2026· International Conference on Design Science Research in Information Systems and Technology· pp. 191-208· 0 citations· 65 references
Computer Science
TL;DR
Effectiveness analysis reveals that delivery order predicted learning behavior, positioning orchestration as a key design concern for AI-assisted educational systems.
Artificial intelligence (AI) has expanded the capacity of educational systems to support learner modelling, performance prediction, adaptive resource recommendation, automated feedback, and conversational tutoring. However, existing AI-based personalized learning systems commonly employ these capabilities as separate t...
Vishaliney Pirathap, S. Arunprakash, M. S. S. Mayadunna· International Journal of Lat...· 0 citations
AgentForge is presented, an immersive learning system in which novices take on one of four software-engineering roles: Task Planner, Patch Author, Code Reviewer, or Test Runner, within a multi-agent code-repair workflow, which clarifies role-specific responsibilities, makes agent coordination and intermediate artifacts...
Autonomous artificial intelligence (AI) agents can now log into a learning management system, read course materials, and complete unproctored, asynchronous assessed work end-to-end with no student involvement. We document that capability and trace its consequences for assessment validity. Three demonstrations on a live...
Stavros P. Hadjisolomou, R. El-Haddad· Intersection: A Journal at t...· 0 citations
Generative artificial intelligence offers new ways to support personalized learning, yet many existing applications emphasize content generation without fully connecting learning evidence, instructional intervention, and subsequent evaluation. Adopting a design and development research approach, this study designs a mu...
Chenwei Liu, Li Xiao· Journal of Contemporary Educ...· 0 citations
Continual learning models offer a transformative approach to artificial intelligence (AI) in education by enabling systems to incrementally adapt to new tasks and data while preserving previously acquired knowledge. This stands in contrast to static AI systems, which are trained once on fixed datasets and cannot ev...
Ghazal Barari, Alyssa Ann DeNaro Dewees, Nicki Barari· International Conference on...· 0 citations
The rapid adoption of artificial intelligence (AI) in higher education raises a critical challenge: how can student learning be assessed when AI systems are readily available to solve complex problems? Designing AI-proof problems that reliably assess student mastery is often infeasible. To address this challenge, thi...
Jarkko Hurme, Lassi Korhonen, Henry Lähteenmäki et al.· Technology, Knowledge and Le...· 0 citations
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