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Article

A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education

Teaching and Learning Centre, Lingnan University, Hong Kong SAR, China
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Academic Editors: Jinan Fiaidhi, Aboul Ella Hassanien and Hye-jin Kim
Systems 2022, 10(4), 96; https://doi.org/10.3390/systems10040096
Received: 4 May 2022 / Revised: 2 June 2022 / Accepted: 14 June 2022 / Published: 5 July 2022
E-learning platforms are being used in higher education to liberate teaching and learning from the constraints of time, pace, and space. These platforms provide rich media content, collaborative assessment, and analytics tools and support learning through a variety of online possibilities. However, the focus of most of this research is on learning analytics inside e-learning platforms and does not cover other related institutional surveys and educator professional development activities. This paper outlines a novel conceptual approach for the creation of a teaching and learning data warehouse analytics system that utilizes a Multi-Dimensional Analysis approach to teaching and learning analytics across these e-learning platforms in combination with other institutional data sources, such as various institutional surveys, tracking of professional development activities, and analysis of the use of the learning management system. The novel teaching and learning data warehouse analytics system (TLDWAS) is being developed at Lingnan University, a leading liberal arts university in Hong Kong. The genesis of this project is analyzing large volumes of teaching and learning data and presenting a big picture for senior management to gain insight from massive amounts of student courses and teacher evaluation data, fill the research gaps mentioned above, and help educators identify problems and solutions more effectively. The TLDWAS provides a visual interface for identifying some indicators and storing, classifying, and analyzing teaching and learning data in various forms to generate statistics, analyze models, and identify meaningful patterns in the data in order to improve teaching and learning. The TLDWAS not only provides more evidence-based decision-making for senior management but is also capable of being applied to identify patterns and relations pertaining to students’ academic performance, usage of e-learning systems, and associated staff development activities. View Full-Text
Keywords: quality assurance; higher education; multi-dimensional analysis; teaching and learning analytics quality assurance; higher education; multi-dimensional analysis; teaching and learning analytics
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MDPI and ACS Style

Li, Q.; Duffy, P.; Zhang, Z. A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education. Systems 2022, 10, 96. https://doi.org/10.3390/systems10040096

AMA Style

Li Q, Duffy P, Zhang Z. A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education. Systems. 2022; 10(4):96. https://doi.org/10.3390/systems10040096

Chicago/Turabian Style

Li, Qingyun, Peter Duffy, and Zhongyang Zhang. 2022. "A Novel Multi-Dimensional Analysis Approach to Teaching and Learning Analytics in Higher Education" Systems 10, no. 4: 96. https://doi.org/10.3390/systems10040096

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