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Record W2073998962 · doi:10.1177/002248702237396

The Importance of the University Campus Program in Preservice Teacher Education

2002· article· en· W2073998962 on OpenAlexaff
Clive Beck, Clare Kosnik

Bibliographic record

VenueJournal of Teacher Education · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsCurriculumMathematics educationTeacher educationTeacher preparationPedagogyPsychologyHigher educationMedical educationSociologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

The university campus component of preservice teacher education is often seen as overly theoretical, fragmented, and unconnected to practice. Indeed, some commentators maintain that a key step in the “reform” of teacher education is to reduce the time student teachers spend on campus. In response, teacher educators have made a number of suggestions for improving the campus program. Building in part on those suggestions, the authors modified the campus aspect of a preservice program. In this study, student teachers’ views were elicited on the redesigned campus program. Whereas the student teachers made several recommendations for improving the campus program, all said it had a major impact on their development as teachers. In particular, it helped them acquire broad goals for teaching, broad pedagogical approaches, specific skills, curriculum knowledge, and a sense of themselves as professionals. However, this impact was largely dependent on program structures and approaches that, to be viable, require significant institutional support.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.060
GPT teacher head0.363
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations29
Published2002
Admission routes1
Has abstractyes

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