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Record W4393106862 · doi:10.1007/978-981-99-6679-0_3

Open Educational Practices (OEPs) for Research Skill Development with In-Service School Teachers

2024· book-chapter· en· W4393106862 on OpenAlexaffabout
Barbara Brown, Michele Jacobsen, Verena Roberts, Christie Hurrell, Mia Travers, Nicole Neutzling

Bibliographic record

VenueSpringer briefs in education · 2024
Typebook-chapter
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSituatedPedagogyParticipatory action researchSituated learningCitizen journalismProfessional developmentPsychologyMathematics educationSociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Abstract In this chapter, we discuss open educational practices (OEPs) that Teacher Educators (TEs) used to facilitate in-service schoolteachers’ (I-STs’) research thinking. The majority of graduate students in the program held teaching roles in K-12 or educational development and training roles in adult learning contexts. OEPs are participatory and collaborative learning opportunities based on social constructivist principles used in a component of a fully online Master’s program in Education offered by a research university situated on the Canadian prairie. The I-STs in the program were situated as scholars of the profession and were provided with structured learning opportunities to help develop research-based skills (Brown et al. in Open Educational Practices (OEP) create conditions for learning in a graduate school, 2022; Jacobsen et al. in J Univ Teach Learn Pract 15(4):1–18, 2018). Results from our study indicate that responsive teaching is integral to OEP and can help I-STs develop research skills and research thinking.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.093
GPT teacher head0.415
Teacher spread0.322 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes2
Has abstractyes

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