ABSTRACT
The educational performance of the learners is analyzed through the process of learning analytics (LA). LA aids educational institutions in improving teaching policies and methods. The LA approaches emphasize on the application of known techniques and tools to address the issues related to the learners and institutional learning mechanisms. The traditional teaching emphasizes on the rote learning but the outcome-based education emphasizes on the development of skills that will aid in enhancing the employability skills of the learners. This chapter proposes a learning analytics model combined with classroom data analytics. The learning skills adopted by the learners are evaluated against the outcome of the course/subjects using the Naive Bayesian classification technique. The performance of the proposed classifier is evaluated against the ZeroR, SimpleCart, Random Tree, and Decision Table classification technique in terms of precision, recall, and accuracy. The results show that the output performance of the proposed model over the existing approaches is improved in terms of accuracy by a factor of 80%.
