An efficient approach to investigate the learner performance in academia

Abstract Now a days, teaching and learning process demands a lot of supervision and analysis to provide quality and easy understanding of subject concepts. Though a lot of innovative approaches are introduced, still looks for efficient mechanism to broadcast the concepts understanding. Many students lose their interest in studies due to traditional way of teaching and memorizing the answers. In addition to that, the assortment of multiple language people and various family background, the investigation of individual student performance still lacks with existing traditional techniques. This paper introduces a novel approaches to deal the students information in higher education level and suggest the hybrid machine learning approaches to provide high quality and amicable education content. The proposed approach investigates ten different traditional machine learning algorithms and finds the optimal solutions. The investigated techniques are evaluated qualitatively and quantitatively using different datasets and yields plausible performance by addressing various challenges.