AI in Education: Cognitive, Social, Affective, and Ethical Impacts on Human Behavior based on Human-Computer Interaction Theories
Keywords:
Artificial Intelligence, Ethical Impacts, Human Behavior, Human-Computer InteractionAbstract
Incorporating Artificial Intelligence (AI) in education is reforming the dynamics of teaching and learning. Due to this, behavioural changes among students and educators triggered by using AI technologies must be studied. In this research, these behavioural changes among individuals in the academe were investigated, particularly in the cognitive, social, affective, and ethical dimensions of Human-Computer Interaction (HCI) theory. Based on a comprehensive literature review, this study examines how AI tools affect cognitive engagement, social interaction, emotional responses, and ethical decision-making. These impacts on behaviour in the educational setting were examined through HCI theories like Distributed Cognition, CASA (Computers as Social Actors), Affective Computing, and Socio-Technical Theory. Positive behavioural outcomes include enhanced cognitive support through reduced mental load, improved collaboration via AI-mediated platforms, increased emotional engagement through adaptive content, and tougher academic integrity enabled by AI-driven proctoring and plagiarism detection systems. However, the paper also identifies critical negative consequences such as cognitive over-reliance, diminished metacognitive reflection, reduced interpersonal interactions, cultural misinterpretation of emotions, and ethical concerns such as surveillance and algorithmic bias. The findings suggest that while AI tools can support human learning and teaching processes, their design and deployment must be guided by ethical principles and pedagogical considerations to allay risks. The study concludes with a call for thoughtful, human-centred AI integration in education that upholds fairness, engagement, and ethical standards.
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