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Record W2758957808

Linking Theory and Practice in Hybrid Spaces through School-University Partnerships

2017· article· en· W2758957808 on OpenAlexaff
Gladys Sterenberg, Kevin O’Connor, David Dillon

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsMcGill UniversityMount Royal University
Fundersnot available
KeywordsPracticumNegotiationSpace (punctuation)PedagogySociologyFocus groupComputer science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this paper is to investigate the effects of our pedagogy designed to create hybrid spaces linking academic and practitioner knowledge within an integrated, school-based, and professionally-oriented practicum semester. Reforms to teacher education have called for extensive practical experience for teacher candidates and many of these calls have advocated for strong school-university partnerships as a means for increasing reciprocal collaboration in order to connect theory and practice. Attending to hybrid spaces, we designed a professional semester to include extensive practicum, school-based courses, seminars, and integrated assignments within the creation of authentic school-university partnerships. Qualitative data gathered included transcripts of six focus group conversations with administrators and teachers from individual schools, two joint meetings with administrators from four partner schools, and ten individual interviews with teacher candidates. Four themes were identified that related to the creation of a third space: co-constructing a common vision, negotiating alumni loyalties to other institutions, developing overlapping communities of practice, and creating new ways of integrating institutional requirements and partner desires. We conclude that the challenges we encountered in creating a third space and our attempts to create new knowledge as we resolved issues prompted robust opportunities for linking theory and practice.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.102
GPT teacher head0.374
Teacher spread0.271 · 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 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
Published2017
Admission routes1
Has abstractyes

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