Connecting Education with Reality: AI as a Catalyst for Situated Learning

Vargas, Chiappe & Fontán de Bedout (2026) argue that AI can act as a catalyst for situated learning by connecting education to authentic, real-world contexts. Drawing on Lave & Wenger's (1991) communities of practice and Dewey's (1926) "learning by doing," the essay positions AI — through personalization, data analytics, and realistic simulation environments — as the mechanism to overcome the curricular rigidity, resource scarcity, and lack of immersive tools that block situated learning in "Education 4.0." The teacher's role is reframed from information transmitter to facilitator, and AI is framed as a complement to, not a substitute for, human interaction, with explicit cautions about over-reliance, equity, and data ethics.

Key Findings

• Central claim: AI is the appropriate mechanism to overcome the structural barriers — curricular rigidity, limited resources, lack of immersive-environment tools — preventing effective implementation of situated learning within an "Education 4.0" that personalizes learning and aligns it with real-world work and life.
• Teacher-role shift: AI redefines teachers from transmitters of information to facilitators of situated learning, who use AI analytics and dashboards to design context-specific, responsive activities; teachers play the critical interpretive role linking assessment insights to practical application.
• Personalization & authentic contexts: AI's ability to analyze learner data and simulate real-world scenarios (Duolingo/Rosetta Stone language role-plays, Microsoft HoloLens AR, Osso VR surgical training, Siemens Simcenter industrial simulators) supports personalization and situated decision-making — and positions "authentic" as compatible with "digital."
• Authentic assessment: AI enables continuous, integrated competency-based assessment woven into the learning process rather than external audits of knowledge, moving beyond memorization-focused standardized tests.
• Cautionary limits: The essay flags risks of over-reliance on simulations (eroding skills for performing under real pressure), technological dependency and cost in resource-limited settings, data privacy/security, algorithmic bias, educator resistance, and the need for equitable access — framing AI as a complement, not a substitute, for human interaction.

Connected Concepts

• Experiential Learning
• Embodied Learning
• Constructivist
• AI Education
• Instructional Design
• Teacher Role
• Higher Ed

Connected Articles

• Beyond Detection Authentic Assessment AI 2025 — Beyond Detection: redesigning authentic assessment in an AI-mediated world
• Embodied Inquiry AI Facilitator Physics 2026 — Embodied Inquiry with an AI Facilitator in Physics Education
• Metacognitive Awareness Experiential Vs Instructional — Experiential Versus Instructional Approaches for Eliciting Metacognitive Awareness
• GenAI AR Physics Simulation Prompt 2026 — GenAI-Powered AR Physics Simulations
• Benzion AI Physics Simulations Virtual Lab — AI Simulations and Virtual Labs in Physics

Citation

Vargas, E. G., Chiappe, A., & Fontán de Bedout, L. (2026). Connecting Education with Reality: AI as a Catalyst for Situated Learning. The Educational Forum, 90(2), 237–247.