OVERVIEW

Learning Analytics can be defined as; “the measurement, collection, analysis and reporting of data about learners and their contexts at course level (e.g. assessment results from Learning Management System (LMS) and institutional level (e.g. data stored in student information systems, registry, financial systems, and institutional research units), for purposes of understanding and optimizing learning and the environments in which it occurs”.
(Society for Learning Analytics Research (SOLAR) (https://www.solaresearch.org/about/what-is-learning-analytics/) and Educause (2020: p. 20)

This priority relates to an evidence-based approach that leverages analysis of relevant data in order to support learning and teaching change. (And strongly aligns with the QAC Audit theme)
 

For Staff
Learning Analytics Community	Mid-term CTLE	Student Early Alert System	The Scholarship of Learning and Teaching
Surveys	Teaching and Learning Data Warehouse	Teaching & Learning Evaluation and Governance
For Students
Avoiding Plagiarism	Mid-term CTLE

PRINCIPLES

This approach to Learning Analytics reflects the following principles;

• The implementation of the University’s institutional surveys related to teaching and learning, and analysis of data generated therefrom should be aligned to the University’s strategic goals
• The University’s institutional surveys pertain to collective and concerted endeavours among various stakeholders. Therefore, coordination and collaboration are indispensable to effective implementation, meaningful analysis and interpretation of data, and formulation of pertinent recommendations to inform design, development and enhancement of curriculum, co-curriculum and extra-curriculum, as well as teaching and learning
• Individual institutional surveys should have their respective focus, so as to avoid overlapping and to gather specific sets of data, in order to derive specific recommendations at institutional level
• A comprehensive picture of student learning experiences and achievements can be ascertained through triangulating various forms of data and evidence, in order to derive overall recommendations at the institutional level
• A central repository should be in place to store, organize, retrieve and archive current and historical data from various sources, so as to facilitate data analysis, management and retention. The ultimate prototype of such repository should possess certain business intelligence functions, characterized with some customized retrieval, analytical, infographic and presentation functions
• The scholarship of teaching and learning can be enhanced via the collection, analysis and dissemination of findings as an essential aspect of the University’s Quality Assurance (QA) cycle

 

OBJECTIVES

The objectives of this approach to Learning Analytics are to:

• integrate various aspects related to design, administration, data analysis, storage and dissemination, and review of institutional surveys into a comprehensive framework
• collaborate with relevant units/ stakeholders together to develop, monitor and enhance the university’s institutional surveys on continuing basis
• advance the utilization of data and evidence generated therefrom to inform change and development in curriculum and teaching and learning
• enhance the development of the scholarship of teaching and learning