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cs.AI2026

Measuring Curriculum Alignment across Topical Coverage, Competency, and Cognitive Depth: A Longitudinal Framework Applied to CS2013 and CS2023

Sherzod Turaev, Mary John, Saja Aldabet +3

Undergraduate computer science is governed by international curricular guidelines revised about once a decade, yet programs lack a reliable way to measure how completely they cover…

cs.AI2026

An NLP-Driven Framework for Curriculum-Labor Market Alignment: Schema-Constrained LLM Extraction, ESCO-Anchored Semantic Matching, and Multi-Dimensional Gap Quantification

Sherzod Turaev, Mary John, Mamoun Awad +2

Schema-constrained information extraction from diverse educational and labor-market corpora remains an open challenge in natural language processing because existing pipelines rely…

cs.AI2026

The Nonverbal Syntax Framework: An Evidence-Based Tiered System for Inferring Learner States from Observable Behavioral Cues

Sherzod Turaev, Mary John, Jaloliddin Rustamov +4

Understanding learners' cognitive and affective states underpins adaptive educational systems and effective teaching. Although research links nonverbal cues to internal states, no…

cs.AI2026

Abnormal Head Movements in Neurological Conditions: A Knowledge-Based Dataset with Application to Cervical Dystonia

Saja Al-Dabet, Sherzod Turaev, Nazar Zaki

Abnormal head movements (AHMs) manifest across a broad spectrum of neurological disorders; however, the absence of a multi-condition resource integrating kinematic measurements, cl…