AI-Powered E-Learning Solution Shows Promise in India's Educational Institutions

Strategic Insights -

A new study by researchers from Veer Kunwar Singh University has explored the potential of artificial intelligence in enhancing e-learning experiences for students in India's educational institutions. The study, which analyzed data from 605 students from various schools across India, focused on the impact of AI-driven social learning networks, personalized learning portfolios, and tailored learning environments on students' perceived usefulness and ease of use.

Key Takeaways:

  • The study proposed a solution using the K-means clustering algorithm to analyze student data and identify the best-fit learning approach for each student.
  • The model was able to predict the suitable learning method for students with an accuracy rate of 82.52%.
  • The study revealed a strong correlation between AI-based tools and students' perceived usefulness and ease of use in their educational experiences.
  • The researchers used machine learning-based classification methods to identify key factors influencing e-learning systems and propose a more tailored and effective e-learning experience.
  • The study highlighted the importance of identifying and addressing the challenges of traditional education, including the disruption caused by online or hybrid teaching models.
  • The research team consisted of Md Alimul Haque, Sultan Ahmad, Devanshu Kumar, and Hikmat A. M. Abdeljaber from Veer Kunwar Singh University.

Statistics:

  • 605 students were involved in the study from various schools across India.
  • The accuracy rate of the model in predicting the suitable learning method for students was 82.52%.
  • The study focused on assessing the impact of AI-driven social learning networks, personalized learning portfolios, and tailored learning environments on students' perceived usefulness and ease of use.
  • The research was published in the Proceedings on Engineering Sciences journal, Volume 7, Issue 2, pages 1211-1218.

Sources:

  • Using Machine Learning Algorithms To Analyze Factors Influencing Acceptance of E-learning. Proceedings on Engineering Sciences, 2025,7(2):1211-1218.
  • Medical Letter on the CDC & FDA. July 20, 2025; p 412 (NewsRx)