Analysis of new data sources in modern teaching and learning processes in the perspective of personalized recommendation

Abstract

The increased variety of learning resources have substantially affected learning styles of students, like e-books with modern collaborative tools, video lectures of different teachers across the world, lively discussion boards etc. Having accepted such forms of learning materials, teaching and learning processes in conventional set up do not have a way to capture the data generated out of students’ learning activities involving such resources and use them effectively. This paper analyses data generated by the student’s activities in Compiler of Resources in Engineering and Technology to Aid Learning (CRETAL) restricted to video resources and asserts that they are indeed critically helpful data for teachers/tutoring systems in generating personalised recommendations which are possible only because of said data. CRETAL is the modern learning station, an intelligent system, being developed at author’s institution to facilitate variety of learning resources created and adapted by the faculty and the teachers worldwide to students.