Wellbeing

When developing health-related educational technology or interventions to improve wellbeing, designers and educational technologists should consider multiple complexities, including the challenges related to measuring wellbeing while conducting research.

Artificial Intelligence

To understand AI, and reap the potential of AI for society, we need to be able to identify the difference between AI and Human Intelligence. In addition, since our students and children will experience the greatest impact of AI - both from an employment perspective, but also from cultural and sociological perspectives - we need to evaluate how AI impacts education.

Motivation, Feedback & Mindset

When developing and using educational digital environments, it is important to consider the conditions that are known to promote learning. Exploring the constructs of motivation, feedback and mindset in education helps to understand how EdTech products and services might be enhanced.

Augmenting Human Decision-Making

The exact role of AI in education is not easy to predict and there are still debates over whether it should be developed to assist human cognition or replicate it.  The use of multimodal classification models have been found to assist educators and businesses and provide advanced feedback and reflection.    

Perceived Credibility of Research Evidence

Public perceptions of educational research credibility are uneven, and it is suggested that more work is required of AI in education's stakeholders, chiefly academics and developers, to communicate with the public and recover a potentially misleading reputation of AI in education and more broadly. 

Guided Independent Learning

For the last 30 years there has been an extensive movement to change teaching in Higher Ed through innovative strategies involving independent learning.  Research suggests that providing guidance during independent learning can benefit knowledge acquisition and understanding.