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An Online Course Design for Inservice Teacher Professional Development in a Digital Age

2015· book-chapter· en· W4235077622 on OpenAlexaff
Kyungmee Lee, Clare Brett

Bibliographic record

VenueAdvances in higher education and professional development book series · 2015
Typebook-chapter
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDesign-based researchContext (archaeology)Online courseProfessional developmentComputer scienceInstructional designMathematics educationLearning designTeacher educationCourse (navigation)Online learningPedagogyPsychologyMultimediaEngineering

Abstract

fetched live from OpenAlex

This chapter introduces a practical model for teacher educators concerned with designing online courses for inservice teachers' technological knowledge learning and its implementation in their teaching. A double-layered CoP model has been developed and repeatedly applied in the teacher professional development (TPD) context using a design-based research (DBR) approach. DBR provides an iterative cycle of design, implementation, evaluation and improvement of the design. This chapter includes a detailed description of the design context of the model including design considerations and theoretical frameworks upon which the model is based. The chapter also demonstrates how the model works in practice referencing important issues in current teacher education practices and offering suggestions for how DBR can guide teacher educators' teaching and research practices. Four course participants' learning experiences are presented as case studies to illustrate more clearly the way the model seems to be facilitating teachers' learning processes.

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 categoriesMeta-epidemiology (narrow), 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 score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.130
GPT teacher head0.441
Teacher spread0.310 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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