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Record W3038188254 · doi:10.14516/fde.726

The school of hard knocks: Pre-service teachers’ mindset and motivational changes during their practicum

2020· article· en· W3038188254 on OpenAlexaffabout
Eleftherios Soleas, Ji Hong

Bibliographic record

VenueForo de Educación · 2020
Typearticle
Languageen
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsQueen's University
Fundersnot available
KeywordsPracticumMindsetPsychologyThematic analysisPsychological resilienceService (business)PedagogyCoachingMathematics educationQualitative researchSocial psychologyComputer scienceSociology

Abstract

fetched live from OpenAlex

The mindset and motivation that teachers demonstrate are likely to influence their students’ mindset and motivation. While mindset and motivation of in-service teachers have been investigated thoroughly, the same cannot be said of pre-service teachers. Pre-service teachers’ mindset and motivation are likely developed during in-class experiences or practicum, the latter seen as the defining experience of pre-service teachers’ preparation. Understanding the changes that pre-service teachers undergo during their practicum experiences in terms of theories of intelligence, teaching efficacy, resilience, and grit is therefore crucial. This study used these constructs as examples of mindsets, self-beliefs, capacities, and personality traits. A cross-sectional design compared American and Canadian pre-practicum versus post-practicum pre-service teachers’ growth mindset and motivation and illustrated that similar effects occur across national contexts through a primarily quantitative questionnaire with open-ended questions. Triangulated statistical and thematic analyses illustrated that post-practicum students were less idealistic about the incremental nature of intelligence and reported higher resilience and a more pragmatic approach to teaching than their pre-practicum peers. The study’s findings extended other studies’ findings illustrating that changes occur specifically in teacher mindset as well as their strategies. Teacher education programs informed by these specific changes can capitalize on the pragmatic shift of teachers’ strategy selection while also coaching them to retain an incremental view of intelligence for their students’ benefit.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.297
Teacher spread0.263 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

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