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Record W2143292250

Collaborative teaching of an integrated methods course

2011· article· en· W2143292250 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

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCourse (navigation)Computer scienceMathematics educationMedical educationPsychologyEngineeringMedicine
DOInot available

Abstract

fetched live from OpenAlex

With an increasing diversity in American schools, teachers need to be able to collaborate in teaching. University courses are widely considered as a stage to demonstrate or model the ways of collaboration. To respond to this call, three authors team taught an integrated methods course at an urban public university in the city of New York. Following a qualitative research design, this study explored both instructors‟ and pre-service teachers‟ experienceswith this course. Study findings indicate that collaborative teaching of an integrated methods course is feasible and beneficial to both instructors and pre-service teachers. For instructors,this collaborative teaching was a reciprocal learning process where they were engaged in thinking about teaching in a broader and innovative way. For pre-service teachers, this collaborative course not only helped them understand how three different subjects could berelated to each other, but also provided opportunities for them to actually see how collaboration could take place in teaching. Their understanding of collaborative teaching was enhanced after the course.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.300
GPT teacher head0.634
Teacher spread0.334 · 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