This study explores the integration of a multi-agent AI system designed to support self-regulated learning (SRL) in computer science education. Building on preliminary work that introduced a Teaching Assistant AI (TA-AI) for real-time scaffolding, an Analytics-AI for pattern recognition, and an AI-Improver for iterativ...
Jing Huang, Seong Min Park, M. P. Lin et al.· CoED· 0 citations
Checkpoint-resolved, per-head analysis under fixed selection rules can expose sparse temporal organization in other factorized video diffusion transformers and, with adapted routing metrics, in joint spatio-temporal architectures.
Taewoo Ha, Shafayat Mowla Anik, Dae Yeol Lee et al.· 0 citations
A classroom-deployed quiz system that combines integrity-preserving hinting (TA-AI), trace summarization (Analytics-AI), and feedback-driven refinement (AI-Improver) to generate instructor diagnostics from routine interaction logs is presented.
M. P. Lin, Daniel H. Chang, V. Janarthanan et al.· International Journal of Eme...· 0 citations
Writing Helper is developed, a multi-agent system that structures iterative revision through four specialized feedback agents (Grammar, Style, Structure, Content) and gamified mastery thresholds, highlighting the importance of pedagogical interface design in L2 writing classrooms.
Yujong Park, Jeeho Ryoo· Language Learning & Tech...· 0 citations
Examining undergraduate students’ AI disclosure practices suggests that institutional AI disclosure frameworks may benefit from addressing both policy compliance and the affective and disciplinary dimensions of students’ SRL decision-making.
Daniel H. Chang, M. Lin, Jing Huang et al.· Frontiers in Education· 0 citations
This work presents Oneiros, a dynamic remapping engine for multi-tenant LLM serving that dynamically repurposes GPU memory allocated for model parameters as KV cache capacity, enabling nonblocking, unidirectional parameter transfer.
