Abstract
<title>Abstract</title> <p>A college that offers several overlapping computing degrees implicitly assumes that its programs are differentiated in line with the way the labor market segments computing work and that, taken together, they prepare graduates for that market. Testing such an assumption is difficult, because the instruments available to curriculum committees, namely advisory boards, graduate tracer studies, and employer surveys, are slow, narrow, and hard to reproduce. In the current work, we apply a uniform, taxonomy-anchored alignment analysis across all five undergraduate programs of a College of Information Technology, comparing 1,922 course learning outcomes against 103,349 competencies extracted from a unified corpus of 5,186 deduplicated job openings drawn from four boards. Every competency, on both sides, is obtained by a grounded single-language-model procedure that copies it verbatim from the source and verifies it against the source, then assigned to one of eleven ESCO-aligned domains and a Bloom cognitive level, and the curricular supply is read not as a catalog but on a realized-attainment basis that respects the credit-hour and elective constraints under which a student completes a degree. The extraction is validated blind by two independent faculty raters (domain κ = 0.91, Bloom level κ = 0.86), and the ESCO matching is validated using a human-adjudicated gold set (κ = 0.72). The analysis yields four findings. The content gaps are systemic rather than program-specific, concentrated in systems, software engineering, security, and web development; the shared college core satisfies only about a third of the demanded competencies; the programs are well differentiated in disciplinary content yet homogeneous in where they fall short; and the curriculum is aligned roughly a full Bloom level below the market across the portfolio, most acutely in systems. We discuss the implications for program design, for curriculum governance, and for the practice of curriculum analytics.</p>