Using generative AI to support inclusion: insights from a psychological perspective

This article considers the insights of viewing (Artificial Intelligence) AI personalization from a psychological perspective by offering detailed consideration of the psychological constraints, both cognitive and socio-emotional, to the current and future application of personalized AI solutions in higher educational settings. It maps the relationship between AI personalized solutions and psychological substrates to illustrate how and why AI is an effective way to promote inclusion. Consideration of psychological infrastructure and the skills that support effective learning highlights the importance of individual differences and reminds us that diversity is present in all students, not only those with disabilities. Learner profiles are variable, and the application of a psychological lens provides a way to conceptualise and operationalise this variability by utilising the concept of psychological barriers and enablers. Psychological attributes such as working memory, executive function, metacognition, self-esteem and motivation can influence learning in a positive or negative manner depending on the degree to which they are present; for example, low working memory capacity is a barrier, but high capacity is an enabler. This variability allows them to be targeted and developed. Human intelligence, unlike artificial intelligence, is psychologically constrained, so AI personalisation must be psychologically informed to maximise its educational and inclusive potential.