Massey University

Measuring plagiarism: researching what students do, not what they say they do

John Walker

2009 · 231 Zit.

Learning analytics dashboard: a tool for providing actionable insights to learners

Teo Sušnjak, Gomathy Ramaswami, Anuradha Mathrani

2022 · 183 Zit.

ChatGPT: The End of Online Exam Integrity?

Teo Sušnjak, Timothy R. McIntosh

2024 · 122 Zit.

Artificial intelligence (<scp>AI</scp>) and machine learning (<scp>ML</scp>) based decision support systems in mental health: An integrative review

Oliver Higgins, Brooke Short, Stephan K. Chalup et al.

2023 · 118 Zit.

Beyond Predictive Learning Analytics Modelling and onto Explainable Artificial Intelligence with Prescriptive Analytics and ChatGPT

Teo Sušnjak

2023 · 81 Zit.

Mitigating Cognitive Biases in Developing AI-Assisted Recruitment Systems

Melika Soleimani, Ali Intezari, David J. Pauleen

2021 · 66 Zit.

From COBIT to ISO 42001: Evaluating cybersecurity frameworks for opportunities, risks, and regulatory compliance in commercializing large language models

Timothy R. McIntosh, Teo Sušnjak, Tong Liu et al.

2024 · 61 Zit.

Current stance on predictive analytics in higher education: opportunities, challenges and future directions

Rahila Umer, Teo Sušnjak, Anuradha Mathrani et al.

2021 · 40 Zit.

Artificial intelligence: An eye cast towards the mental health nursing horizon

Rhonda Wilson, Oliver Higgins, Jacob Atem et al.

2023 · 29 Zit.

Telehealth as a Means of Enabling Health Equity

Craig Kuziemsky, Inga Hunter, Jai Ganesh Udayasankaran et al.

2022 · 26 Zit.

Discovering students' continuous intentions to use ChatGPT in higher education: a tale of two theories

Christine Nya-Ling Tan, Mcxin Tee, Kian Yeik Koay

2024 · 25 Zit.

A Reasoning and Value Alignment Test to Assess Advanced GPT Reasoning

Timothy R. McIntosh, Tong Liu, Teo Sušnjak et al.

2024 · 24 Zit.

The evolving field of learning analytics research in higher education

Megan Axelsen, Petrea Redmond, Eva Heinrich et al.

2020 · 23 Zit.

Reducing AI bias in recruitment and selection: an integrative grounded approach

Melika Soleimani, Ali Intezari, James Arrowsmith et al.

2025 · 14 Zit.

AI explainability in oculomics: How it works, its role in establishing trust, and what still needs to be addressed

Songyang An, Kelvin Yi Chong Teo, Michael V. McConnell et al.

2025 · 6 Zit.