Curricular Analytics

Researchers: Geetha Paulmani

Introduction

Curricular Learning Analytics explores relations between efficiency of student learning with curricular elements such as topics coverage, prerequisite relations among topics, learning outcomes, instructor effectiveness, student workload, students’ capacity, cultural constraints, socio-economic-political influences, and so on. We are looking for insights and evidences from learner interactions with respect to the curricular elements that allow us to measure the degree of achievement of curricular outcomes.

Further description

While we have demos for individual pieces, should we also think about an overarching demo that exemplifies the vision of learning analytics at the curricular level? Can we take up the exercise of identifying learning analytics opportunities in each course in BSc CIS? Suppose we have done that, can we image the flow of data from a variety of sensors from students taking these courses? How much data would that be? What types of data? What kind of support we could offer students and teacher? How do we measure their effectiveness?  Can we imagine and simulate, with fake data, such a curricular encompassing interactive dashboard used by a) a student, b) a teacher, c) a parent, d) a university administrator, and e) a politician?

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