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Data · dataset · 2026

Study 3: Supporting self-regulated learning during diagnostic reasoning in dental students: A mixed-methods comparison of three approaches

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Description

Summary

This mixed-methods comparative intervention study examined three approaches to supporting self-regulated learning (SRL) during authentic diagnostic reasoning tasks in workplace-based dental education: preparatory Prompt-Based SRL Support (PBS), Clinical Scaffolding SRL Support (CSS), and Combined Support (CS). Eighty-six fourth- and fifth-year dental students participated. SRL skills were assessed microanalytically and diagnostic reasoning performance was assessed using the Assessment of Reasoning Tool–Reconstructed (ART-R) across 211 observed clinical case presentations.

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Diagnostic reasoning was independently rated by a clinical supervisor and a research-team member for each presentation, yielding 422 ART-R assessments; the observation-level ART-R global score was calculated as the mean of the two independent ratings. Three focus groups with 13 students explored experiences of the three support approaches, including planning, monitoring, reflection, feedback, confidence, and perceived learning.

Datafiles The dataset accompanying this descriptor contains two files. • Study3_Quantitative_Data_EN_Deidentified.xlsx: De-identified quantitative dataset presented in English. The workbook contains an observation-level dataset for the 211 clinical presentations, the 422 individual ART-R ratings, and the de-identified analytic dataset used for statistical modelling. Original student, observation, and rater codes were replaced with repository-specific identifiers, and no re-identification key is included. • Study3_FocusGroup_Qualitative_Data_EN_Deidentified.docx: De-identified qualitative data derived from the final focus-group analysis.

The file consolidates coded excerpts from the three intervention groups (PBS, CSS, and CS), organised by analytical code. It contains analysed excerpts rather than full transcripts. Original ATLAS.ti quotation numbers, source filenames, participant labels, and selected potentially identifying contextual details were removed or generalised.

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Catalogue records · 1

Topics

Stated by source
Social Sciences
Inferred from text
Dentistry 72%
Provenance · 1 source records, 10 field assertions
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IISH Dataversedoi:10.34894/9RZZPU12 d agoJSON v1
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concepts[field].local:field:medicine-healthmapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
concepts[field].local:field:social-sciencemapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
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