AI-Driven Question Generation for Automated E-Learning Assessment and Personalized Feedback


Authors : Keerthana S; Sandra Paul; Soundarya R; Vaishnavi BN; Dr. Sathish Kumar S

Volume/Issue : Volume 9 - 2024, Issue 11 - November


Google Scholar : https://tinyurl.com/25mw22pu

Scribd : https://tinyurl.com/5f7sx3mb

DOI : https://doi.org/10.5281/zenodo.14408780


Abstract : The utilization of artificial intelligence (AI) in educational settings has become a topic of increasing significance in recent years, with particular emphasis on its role in evaluating online learning experiences. This survey explores the innovative use of AI- driven question generation and personalized feedback mechanisms, highlighting their potential to enhance learner engagement and improve educational outcomes. We begin by examining various AI technologies, including natural language processing (NLP) and machine learning algorithms, that facilitate the automatic generation of diverse assessment items tailored to individual learner profiles. The paper discusses the importance of real-time feedback in fostering a growth mindset, enabling learners to identify strengths and areas for improvement. We also review existing literature on adaptive learning systems and their effectiveness in creating personalized learning experiences. Additionally, this review examines the obstacles encountered when integrating AI into educational settings, including issues related to data security and the necessity for reliable validation techniques. Through the compilation of results from diverse studies, we seek to offer a thorough examination of AI's current role in e- learning assessment practices.

Keywords : Artificial Intelligence, E-Learning, Question Generation, Personalized Feedback, Adaptive Learning, Natural Language Processing, Educational Technology, Learner Engagement, Assessment, Data Privacy.

References :

    1. Luckin, S., Holmes, M., Griffiths, W., and Forcier, L., 2016. "Intelligence Unleashed: An Argument for AI in Education." Pearson, London. This publication discusses the transformative potential of artificial intelligence in educational settings, advocating for its integration to enhance learning outcomes.
    2. Chen, C., Zhang, H. P., and Zhang, J., 2019. "Exploring AI's Contribution to Individualized Learning Approaches." International Journal of Educational Technology in Higher Education, vol. 16, no. 1, pp. 1-12. This article explores how AI technologies can tailor educational experiences to individual learners, promoting engagement and efficiency.
    3. Kumar, S. and Singh, S., 2020. "Using Natural Language Processing Techniques for Automated Question Generation."Journal of Educational Technology Systems, vol. 48, no. 2, pp.153-167. The authors present methodologies for generating assessment questions automatically using NLP, highlighting their implications for personalized education.
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    6. Persson, T., 2020. "The Ethics of Artificial Intelligence in Education: Considerations and Challenges." AI & Society, vol. 35, no. 2, pp. 319-327. This paper addresses ethical concerns related to the implementation of AI in educational settings, focusing on privacy, bias, and equity.
    7. Silva, A. D. G. G., Costa, A. D. P., and Silva, T. M. A., 2020. "Artificial Intelligence and Personalized Learning: A Systematic Review." Journal of Computer Assisted Learning, vol. 36, no. 1, pp. 34-47. The authors perform a comprehensive review of the literature on AI-powered personalized learning, emphasizing current trends and potential future developments.
    8. Shute, M. R. and Rahimi, R., 2018. "Adaptive Learning: "An Examination of Research on Its Efficacy." International Journal of Computer-Supported Learning, vol. 33, no. 4, pp. 321-334. This review evaluates the effectiveness of adaptive learning technologies, with a focus on their impact on student achievement.

The utilization of artificial intelligence (AI) in educational settings has become a topic of increasing significance in recent years, with particular emphasis on its role in evaluating online learning experiences. This survey explores the innovative use of AI- driven question generation and personalized feedback mechanisms, highlighting their potential to enhance learner engagement and improve educational outcomes. We begin by examining various AI technologies, including natural language processing (NLP) and machine learning algorithms, that facilitate the automatic generation of diverse assessment items tailored to individual learner profiles. The paper discusses the importance of real-time feedback in fostering a growth mindset, enabling learners to identify strengths and areas for improvement. We also review existing literature on adaptive learning systems and their effectiveness in creating personalized learning experiences. Additionally, this review examines the obstacles encountered when integrating AI into educational settings, including issues related to data security and the necessity for reliable validation techniques. Through the compilation of results from diverse studies, we seek to offer a thorough examination of AI's current role in e- learning assessment practices.

Keywords : Artificial Intelligence, E-Learning, Question Generation, Personalized Feedback, Adaptive Learning, Natural Language Processing, Educational Technology, Learner Engagement, Assessment, Data Privacy.

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