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Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

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Published on: December 9, 2022

Do teaching staff trust stakeholders and tools in learning analytics? A mixed methods study.

Asma Shannan Alzahrani¹, Yi-Shan Tsai¹, Naif Aljohani²

¹Centre for Learning Analytics, Faculty of Information Technology, Monash University, Melbourne, Australia.

Educational Technology Research and Development : ETR & D

|June 26, 2023

Summary

Teaching staff trust higher education institutions in learning analytics (LA) but distrust third parties regarding data privacy and accuracy. Building trust requires improved data governance and transparent policies for effective LA adoption in higher education.

Keywords:

Higher education Learning analytics Mixed methods Teaching staff Trust

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Area of Science:

Educational Technology
Information Systems
Higher Education Studies

Background:

Learning analytics (LA) adoption in higher education is growing, influenced by factors like stakeholder engagement and data transparency.
Trust is a critical predictor of technology adoption in information systems, yet its specific role in LA adoption remains underexplored.

Purpose of the Study:

To investigate the extent of teaching staff trust in LA stakeholders and technology within higher education.
To identify key factors influencing the adoption of LA, focusing on trust-related barriers and enablers.

Main Methods:

A mixed-methods approach combining surveys and interviews with teaching staff.
Exploration of trust levels in higher education institutions, third-party vendors, and LA technology itself.

Main Results:

Teaching staff exhibit high trust in institutional competence and LA usefulness but low trust in third parties concerning privacy and ethics.
Low trust in data accuracy, stemming from outdated information and inadequate data governance, was also identified.

Conclusions:

Addressing third-party data handling and data accuracy issues is crucial for fostering trust in LA.
Recommendations include enhancing data governance, clarifying data ownership, and improving consent processes to facilitate LA adoption in higher education.