AI-Driven Question Generation for Automated E-Learning Assessment and Personalized Feedback
Year: 2024
Type: article
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.
Authors: Keerthana S, Sandra Paul, Soundarya R, Vaishnavi BN, Dr. Sathish Kumar S
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6893089417