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Record W3017792979 · doi:10.5430/wje.v10n2p89

Examining the Changes in Beliefs of Preservice Mathematics Teachers Attending the Pedagogic Formation Program about Teacher and Students Roles

2020· article· en· W3017792979 on OpenAlexvenueno aff
Davut Köğce

Bibliographic record

VenueWorld Journal of Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationTeacher educationPsychologyQualitative researchQualitative propertyProfessional developmentPedagogySociologyMathematics

Abstract

fetched live from OpenAlex

This study aimed to identify the beliefs of preservice mathematics teachers receiving formation program as undergraduates or graduates in the Faculty of Science and Letters about teacher and student roles in the classroom setting and to explore how their beliefs changed at the end of the program. The research was conducted in the qualitative research design. The data were collected with a form of three open-ended questions asked to the preservice mathematics teacher attending the formation program in the faculty of education in the fall term of 2014-2015 academic year. The data were collected by applying this questionnaire to the preservice teachers at the beginning and end of the formation program. The answers of the preservice teachers were analyzed by classifying thematically by similarity and difference using the MAXQDA 11 qualitative data analysis software. While the preservice teachers had had beliefs placed somewhere between absolute knowing and transitional knowing about both teacher and student roles before the formation program, these beliefs were transformed into ones placed somewhere between transitional knowing and independent knowing after the formation program. This result indicated how important the pedagogical formation programs are for preservice teachers.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.167
GPT teacher head0.428
Teacher spread0.261 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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