Design agentic AI learning platforms to support psychological needs and social-presence affordances¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Based on the validated model, the article states that "AI learning platform developers can gain insights from this model to design Agentic AI-enabled learning platforms" and that instructors can draw insights for introducing effective agentic AI interventions. The strategy is to build in supports for autonomy, competence, and relatedness (e.g., self-paced learning, progress monitoring, step-by-step explanations, empathetic feedback) and for interactivity, information sharing, and collaborative environment, since these were the antecedents of motivation and social presence in the model.

Design Implications¶

Context¶

Requirements¶

• Platform features must actually be experienced by learners as supportive of autonomy, competence, relatedness, interactivity, information sharing, and collaboration

Constraints¶

• Recommendations rest on perception-based cross-sectional data; the article notes conclusions refer to learners' perceptions, not objective academic performance measures

Target Learners¶

• higher education students using AI-supported online learning

Target Learning Goals¶

• learning motivation
• social presence
• learner engagement

Affordances¶

• Gdct Sdt Spt Integrated Agentic Ai Framework

Related Strategies¶

Examples¶

-

Key Sources¶

• Dhanya Pramod and Kanchan Pranay Patil. (2026). Agentic AI in educational environments and its association with social and motivational pathways to learning performance. Discover Education. https://doi.org/10.1007/s44217-026-02168-4