Three-Way Data Detective Work Exposes Hidden CT Curriculum Gap Behind Licensure Slump

When a cohort of radiological sciences graduates at King Saud University posted an unexpectedly weak showing on Saudi Arabia’s national licensure examination in 2024, the obvious question was where the curriculum had failed them. A new study argues that the answer cannot come from any single source of evidence, and it backs that claim with an unusually thorough forensic exercise: mapping 33 courses and 135 credit hours against an eleven-section national examination blueprint, then cross-checking the map against 14,203 student-course records spanning fourteen semesters, and finally against the verified examination outcomes of 202 graduates. The three lines of evidence converged on one suspect: computed tomography.

The study, published in BMC Medical Education by Layal K. Jambi of King Saud University and Saeed M. Kabrah of Umm Al-Qura University, addresses a persistent weakness in health professions education. Most curriculum gap analyses rely on curriculum mapping alone, essentially a paper exercise in which course content is compared with the topics an examination will cover. The problem is that a coverage gap on paper does not necessarily translate into a performance deficit in practice, and vice versa. A course may nominally cover a topic while students underperform on it, or a thin syllabus may be compensated by strong clinical placements. Without independent confirmation, curriculum committees can end up redesigning courses that were never the problem, or overlooking the ones that were.

To resolve this ambiguity, the researchers built a three-source triangulation framework. Source one was the curriculum map itself: every course in the radiological sciences program was weighted according to how deeply it covered each section of the Saudi Radiologic Technologist Licensure Examination blueprint, with primary coverage weighted at 1.00, secondary coverage at 0.50, and tertiary coverage at 0.25. From these weights the team computed a coverage ratio for each of the eleven blueprint sections, quantifying exactly how much curricular attention each examination domain received. Source two was longitudinal student performance: fourteen semesters of course marks, aggregated to the domain level and compared against the program-wide mean, revealing whether students actually struggled where coverage was thin. Source three, used as corroboration rather than proof, was the official licensure examination performance of graduates from 2023 to 2025.

The technical centerpiece of the analysis is a three-tier risk typology that the authors introduce to classify gaps. A coverage gap exists when the curriculum map shows deficient coverage and student performance in that domain is also below par, meaning the deficit is both documented and felt. A recognition gap describes a domain where the deficit is acknowledged but not yet fully addressed, for example because no dedicated standalone course exists. A borderline classification flags domains that warrant monitoring without immediate intervention. This typology turns what is often a subjective judgment call into a structured, replicable decision rule, which is precisely what curriculum quality assurance processes in regulated health programs tend to lack.

What the triangulation revealed was striking. The computed tomography domain had the lowest curriculum coverage ratio of all eleven sections, at 0.74, meaning the program’s courses covered the CT portion of the national blueprint far less thoroughly than any other domain. It also recorded the lowest domain average mark in the entire program, 84.82 percent, which sits 1.54 percentage points below the program mean of 86.36 percent. Two independent evidence sources, one structural and one behavioral, pointed at the same target. The third source then added temporal corroboration: the 2024 graduate cohort, whose coursework partially overlapped with a documented decline in CT teaching performance, achieved the weakest licensure result of the three years studied.

That decline deserves attention in its own right. The core CT techniques course, RAD 472, fell from an average mark of 86.46 percent in the second semester of the 1445 Hijri year to 68.30 percent in the corresponding semester of 1446, before partially recovering to 76.92 percent in the first semester of 1447. A swing of nearly eighteen percentage points in a single specialized course is not statistical noise; it is the kind of signal that curriculum monitoring systems are supposed to catch in real time. The study’s framework shows how such a signal, once aggregated to the domain level and compared with the program mean, becomes visible even in large administrative datasets that institutions already collect but rarely analyze in this integrated way.

The licensure outcomes provided the external validation. Pass rates on the Saudi Radiologic Technologist Licensure Examination were 88.89 percent in 2023, dropped to 76.00 percent in 2024, and rebounded to 87.95 percent in 2025. The 2024 cohort, the one whose coursework overlapped with the CT performance dip, passed with the narrowest margin above the cutoff, scoring just 30 points above the 550-point threshold on the 1000-point scale. The authors are careful about the logic here: examination outcomes are treated as corroborative evidence only, not as proof of causation, because cohort-level pass rates reflect many factors beyond any single domain. But the temporal association, layered on top of a documented coverage deficit and a documented performance deficit, gives the CT finding what the researchers call the strongest convergent evidence in the entire analysis.

The framework also caught a second, structurally different problem. Angiography and fluoroscopy were classified as dual-confirmed recognition gaps, because the program offers no dedicated standalone courses in these modalities. Unlike the CT case, where a course exists but underperformed, this is a gap of absence rather than of quality. The distinction matters operationally: fixing a recognition gap means creating new curricular capacity, whereas fixing a coverage-and-performance gap like CT means strengthening existing courses. A single-source analysis using only curriculum mapping would have flagged both problems identically as coverage shortfalls, obscuring the different remedies each requires.

One further finding adds a dimension that curriculum maps alone could never reveal. Across CT, magnetic resonance imaging, and ultrasound courses, the study observed a consistent gender performance gap of four to five percentage points between male and female students. Because the analysis pooled fourteen semesters of records, this pattern emerged with a clarity that single-cohort comparisons rarely achieve. The authors do not over-interpret the finding, but its consistency across three imaging modalities suggests a systemic factor worth investigating, and it illustrates a broader virtue of the triangulation approach: longitudinal administrative data, when aggregated thoughtfully, can surface equity issues that remain invisible in blueprint documents and examination statistics alike.

The wider significance of the study lies in its replicability. Health professions programs worldwide operate under licensure regimes, from the American Registry of Radiologic Technologists in the United States to equivalent bodies in Canada and elsewhere, and most face the same challenge: demonstrating that their curricula genuinely prepare graduates for the examinations that gate entry to practice. The three-source framework requires no new data collection, only the integration of records that accredited institutions already maintain, weighted curriculum maps, longitudinal grade records, and official examination outcomes. By converting these into coverage ratios, domain-level performance deltas, and a structured risk typology, the method transforms curriculum review from an episodic, judgment-heavy exercise into a continuous, evidence-driven quality assurance loop. For a field where a single weak domain can measurably suppress pass rates, that shift may prove as important as any individual finding about computed tomography.

Subject of Research: Curriculum gap analysis in radiological sciences education using triangulation of curriculum mapping, student performance, and licensure examination outcomes

Article Title: Triangulating curriculum gaps in radiological sciences education: a longitudinal multi-source analysis of blueprint alignment, student performance, and national licensure outcomes

Article References: Jambi, L. K., & Kabrah, S. M. (2026). Triangulating curriculum gaps in radiological sciences education: a longitudinal multi-source analysis of blueprint alignment, student performance, and national licensure outcomes. BMC Medical Education. https://doi.org/10.1186/s12909-026-10591-2

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10591-2

Keywords: curriculum alignment, radiological sciences education, licensure examination, gap analysis, computed tomography, medical education, student performance, curriculum mapping, Saudi Arabia, health professions education, quality assurance, triangulation