🏷️ Concept
Well-Being
Well-being — the positive state of being mentally, physically, and socially healthy, encompassing emotional, psychological, and social dimensions. In AI in education, well-being has become a central concern because the rapid integration of generative AI into learning environments can affect students' and educators' mental health, motivation, belonging, anxiety, and sense of agency — raising questions about whether AI supports or undermines learners' well-being.
Well-being in education is multifaceted: it includes emotional well-being (positive affect, low distress), psychological well-being (purpose, autonomy, competence), and social well-being (belonging, positive relationships). In the AI era, well-being matters because AI can reshape learning in ways that affect these dimensions — from reducing students' confidence and increasing anxiety about academic integrity, to fostering or undermining engagement and belonging. Concerns about AI's impact on students' socio-emotional skills, well-being, sociability, and sense of trust and empathy (raised by the OECD and others) have positioned well-being as a key consideration in responsible AI integration.
How well-being appears in the research
Well-being as a design consideration
A recurring theme is that well-being should be a deliberate design consideration in AI in education, not an afterthought. This means: designing AI to support rather than replace human relationships; ensuring students can maintain agency and confidence rather than experiencing AI-induced anxiety or over-reliance; supporting educators' capacity and well-being as they integrate AI; and evaluating AI systems not only for learning outcomes but also for their effects on students' and teachers' well-being. Research connects well-being to Motivation, Self Regulated Learning, and Student Experience (belonging and engagement).
Connections to related concepts
Well-being connects to Student Experience (as a dimension of learners' overall experience), Social Emotional Learning and Affective Computing (the emotional competencies AI intersects with), Ethics (as a core ethical consideration), Motivation and Self Regulated Learning (well-being supports and is supported by these), Teacher AI Competency (educators' capacity and well-being), and Higher Ed and K 12 as the settings where AI shapes well-being.