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Record W2574577268 · doi:10.1080/13611267.2016.1270899

Student-faculty team teaching – A collaborative learning approach

2016· article· en· W2574577268 on OpenAlex
Enza Gucciardi, Calvin Mach, Stephanie Mo

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMentoring & Tutoring Partnership in Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsToronto Metropolitan University
FundersRyerson University
KeywordsThematic analysisMedical educationClass (philosophy)Peer learningFocus groupPsychologyStudent engagementPeer groupAnxietyMathematics educationQualitative researchMedicineComputer scienceSociology

Abstract

fetched live from OpenAlex

In this study, we aim to gage students’ satisfaction, learning outcomes, and experiences with student-faculty team-teaching in an undergraduate quantitative-research-methods course. Three peer tutors co-taught with a faculty instructor each year, receiving pedagogical-placement credits. Data were collected via bi-weekly journals, a focus group, and a questionnaire on students’ satisfaction and learning experiences. Data were analyzed through descriptive and thematic analyses. Peer tutors reduced student anxiety, increased engagement, and availability of help inside/outside class. Peer tutors described uncertainty about their roles and tension with classmates. However, peer tutors gained new perspectives, skills, and described supportive student-faculty teaching teams as assets to improving the course experience for students.

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)0.008
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.062
GPT teacher head0.437
Teacher spread0.375 · 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