Evidence map›Paper›PMID 40550955›Full record

ReviewAnatomical sciences education2025

Lessons learned from conducting assessments in radioanatomy courses on learning management systems.

Christian Grévisse, Françoise Kayser

Abstract readReview
In one paragraph

Review in Anatomical sciences education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Christian GrévisseDepartment of Life Sciences and Medicine, Université du Luxembourg, Esch-sur-Alzette, Luxembourg.ORCID https://orcid.org/0000-0002-9585-1160
Françoise KayserDepartment of Radiology, CHU UCL Namur, Université Catholique de Louvain, Yvoir, Belgium.ORCID https://orcid.org/0000-0002-2151-9253

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radioanatomy, short for radiographic anatomy, is the study of anatomy through medical imaging. Its early-stage introduction into medical curricula has been recommended in the literature. As with many other medical courses, it has seen a shift toward blended learning, including assessment on learning management systems such as Moodle, one advantage being automatic or at least assisted grading. The majority of previous studies in the realm of radioanatomy report only on the usage of multiple choice questions, due to several challenges related to computer-based assessment. Nonetheless, we encourage radioanatomy teachers to include a more diverse set of question types. We consolidated the lessons learned during our experience over three academic years of carrying out summative assessments in radioanatomy courses on Moodle. Among others, we discuss technical aspects such as image optimization. Providing a lexicon for standardized answers fosters automatic grading. A student survey supports the idea of using stack visualizations for better image interpretation. We finally underline the importance of collaboration between different stakeholders to ensure a smooth assessment preparation, execution, and analysis. These findings offer valuable insights for improving e-assessment in radioanatomy and potentially other medical courses.

Indexed as

AnatomyComputer-Assisted InstructionEducational MeasurementEducation, Medical, UndergraduateRadiologyCurriculumHumansLearningRadiographyStudents, MedicalSurveys and Questionnairesassessmentlearning management systemradioanatomy

Identifiers

PMID40550955
PMCPMC12413473

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.