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Inquiry-based learning as a facilitator to student engagement in undergraduate and graduate social work programs

2020· article· en· W3011828942 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

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFacilitatorPsychologyExperiential learningProfessional learning communityQualitative researchActive learning (machine learning)PedagogyWork-based learningStudent engagementCooperative learningMedical educationHigher educationMathematics educationWork (physics)Teaching methodSociologyMedicineComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

This seven-cohort mixed methods study examines student engagement in their learning in higher education utilizing inquiry-based learning. The study was conducted in varied settings (on-campus, in community, and study abroad), and across various degree levels (undergraduate, graduate, and doctoral) in social work education. Study results reveal an increase in participant reflective and integrative learning, and an increase in higher-order learning. Qualitative findings support the results through four emergent themes: (1) experience of inquiry-based learning, (2) adjustments required for learning process, (3) impactful facilitators to learning, and (4) developing deep learning. Implications and recommendations are offered for higher education and professional programs.

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)0.011
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.171
GPT teacher head0.431
Teacher spread0.260 · 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