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Research Paper | Computer Science and Information Technology | Volume 15 Issue 8, August 2026 | Pages: 1592 - 1597 | India
Applications of Artificial Intelligence and Deep Learning in Education
Abstract: Artificial Intelligence (AI) and Deep Learning are changing how teaching and learning happen. This paper reviews the literature on AI and Deep Learning in education and presents three technically explicit case studies: predicting at-risk students from Virtual Learning Environment (VLE) interaction data in the style of the Open University Learning Analytics Dataset (OULAD); tracing a student?s evolving knowledge state with a recurrent neural network (Deep Knowledge Tracing, DKT); and scoring free-text answers with transformer language models (BERT-family Automated Essay Scoring). Each case study specifies an illustrative dataset schema, the model architecture used in the literature, and representative published performance figures. The paper also reviews the documented benefits of these systems (time saved for teachers, faster feedback, wider access), the challenges that limit them in practice (cost, the digital divide, data privacy, algorithmic bias, over-reliance), and the ethical principles- fairness, transparency, consent, and human oversight- that should govern their use. The overall finding is that AI and Deep Learning are most valuable in education when designed as decision-support tools for teachers rather than as replacements for them.
Keywords: Artificial Intelligence, Deep Learning, Learning Analytics, Knowledge Tracing, Automated Essay Scoring
How to Cite?: Somnath Kar, Priya Sahoo, Supriya Panda, "Applications of Artificial Intelligence and Deep Learning in Education", Volume 15 Issue 8, August 2026, International Journal of Science and Research (IJSR), Pages: 1592-1597, https://www.ijsr.net/getabstract.php?paperid=SR26821214723, DOI: https://dx.doi.org/10.21275/SR26821214723