Learning Analytics: Gamification in Flipped Classroom for Higher Education

Abstract

Abstract: The Flipped classroom is an innovative pedagogical model that has been adopted in various colleges across different disciplines. The Flipped classroom allows the students to actively participate and collaborate during in-class activities. The measure of learner's performance, cognitive skills, and behaviour is essential in any teaching-learning process to assess and improvise the curriculum, syllabus, learning methodology, and educational technology. In this research work, various innovative teaching models suitable for Gen Z learners have been experimented with. These models included a virtual classroom, laboratory sessions, and flipped classrooms that were compared with the traditional classroom approach. A new model “CAM-S” is proposed to measure the Cognitive, Affective, and Motivational traits and identify slow learners. Learning analytics using the K-Means clustering algorithm is performed to analyze the behaviour and learning patterns of the learners in these pedagogical models. From the clusters obtained, the students were categorized into 3 different groups based on their performances. The result obtained after the analysis shows that Flipped Classroom has better learner performances when compared with the otherpedagogical methodologies. Additionally, separate questionnaires are also created to obtain feedback from the students about their experiences with the 3 pedagogical techniques used. Even the behavioural models are analyzed using the gaming environment in the flipped classroom. Keywords: Blended Learning, Clustering algorithm, Flipped Classroom, Gamification, Learning Analytics.