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Record W4313332060 · doi:10.1186/s12909-022-03966-8

Does your group matter? How group function impacts educational outcomes in problem-based learning: a scoping review

2022· review· en· W4313332060 on OpenAlexaff
Athena Li, Elif Bilgiç, Amy Keuhl, Matthew Sibbald

Bibliographic record

VenueBMC Medical Education · 2022
Typereview
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCINAHLContext (archaeology)Medical educationPsychologyExperiential learningCurriculumProblem-based learningMEDLINEMedicineNursingPedagogyPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Problem-based learning (PBL) is a common instructional method in undergraduate health professions training. Group interactions with and within PBL curricula may influence learning outcomes, yet few studies have synthesized the existing evidence. This scoping review summarized the literature examining the influence of group function on individual student PBL outcomes. Following Kirkpatrick's framework, experiential, academic, and behavioral outcomes were considered. The impacts of three aspects of group function were explored: (1) Group Composition (identities and diversity), (2) Group Processes (conduct and climate, motivation and confidence, and facilitation), and (3) PBL Processes (tutorial activities). METHODS: A literature search was conducted using Medline, CINAHL, and APA PsychInfo from 1980-2021, with the help of a librarian. English-language empirical studies and reviews that related group function to learning outcome, as defined, in undergraduate health professions PBL curricula were included. Relevant references from included articles were also added if eligibility criteria were met. The methods, results, discussions, and limitations of the sample were summarized narratively. RESULTS: The final sample (n = 48) varied greatly in context, design, and results. Most studies examined junior medical students (n = 32), used questionnaires for data collection (n = 29), and reported immediate cross-sectional outcomes (n = 34). Group Processes was the most frequently examined aspect of group function (n = 29), followed by Group Composition (n = 26) and PBL Processes (n = 12). The relationships between group function and outcomes were not consistent across studies. PBL experiences were generally highly rated, but favorable student experiences were not reliable indicators of better academic or behavioral outcomes. Conversely, problematic group behaviors were not predictors of poorer grades. Common confounders of outcome measurements included exam pressure and self-study. CONCLUSIONS: The main findings of the review suggested that (1) group function is more predictive of experiential than academic or behavioral PBL outcomes, and (2) different Kirkpatrick levels of outcomes are not highly correlated to each other. More research is needed to understand the complexity of group function in PBL tutorials under variable study contexts and better inform curricular training and design. Standardized tools for measuring PBL group function may be required for more conclusive findings.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0140.018
Science and technology studies0.0010.002
Scholarly communication0.0060.005
Open science0.0020.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.071
GPT teacher head0.425
Teacher spread0.354 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations47
Published2022
Admission routes1
Has abstractyes

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