AI and Student Engagement: A Comparative Analysis
DOI:
https://doi.org/10.56345/ijrdv11n326Keywords:
Adaptive learning, AI in education, Personalized Learning, Student Engagement, Comparative analysis, Learning platforms, Educational OutcomesAbstract
This study will investigate in detail about the impact of AI on student engagement by using a comparative analysis of different AI-powered educational technologies. The study focuses on various tools include Knewton, GenAI, Smart Sparrow, DreamBox Learning, Carnegie and other technologies. Secondly, the research examines in detail about the influence of these technologies on student motivation, personalized learning, participation, and overall educational outcomes. For conducting required results, the study employs a quantitative methodology by using surveys for obtaining data on satisfaction, student engagement, and adaptive feedback effectiveness in traditional and AI driven learning environments. Moreover, the results shows that the AI technologies are significantly enhancing engagement level of students particularly with those platforms that are providing personalized learning, real-time feedback, and interactive content. This study also identifies various challenges related to ethical concerns, user interface, accessibility, and concerns like data privacy. The findings are suggesting that AI has the potential to transform education. However, addressing these challenges is also important for ensuring equitable learning experience for the students and teachers.
Received: 11 September 2024 / Accepted: 10 November 2024 / Published: 3 December 2024
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.