DATA-DRIVEN QUALITY CONTROL SYSTEMS IN HIGHER EDUCATION: ROLE OF LEARNING ANALYTICS AND ACADEMIC DASHBOARDS IN PERFORMANCE MONITORING

Abstract

As changes in higher education systems become more complex and the requirements for accountability, transparency, and measurable outcomes have also increased; there is a growing demand for quality assurance systems that are more responsive to institutions’ needs. Current quality control systems rely mainly on retrospective reporting and scheduled evaluations; these approaches do not provide timely feedback for continuous improvement. Rapidly changing teaching and learning environments, due to digitalization, have provided higher education institutions with a vast amount of educational data to support the development and implementation of data-driven methods of assessing and improving academic achievement. This paper will discuss how data-driven quality control systems have evolved, have been adopted and can be implemented in higher education, specifically focusing on the use of learning analytics and academic dashboards as tools for performance monitoring and institution-level decision making. Learning analytics and dashboard technologies support the ongoing collection, analysis, visual display, and interpretation of learner and institutional data. Therefore, stakeholders will be able to move from making judgments based solely on intuition to taking evidence-based action. Universities will use these systems to monitor student engagement, determine academic progress in real time, identify learners who may be at risk of not succeeding, and assess the effectiveness of instructional strategies. Although much of the focus of prior research has been on analytical theory, models & theoretical benefits of analytics and not the empirical analysis of empirical analytics and how these are integrated in quality assurance systems or how they influence day-to-day academic practice; therefore, there is still a lack of understanding around how effective these technologies are and the impact they have on organisations within institutions.  This research will begin to address that lack of understanding through an exploration of how learning analytics and academic dashboards are used within higher education institutions as part of performance monitoring. A mixed-methods research design was developed to gather measurable outcomes and understand human experiences related to the use of analytics. Quantitative data from performance indicators at the institution-level such as retention rates, course completion rates and engagement measures for students were collected to examine the correlation between use of dashboards and academic performance outcomes; in addition, qualitative data from interviews with faculty, administrative