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Record W2011854261 · doi:10.1111/medu.12649

Self‐regulated learning in simulation‐based training: a systematic review and meta‐analysis

2015· review· en· W2011854261 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Education · 2015
Typereview
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsPsychological interventionContext (archaeology)Meta-analysisScopusPsychologyMedical educationSystematic reviewMEDLINEIntervention (counseling)Educational measurementMedicineNursingCurriculumPedagogyInternal medicine

Abstract

fetched live from OpenAlex

CONTEXT: Self-regulated learning (SRL) requires an active learner who has developed a set of processes for managing the achievement of learning goals. Simulation-based training is one context in which trainees can safely practise learning how to learn. OBJECTIVES: The purpose of the present study was to evaluate, in the simulation-based training context, the effectiveness of interventions designed to support trainees in SRL activities. We used the social-cognitive model of SRL to guide a systematic review and meta-analysis exploring the links between instructor supervision, supports or scaffolds for SRL, and educational outcomes. METHODS: We searched databases including MEDLINE and Scopus, and previous reviews, for material published until December 2011. Studies comparing simulation-based SRL interventions with another intervention for teaching health professionals were included. Reviewers worked independently and in duplicate to extract information on learners, study quality and educational outcomes. We used random-effects meta-analysis to compare the effects of supervision (instructor present or absent) and SRL educational supports (e.g. goal-setting study guides present or absent). RESULTS: From 11,064 articles, we included 32 studies enrolling 2482 trainees. Only eight of the 32 studies included educational supports for SRL. Compared with instructor-supervised interventions, unsupervised interventions were associated with poorer immediate post-test outcomes (pooled effect size: -0.34, p = 0.09; n = 19 studies) and negligible effects on delayed (i.e. > 1 week) retention tests (pooled effect size: 0.11, p = 0.63; n = 8 studies). Interventions including SRL supports were associated with small benefits compared with interventions without supports on both immediate post-tests (pooled effect size: 0.23, p = 0.22; n = 5 studies) and delayed retention tests (pooled effect size: 0.44, p = 0.067; n = 3 studies). CONCLUSIONS: Few studies in the simulation literature have designed SRL training to explicitly support trainees' capacity to self-regulate their learning. We recommend that educators and researchers shift from thinking about SRL as learning alone to thinking of SRL as comprising a shared responsibility between the trainee and the instructional designer (i.e. learning using designed supports that help prepare individuals for future learning).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.840
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.157
GPT teacher head0.486
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it