DEVELOPING AN OPEN-SOURCE LEARNING ANALYTICS TOOL FOR PROVIDING INSIGHTS TO SUPPORT STUDENTS AND IMPROVE TEACHING PRACTICE
Year: 2024
Editor: Grierson, Hilary; Bohemia, Erik; Buck, Lyndon
Author: Covill, Derek; Tooze, James; Prieto Cabrera, Pablo; Owen Lloyd, Gareth; Grundy, Cate
Series: E&PDE
Institution: University of Brighton, United Kingdom
Page(s): 639 - 644
DOI number: 10.35199/EPDE.2024.108
ISBN: 978-1-912254-200
ISSN: 3005-4753
Abstract
This abstract introduces the development of a course level data analytics tool which we’ve called ‘the student record’. This tool aims to transition our course team away from a passive, standardised, compliance-centric institutional approach to instead complement this with a responsive, context-specific and user-centred approach to gathering, analysing and presenting student attendance data at course level. The student record is a relatively simple MS Excel-based system which uses a long-standing total quality management approach (statistical process and control - SPC), as a framework for identifying patterns and interpreting data. This framework helps us gain statistically significant insights which are presented on a configurable dashboard showing flags and recommendations. We feel the tool informs and promotes a more dynamic ‘student engagement’ dialogue between staff and students. In effect it facilitates a rolling academic ‘health check’ to help provide support for students, as well as key contextual insights for module teams and course leaders. One key attribute of the tool is that it exploits the natural language interface of the ‘Analyse Data’ tool in Excel. It is driven by artificial intelligence in way that is similar (but somewhat more limited) than more open systems such as Chat GPT, Bard and others. Importantly it allows staff to ask questions of the data within Excel itself, without having to write complicated formulas and can provide high-level visual summaries, trends, and patterns using automatically created ‘Pivot Tables’. This has empowered staff with data insights that were previously unattainable or excessively time-consuming using institutional systems. Central to our approach is the system's legacy development - building a long term knowledge-base to facilitate decision-making that is grounded in robust historical records rather than anecdotal observations or longstanding assumptions in order to foster an evidence-based practice. Ethical considerations are also at the forefront of our system design, where transparency and data privacy are key, and where accessibility for students’ own data is a priority and is encouraged. For example, the presentation to students of their own data forms part of our personal academic tutorial system where students meet with their personal academic tutors three times per year. The intention here is to foster a reflective learning process and continuous professional development while maintaining data security using simple in-house data management systems. The full paper will provide a more detailed description of the tool and an evaluation of its capabilities, as well as a critical discussion of the key aspects of its development as mentioned above (e.g. AI, data security, ethics).
Keywords: attendance monitoring, ethics, information system, contextual insights