindaraju, V. (2021). A Review Of Social Cognitive Theory From The Perspective Of Interpersonal Communication. Multicultural Education, 7(12).

Hao, Z., Bin Yahya, M. Y., & Lu, J. (2023). Influence of Blockchain Technology Application in Education on Online Teaching Resources Sharing. International Journal of Emerging Technologies in Learning, 18(11).

Harry, A. (2023). Role of AI in Education. Interdiciplinary Journal and Hummanity (INJURITY), 2(3).

Hatlevik, I. K. R., Jakhelln, R., & Jorde, D. (2024). Transforming University-based Teacher Education through Innovation. In Transforming University-based Teacher Education through Innovation.

Hernández-de-Menéndez, M., Morales-Menendez, R., Escobar, C. A., & Ramírez Mendoza, R. A. (2022). Learning analytics: state of the art. International Journal on Interactive Design and Manufacturing, 16(3).

Herodotou, C., Naydenova, G., Boroowa, A., Gilmour, A., & Rienties, B. (2020). How can predictive learning analytics and motivational interventions increase student retention and enhance administrative support in distance education? Journal of Learning Analytics, 7(2), 72–83.

Hilz, A., Guill, K., Roloff, J., Sommerhoff, D., & Aldrup, K. (2023). How to Continue? New Approaches to Investigating the Effects of Adaptive Math Learning Programs on Students’ Performance, Self-Concept, and Anxiety. Journal of Intelligence, 11(6).

Islam, K. F., Awal, A., Mazumder, H., Munni, U. R., Majumder, K., Afroz, K., Tabassum, M. N., & Hossain, M. M. (2023). Social cognitive theory-based health promotion in primary care practice: A scoping review. In Heliyon (Vol. 9, Issue 4).

Ismail, S. N., Hamid, S., Ahmad, M., Alaboudi, A., & Jhanjhi, N. (2021). Exploring students engagement towards the learning management system (LMS) using learning analytics. Computer Systems Science and Engineering, 37(1).

Kim, C. J., Mo, H., & Lee, J. Y. (2022). Evaluation of an ultrasound program in nationwide Continuing Professional Development (CPD) in Korean public health and medical institutions. BMC Medical Education, 22(1).

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for Language Teaching and Learning. In RELC Journal (Vol. 54, Issue 2).

Lange, P. A. M. Van, Kruglanski, A. W., & Higgins, E. T. (2012). Theories of Social Psychology. In Psikodimensia (Vol. 1, Issue 1).

Lee, C. A., Huang, N. F., Tzeng, J. W., & Tsai, P. H. (2023). AI-Based Diagnostic Assessment System: Integrated With Knowledge Map in MOOCs. IEEE Transactions on Learning Technologies, 16(5).

Lee, S. S., Li, N., & Kim, J. (2024). Conceptual model for Mexican teachers’ adoption of learning analytics systems: The integration of the information system success model and the technology acceptance model. Education and Information Technologies, 29(11).

Miles, M. B., & Huberman, A. M. (1994). Data analysis Qualitative Data Analysis A Methods Sourcebook Edition. Qualitative Data Analysis A Methods Sourcebook.

Mozahem, N. A. (2022). Social cognitive theory and women’s career choices: an agent—based model simulation. Computational and Mathematical Organization Theory, 28(1).

Munir, H., Vogel, B., & Jacobsson, A. (2022). Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision. In Information (Switzerland) (Vol. 13, Issue 4).

Nafiati, D. A. (2021). Revisi taksonomi Bloom: Kognitif, afektif, dan psikomotorik. Humanika, 21(2).

Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers’ trust in AI-powered educational technology and a professional development program to improve it. British Journal of Educational Technology, 53(4).

Nguyen, A., Gardner, L., & Sheridan, D. (2020). A design methodology for learning analytics information systems: Informing learning analytics development with learning design. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-January.

Nguyen, A., Wandabwa, H., Rasco, A., & Le, A. L. (2021). A framework for designing learning analytics information systems. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-January.

Rahmatullah, A. S., Mulyasa, E., Syahrani, S., Pongpalilu, F., & Putri, R. E. (2022). Digital era 4.0. Linguistics and Culture Review, 6.

Rets, I., Herodotou, C., Bayer, V., Hlosta, M., & Rienties, B. (2021). Exploring critical factors of the perceived usefulness of a learning analytics dashboard for distance university students. International Journal of Educational Technology in Higher Education, 18(1).

Risdianto, E., Masito, F., Yustisia, N., Macariola, J. S., Fathurrochman, I., & Yunita, W. (2023). The Effectiveness of Augmented Reality (AR)-Based Blended Learning Models to Increase the Creativity of Prospective Educators.

Roblyer, M. . (2015). IntroductIon to SyStematIc InStructIonal deSIgn for tradItIonal, onlIne, and Blended envIronments (Issue September).

Roumba, E., & Nicolaidou, I. (2022). Augmented Reality Books: Motivation, Attitudes, and Behaviors of Young Readers. International Journal of Interactive Mobile Technologies, 16(16).

Schroeder, K. T., Hubertz, M., Van Campenhout, R., & Johnson, B. G. (2022). Teaching and Learning with AI-Generated Courseware: Lessons from the Classroom. Online Learning Journal, 26(3), 73–87.

Sethi, Y., Patel, N., Kaka, N., Desai, A., Kaiwan, O., Sheth, M., Sharma, R., Huang, H., Chopra, H., Khandaker, M. U., Lashin, M. M. A., Hamd, Z. Y., & Emran, T. Bin. (2022). Artificial Intelligence in Pediatric Cardiology: A Scoping Review. In Journal of Clinical Medicine (Vol. 11, Issue 23).

Sghir, N., Adadi, A., & Lahmer, M. (2023). Recent advances in Predictive Learning Analytics: A decade systematic review (2012–2022). In Education and Information Technologies (Vol. 28, Issue 7). Springer US.

Shimada, A., Konomi, S., & Ogata, H. (2018). Real-time learning analytics system for improvement of on-site lectures. Interactive Technology and Smart Education, 15(4).

Shishakly, R., Almaiah, M. A., Lutfi, A., & Alrawad, M. (2024). The influence of using smart technologies for sustainable development in higher education institutions. International Journal of Data and Network Science, 8(1).

Singh, S., Kumar, R., Payra, S., & Singh, S. K. (2023). Artificial Intelligence and Machine Learning in Pharmacological Research: Bridging the Gap Between Data and Drug Discovery. Cureus.

Sridhar, A., & Rajshekhar, J. S. (2022). AI-Integrated Proctoring System for Online Exams. Journal of Artificial Intelligence and Capsule Networks, 4(2).

Susnjak, T., Ramaswami, G. S., & Mathrani, A. (2022). Learning analytics dashboard: a tool for providing actionable insights to learners. International Journal of Educational Technology in Higher Education, 19(1).

Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. Electronic Journal of E-Learning, 20(5).

Turnbull, D., Chugh, R., & Luck, J. (2022). An Overview of the Common Elements of Learning Management System Policies in Higher Education Institutions. TechTrends, 66(5), 855–867.

Unaida, R., Fakhrah, & Lukman, I. R. (2023). Perception of Prospective Teachers to the Needs of ICT in Chemical Learning in the Age of Digital Transformation.

Unesco. (2018). UNESCO ICT Competency Framework for Teachers Version 3. In United Nations Educational, Scientific and Cultural Organization.

Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. In Computers in Human Behavior (Vol. 89).

W. LaMorte MD, PhD, MPH, W. (2019). The social cognitive theory. In Boston University School of Public Health (Vol. 12, Issue 2).

Wang, W. (2022). Influences of Education App-Assisted Teaching Technology on Learning Efficacy of Learners. International Journal of Emerging Technologies in Learning, 17(21).

Wu, W., Zhang, B., Li, S., & Liu, H. (2022). Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory. Frontiers in Psychology, 13.

Xin, O. K., & Singh, D. (2021). Development of Learning Analytics Dashboard based on Moodle Learning Management System. International Journal of Advanced Computer Science and Applications, 12(7).

Zhao, R., Zhuang, Y., Zou, D., Xie, Q., & Yu, P. L. H. (2023). AI-assisted automated scoring of picture-cued writing tasks for language assessment. Education and Information Technologies, 28(6).

Zheng, F. (2022). Personalized Education Based on Hybrid Intelligent Recommendation System. In Journal of Mathematics (Vol. 2022).

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Published

2025-06-30

How to Cite

Andrini, V. S., Hidayati, U., & Etika, E. D. (2025). LEVERAGING EDUCATIONAL TECHNOLOGY: STATISTICAL EVIDENCE ON AI’S ROLE IN MATHEMATICS LEARNING OUTCOMES. Edukasi: Jurnal Pendidikan, 23(1), 114–129. https://doi.org/10.31571/edukasi.v23i1.8754

Issue

Vol. 23 No. 1 (2025): Edukasi: Jurnal Pendidikan

Section

Research Article (Artikel Penelitian)

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Copyright (c) 2025 Vera Septi Andrini, Umi Hidayati, Erdyna Dwi Etika

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