A Framework for Implementation of Learning Analytics and Educational Data Mining in Traditional Learning Environment

The use of the learning analytics (LA) and educational data mining (EDM) is going on from the last two decades. LA is a human-lead process which predicts learners’ performance as well as identifying potential problematic issues of the learner as the EDM translates the data into meaningful actions to support and empower the learning. In literature, these practices are used for online learning platform. In face-to-face teaching, these practices are rarely applied. The academic analytic systems are used for collecting the student, teacher and course data, but unable to create actionable and perceptive reports to the educational stakeholders. This paper designed a model for implementation of LA and EDM practices in face-to-face teaching environment. The model used the data about student’s continuous evaluation marks, the question paper or learning events used for the assessment. The different processes are generating the reports from it. The system is implemented by R. Shiny.