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COJ Robotics & Artificial Intelligence

Extractive Analytics in Higher Education: A Conceptual Framework

  • Open or CloseRanjan Vaidya*

    Department of Business Information Systems, Auckland University of Technology, Auckland, New Zealand

    *Corresponding author:Asad Ullah, Assistant Professor, Middle East College, Muscat, Oman

Submission: March 13, 2024;Published: April 01, 2024


Research and teaching in higher education institutions have seen increasing use of information systems. Currently, the focus of data analytics is mainly on one stakeholder group, the students. The other important stakeholder groups that can benefit from big data analytics are the instructors and the management. Studies have also called for a more inclusive approach in using data analytics in higher education. Our study addresses these calls and focuses on the instructors and how analytics can reduce the workload of instructors. Specifically, we present two example situations in which analytics can help instructors. Based on the characteristics of these examples, we conceptualize a new type of analytics and call it extractive analytics. We further suggest that extractive analytics forms an analytical layer that is fundamental to analytics.

Keywords:Extractive Analytics; Higher Education; R Language; Research

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