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Conrad Borchers; Tianze Shou – Grantee Submission, 2025
Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are explicitly modeled. We propose a prompt variation framework to assess LLM-generated instructional moves' adaptivity…
Descriptors: Benchmarking, Computational Linguistics, Artificial Intelligence, Computer Software
Kelly J. Williams; Christina Novelli – Grantee Submission, 2025
There is a strong connection between word-reading and spelling development. Students' spelling can provide insight into their word-level reading skills and inform intensive reading interventions delivered within a data-based individualization framework. The purpose of this article is to describe the linguistic knowledge bases that connect word…
Descriptors: Spelling, Word Recognition, Reading Processes, Reading Instruction

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