MétaCan
Menu
Back to cohort
Record W3148001342 · doi:10.29173/iasl7991

Collaborative Planning and Team Teaching in a Large Lecture Hall: Modeling Leadership for Change

2021· article· en· W3148001342 on OpenAlexaffvenueabout
Jennifer Branch, Leonora Macy, Jill McClay, Carol Leroy

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProcess (computing)Action researchService (business)Control (management)Medical educationPsychologyPedagogyMathematics educationComputer scienceMedicineBusiness

Abstract

fetched live from OpenAlex

This paper presents data from initial interviews of instructors collaboratively planning a new course in the Faculty of Education at the University of Alberta. There is a need to investigate the courses we offer in pre-service teacher education in order to understand the best ways to prepare pre-service teachers for teaching in today’s ever changing environments. The interviews were the first part of an action research cycle that follows students and instructors through the initial implementation of the course. The paper discusses the collaborative process and highlights five themes that emerged from the data: fear and risk-taking, control, course content, process, and the possibilities for positive change. Recommendations for pre-service teacher educators and teacher-librarians involved in collaboration are included. Through studying the implementation of this complex course, the research will provide us with information to improve the course and to offer our experiences as models for others involved in such a process.

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.103
GPT teacher head0.365
Teacher spread0.262 · 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 teacher head, 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

Citations0
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueIASL Annual Conference ProceedingsSame topicCollaborative Teaching and InclusionFrench-language works237,207