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Record W4407568787 · doi:10.1080/10476210.2025.2462299

<i>‘We can help when you lose your way.’</i> High-school students’ reflections on pre-service teachers and the teaching practicum

2025· article· en· W4407568787 on OpenAlexafffundabout
Joanne Pattison‐Meek

Bibliographic record

VenueTeaching Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsBishop's University
FundersBishop's University
KeywordsPracticumMathematics educationPedagogyPsychologyService (business)SociologyBusiness

Abstract

fetched live from OpenAlex

Classroom students are stakeholders in initial teacher education given that many preparation programs include field-based practice in classroom settings as a certification requirement. Owing to their frequent contact with pre-service teachers (PSTs) during practicum periods, students are well positioned to contribute to PSTs’ learn-to-teach experiences. Practicum scholarship, however, commonly positions classroom students as passive participants, or bystanders, tending to overlook their learning relationships with PSTs. Utilizing group interviews with students from three high schools in Québec (Canada), this qualitative study asked the following: How do high-school students experience practice teaching? How might students’ experiences with practice teaching inform PSTs’ professional learning? The findings highlight ways PSTs and practice teaching have the potential to both enhance and impede students’ learning and classroom experiences. Students widely acknowledged that they have an important role to play in supporting the professional learning of PSTs. Drawing on the theory of practice architectures, the student testimonies shared in this study incite initial teacher education programs to develop contemporary models of practicum mentorship that support reciprocal learning relationships between PSTs and their students.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.143
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.012
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0090.003

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 head0.029
GPT teacher head0.407
Teacher spread0.378 · 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 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

Citations1
Published2025
Admission routes3
Has abstractyes

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