Implementing AI-Enhanced Learning Analytics to Improve Educational Outcomes Using Psychological Insights

References

[1] ADDIN EN.REFLIST Ahmad, K., Iqbal, W., El-Hassan, A., Qadir, J., Benhaddou, D., Ayyash, M., & Al-Fuqaha, A. (2023). Data-driven artificial intelligence in education: A comprehensive review. IEEE Transactions on Learning Technologies.

[2] Alam, A., & Mohanty, A. (2022). Predicting students’ performance employing educational data mining techniques, machine learning, and learning analytics. Paper presented at the International Conference on Communication, Networks and Computing.

[3] Alamri, H., Lowell, V., Watson, W., & Watson, S. L. (2020). Using personalized learning as an instructional approach to motivate learners in online higher education: Learner self-determination and intrinsic motivation. Journal of Research on Technology in Education, 52(3), 322-352.

[4] Alias, N. F., & Razak, R. A. (2023). Meeting the Demands of Higher Education: Examining Teaching and Learning Practices and Academic Challenges. Asian Journal of University Education, 19(4), 796-811.

[5] Barkley, E. F., & Major, C. H. (2020). Student engagement techniques: A handbook for college faculty: John Wiley & Sons.

[6] Broderick, P. C. (2021). Learning to breathe: A mindfulness curriculum for adolescents to cultivate emotion regulation, attention, and performance: new harbinger publications.

[7] Divanji, R. A., Bindman, S., Tung, A., Chen, K., Castaneda, L., & Scanlon, M. (2023). A one stop shop? Perspectives on the value of adaptive learning technologies in K-12 education. Computers and Education Open, 5, 100157.

[8] Filgona, J., Sakiyo, J., Gwany, D., & Okoronka, A. (2020). Motivation in learning. Asian Journal of Education and social studies, 10(4), 16-37.

[9] Gado, S., Kempen, R., Lingelbach, K., & Bipp, T. (2022). Artificial intelligence in psychology: How can we enable psychology students to accept and use artificial intelligence? Psychology Learning & Teaching, 21(1), 37-56.

[10] García-Pérez, D., Fraile, J., & Panadero, E. (2021). Learning strategies and self-regulation in context: How higher education students approach different courses, assessments, and challenges. European Journal of Psychology of Education, 36(2), 533-550.

[11] Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: a literature review. Education Sciences, 13(12), 1216.

[12] Greene, J. A., Bernacki, M. L., & Hadwin, A. F. (2024). Self-regulation. Handbook of educational psychology, 314-334.

[13] Hellín, C. J., Calles-Esteban, F., Valledor, A., Gómez, J., Otón-Tortosa, S., & Tayebi, A. (2023). Enhancing student motivation and engagement through a gamified learning environment. Sustainability, 15(19), 14119.

[14] Hogan, J. P., & White, P. (2021). A self-study exploration of early career teacher burnout and the adaptive strategies of experienced teachers. Australian Journal of Teacher Education (Online), 46(5), 18-39.

[15] Holstein, K., & Doroudi, S. (2021). Equity and artificial intelligence in education: will" aied" amplify or alleviate inequities in education? arXiv preprint arXiv:2104.12920.

[16] Huang, J., Saleh, S., & Liu, Y. (2021). A review on artificial intelligence in education. Academic Journal of Interdisciplinary Studies, 10(3).

[17] Kaswan, K. S., Dhatterwal, J. S., & Ojha, R. P. (2024). AI in personalized learning. In Advances in Technological Innovations in Higher Education (pp. 103-117): CRC Press.

[18] Kaur, S., Tandon, N., & Matharou, G. S. (2020). Contemporary trends in education transformation using artificial intelligence. In Transforming Management Using Artificial Intelligence Techniques (pp. 89-103): CRC Press.

[19] Kim, J. (2024). Leading teachers' perspective on teacher-AI collaboration in education. Education and Information Technologies, 29(7), 8693-8724.

[20] Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., . . . Gašević, D. (2023). Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning. Computers in Human Behavior, 139, 107547.

[21] Madaio, M., Blodgett, S. L., Mayfield, E., & Dixon-Román, E. (2022). Beyond “fairness”: Structural (in) justice lenses on ai for education. In The ethics of artificial intelligence in education (pp. 203-239): Routledge.

[22] Mahmoud, C., & Sørensen, J. (2024). Artificial Intelligence in Personalized Learning with a Focus on Current Developments and Future Prospects. Research and Advances in Education, 3(8), 25-31.

[23] Mello, R. F., Freitas, E., Pereira, F. D., Cabral, L., Tedesco, P., & Ramalho, G. (2023). Education in the age of Generative AI: Context and Recent Developments. arXiv preprint arXiv:2309.12332.

[24] Meng, N., Dhimolea, T. K., & Ali, Z. (2022). AI-enhanced education: Teaching and learning reimagined. In Bridging human intelligence and artificial intelligence (pp. 107-124): Springer.

[25] Namoun, A., & Alshanqiti, A. (2020). Predicting student performance using data mining and learning analytics techniques: A systematic literature review. Applied Sciences, 11(1), 237.

[26] Nückles, M., Roelle, J., Glogger-Frey, I., Waldeyer, J., & Renkl, A. (2020). The self-regulation-view in writing-to-learn: Using journal writing to optimize cognitive load in self-regulated learning. Educational Psychology Review, 32(4), 1089-1126.

[27] Ouyang, F., & Zhang, L. (2024). AI-driven learning analytics applications and tools in computer-supported collaborative learning: A systematic review. Educational Research Review, 44, 100616.

[28] Sajja, R., Sermet, Y., Cikmaz, M., Cwiertny, D., & Demir, I. (2024). Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education. Information, 15(10), 596.

[29] Schwartz, R., Schwartz, R., Vassilev, A., Greene, K., Perine, L., Burt, A., & Hall, P. (2022). Towards a standard for identifying and managing bias in artificial intelligence (Vol. 3): US Department of Commerce, National Institute of Standards and Technology.

[30] Shoaib, M., Sayed, N., Singh, J., Shafi, J., Khan, S., & Ali, F. (2024). AI student success predictor: Enhancing personalized learning in campus management systems. Computers in Human Behavior, 158, 108301.

[31] Skulmowski, A., & Xu, K. M. (2022). Understanding cognitive load in digital and online learning: A new perspective on extraneous cognitive load. Educational Psychology Review, 34(1), 171-196.

[32] Usman, F. O., Eyo-Udo, N. L., Etukudoh, E. A., Odonkor, B., Ibeh, C. V., & Adegbola, A. (2024). A critical review of ai-driven strategies for entrepreneurial success. International Journal of Management & Entrepreneurship Research, 6(1), 200-215.

[33] Vashishth, T. K., Sharma, V., Sharma, K. K., Kumar, B., Panwar, R., & Chaudhary, S. (2024). AI-driven learning analytics for personalized feedback and assessment in higher education. In Using traditional design methods to enhance AI-driven decision making (pp. 206-230): IGI Global.

[34] Vejmelka, L., Katulic, T., & Jurić, M. (2020). Application of the General Data Protection Regulation in Schools: A Qualitative Study with Teachers, Professional Associates and Principals. Paper presented at the 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO).

[35] Vermote, B., Aelterman, N., Beyers, W., Aper, L., Buysschaert, F., & Vansteenkiste, M. (2020). The role of teachers’ motivation and mindsets in predicting a (de) motivating teaching style in higher education: A circumplex approach. Motivation and emotion, 44, 270-294.

[36] Xu, J., Lio, A., Dhaliwal, H., Andrei, S., Balakrishnan, S., Nagani, U., & Samadder, S. (2021). Psychological interventions of virtual gamification within academic intrinsic motivation: A systematic review. Journal of Affective Disorders, 293, 444-465.

[37] Yuskovych-Zhukovska, V., Poplavska, T., Diachenko, O., Mishenina, T., Topolnyk, Y., & Gurevych, R. (2022). Application of artificial intelligence in education. Problems and opportunities for sustainable development. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 13(1Sup1), 339-356.

[38] Zhao, S., & Song, J. (2022). Unpacking the emotional experiences of learners in a blended learning context. Frontiers in Psychology, 13, 879696.

[39] Zhou, Q., Suraworachet, W., Pozdniakov, S., Martinez-Maldonado, R., Bartindale, T., Chen, P., . . . Cukurova, M. (2021). Investigating students’ experiences with collaboration analytics for remote group meetings. Paper presented at the Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part I 22.

@article{1706747,
      author = {Uyok Hanson, Chioma Angela Okonkwo, Christiana Uchechukwu Orakwe},
      title = {Implementing AI-Enhanced Learning Analytics to Improve Educational Outcomes Using Psychological Insights},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {6},
      pages = {543-553},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706747.pdf},
      abstract = {This review explores the integration of AI-enhanced learning analytics with psychological insights to improve educational outcomes. AI-driven tools have emerged as a powerful mechanism to personalize learning experiences, offering data-driven insights into student behavior and performance. Educators can create adaptive learning environments that foster engagement, retention, and academic success by incorporating key psychological theories?such as motivation, cognitive load, and self-regulation?into these systems. This paper highlights how AI tools, when combined with psychological principles, provide tailored interventions that address individual student needs in real time. It also discusses potential challenges, including data privacy concerns and ethical implications, while offering recommendations for educators and policymakers on leveraging these technologies effectively to ensure equitable access and improved learning outcomes. The review concludes by emphasizing the importance of balancing AI integration with the irreplaceable role of human interaction in education.},
      keywords = {AI-Enhanced Learning Analytics, Educational Outcomes, Psychological Insights, Personalized Learning, Student Engagement},
      month = {December},
  }