Agentic AI in educational environments and its association with social and motivational pathways to learning performance

The present study assesses the associations of agentic AI-based online learning with learner engagement and perceived learner performance through the learning motivation and perceived social presence pathway. This is done through a cross-sectional, perception-based survey conducted among students of business schools in India through a non-probability sampling design. Students having previous exposure to AI-based online learning platforms in order to acquire academic qualifications were included in this study. A total of 398 valid participants’ data were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Perceived autonomy (β = 0.504, 95% CI: 0.442–0.560), perceived competence (β = 0.425, 95% CI: 0.358–0.491), and perceived relatedness (β = 0.189, 95% CI: 0.109–0.272) had a positive relationship with learning motivation. Interactivity (β = 0.468, 95% CI: 0.404–0.528), information sharing (β = 0.323, 95% CI: 0.248–0.398), and collaborative environment (β = 0.184, 95% CI: 0.112–0.265) had a positive relationship with perceived social presence. Learning motivation (β = 0.533, 95% CI: 0.467–0.598) and perceived social presence (β = 0.493, 95% CI: 0.427–0.558) greatly increased learner engagement, which, in turn, greatly affected perceived learner performance (β = 0.671, 95% CI: 0.615–0.725). The present research integrates both Self-Determination Theory and Social Presence Theory in order to understand the combined effect of learners’ need for psychological learning motivation and their social presence during learning on learner engagement and perceived learner performance in agentic AI-based online learning environments. This research contributes to the literature on agentic AI in higher education, considering the fact that the conclusions refer to learners’ perceptions, not objective academic performance measures.