Adaptive Cognitive Computing For Personalized Learning Evaluations
Keywords:
Adaptive assessments, cognitive computing, intelligent learning systems, personalised evaluations, machine learning, dynamic feedbackAbstract
The integration of cognitive computing in intelligent learning systems has enabled dynamic and adaptive assessments tailored to individual learners. This study explores a machine learning-driven evaluation framework that continuously analyses examinee performance data to adjust assessment difficulty in real time. Using smart algorithms, the system personalises feedback and question sequencing, optimising learning pathways for improved educational outcomes. Empirical results show that this approach significantly enhances exam precision, engagement, and knowledge retention, outperforming static evaluation methods.
DOI: https://doi.org/10.24321/2395.3802.202509
References
Halkiopoulos C, Gkintoni E. Leveraging AI in e-learning: Personalised learning and adaptive assessment through cognitive neuropsychology—A systematic analysis. Electronics. 2024 Sep 22;13(18):3762.
Muhammad K, Khan S, Del Ser J, De Albuquerque VH. Deep learning for multigrade brain tumor classification in smart healthcare systems: A prospective survey. IEEE Transactions on Neural Networks and Learning Systems. 2020 Jun 30;32(2):507-22.
