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Record W2892316037 · doi:10.1080/09650792.2018.1515094

Pre-service teachers’ experiences of learning study: learning with and using variation theory

2018· article· en· W2892316037 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducational Action Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVariation (astronomy)Mathematics educationLived experienceContext (archaeology)PedagogyPsychologyPhenomenology (philosophy)Teacher educationLearning theoryEpistemology

Abstract

fetched live from OpenAlex

Our study examines pre-service teachers’ (PSTs) lived experiences designing lessons and preparing for teaching while participating in Learning Study with Variation Theory. Using a phenomenological approach, we examine the experiences of seven elementary PSTs enrolled in a mathematics education course. Data collected include transcripts of in-depth participant interviews, reflective journals, and course assignments. Our phenomenological analysis offers a general structure of participants’ experiences and discusses five structural constituents particularly related to Variation Theory. Results indicate that PSTs found collaborative aspects of Learning Study challenging, and learning to theorize with Variation Theory difficult and unfamiliar. However, PSTs also found the experience valuable in helping them discern critical aspects of a complex concept, thereby helping them understand and teach mathematics in different ways. This study highlighting PSTs’ lived experiences extends the limited research on using Learning Study with Variation Theory in the context of a teacher education course.

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.

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)0.005
metaresearch head score (Gemma)0.002
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.201
GPT teacher head0.525
Teacher spread0.324 · 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