Improving Didactic Teaching and Learning Outcomes: A Framework for Sensor based Approach in Education

Abstract

Learner monitoring is key to personalized education. Technology can be used extensively to capture and improve learning and didactic teaching outcomes. The paper examines pioneering application cases of sensors and management systems, learning, content, and awareness; for delivery, supervision, assessment, and social interaction; and to measure, monitor, and offer real-time learning outcomes. Educational intelligence, emerging as a prominent trend in student data and management systems, empowers data-driven decision-making, planning, and forecasting within the educational landscape. Our work provides a 3-step framework for inferential analysis on heterogeneous datasets.