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Record W4300801611 · doi:10.1177/016146810610800707

Student Cohorts in Teacher Education: Support Groups or Intellectual Communities?

2006· article· en· W4300801611 on OpenAlexaff
Kelvin Seifert, David Mandzuk

Bibliographic record

VenueTeachers College Record The Voice of Scholarship in Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBachelorCohortPsychologyHigher educationFriendshipPedagogyMedical educationSociologySocial psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

Recent initiatives in preservice teacher education have experimented with cohorts as a way to create supportive ties among peers, mutual intellectual support, and a sense of professionalism. The initiatives reflect a belief in collaboration, one expressed in educational literature supporting related forms of collaboration in education, such as descriptions of learning communities and of cooperative learning in classrooms. A review of this literature suggests a number of cautions, however, about the value and success of collaboration among colleagues, and in any case does not address the needs of cohorts in teacher education directly. To begin closing this information gap, the authors studied one particular teacher education program organized around cohorts. Sixteen students in a preservice bachelor of education program were interviewed at length about their experiences with cohort peers. Their comments were analyzed for recurring themes. Overall, they expressed a liking for cohort organization, but to varying degrees. Appreciation of the cohorts was focused almost entirely on the immediate social support provided by the cohort as a whole. It had little to do with its potential for academic stimulation, long-term professional ties, or individual personal friendships. Students reported a number of factors that affected their liking for cohorts, such as their age, prior family or job responsibilities, religion, and geographic distance of their home from the university.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.211
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.386
Teacher spread0.312 · 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.

Study designObservational
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

Citations8
Published2006
Admission routes1
Has abstractyes

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