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Record W2470072566 · doi:10.1177/1746197916653583

From Minnesota to Cairo: Student perceptions of community-based learning

2016· article· en· W2470072566 on OpenAlexfundno aff
Mona Ibrahim, Marnie R Rosenheim, Mona M. Amer, Haley A Larson

Bibliographic record

VenueEducation Citizenship and Social Justice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
FundersConcordia University of Edmonton
KeywordsLiberal arts educationSample (material)PerceptionScale (ratio)Rating scalePsychologyCommunity collegeThe artsMedical educationPedagogyMathematics educationHigher educationPolitical scienceMedicineGeographyDevelopmental psychology

Abstract

fetched live from OpenAlex

This study explored perceptions of community-based learning in a sample of 176 students at a liberal arts college in Cairo, Egypt, and a sample of 176 students at a liberal arts college in the Midwestern United States. Students responded to a 38-item rating scale that assessed gains in several domains as a result of engaging in community-based learning and provided ratings of their level of interest in and satisfaction with the community-based learning experience. The rating scale revealed differences in the extent of gains in several domains reported by each sample, as indicated by the results of independent samples t tests. Open-ended questions were used to solicit student opinions about their community-based learning experiences. These questions revealed differences in the benefits, challenges, and types of recommendations that were reported by the students in both samples. Suggestions are offered for culturally relevant administration of community-based learning pedagogy as well as for future research.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.050
GPT teacher head0.371
Teacher spread0.321 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations6
Published2016
Admission routes1
Has abstractyes

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