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Record W1615478907 · doi:10.21225/d52c75

Teacher Professional Development in Mathematics and Science: A Blended Learning Approach

2006· article· en· W1615478907 on OpenAlexaffvenue
Margaret Sinclair, Ron Owston

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsYork University
Fundersnot available
KeywordsFlexibility (engineering)Blended learningProfessional developmentMathematics educationSubject matterFaculty developmentPsychologyCohesion (chemistry)Drop outPedagogyEducational technologyCurriculumMathematics

Abstract

fetched live from OpenAlex

Blended learning is a promis- ing model for supporting teacher professional development that combines the advantages of tradi- tional face-to-face interaction with the flexibility of online learning. In this study, we examine the impact of two one-year blended learning programs on teachers’ attitudes, knowledge, and classroom practices. These professional development programs were designed to enhance middle school teachers’ subject matter knowledge and pedagogical skills in mathematics and science/ technology. Our results indicate that the programs positively affected teacher attitudes and content knowledge in these curricular areas and motivated many teachers to transform their classroom practices. Increased teacher collaboration and involvement at the school level sug- gest that the experiences contrib- uted to the emergence of fledgling communities of practice. At the same time, the lack of cohesion in online groups and the drop off in participation suggest the need to rethink some aspects of the design of blended learning environments.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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.

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

Citations11
Published2006
Admission routes2
Has abstractyes

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