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Record W1546006813

Designing a Professional Practice Doctoral Degree in Educational Technology: Signature Pedagogies, Implications and Recommendations

2011· article· en· W1546006813 on OpenAlexvenueno aff
Kara Dawson, Terence Cavanaugh, Christopher Sessums, Erik W. Black, Swapna Kumar

Bibliographic record

VenueInternational journal of e-learning & distance education · 2011
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPedagogySociologyPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

In this article we outline the three dimensions of signature pedagogy guiding the design of our professional practice doctoral degree in Educational Technology. This program was developed based on our experiences with the Carnegie Initiative on the Education Doctorate and work with many students for whom the Ph.D. was not an exact match with their career goals. We also share preliminary data related to program effectiveness and provide recommendation for others interesting in designing professional practice programs. Through this work we have come to believe Educational Technology is a discipline ripe with potential to meet the needs of scholars and professional practitioners through terminal degree programs differentiated based on career goals and contexts. Resume Dans cet article, nous decrivons les trois dimensions de la didactique appliquee, dit signature pedagogy en anglais ayant guide la conception de notre programme de doctorat professionnel en technologie educative. Ce programme a ete elabore a partir de nos experiences realisees dans le cadre de la Carnegie Initiative on the Education Doctorate et du travail effectue avec de nombreux etudiants pour qui le diplome doctoral traditionnel―axe sur une carriere academique―ne correspondait pas a leurs objectifs de carriere. Nous partageons aussi des resultats preliminaires en lien avec l’efficacite des programmes et fournissons des conseils pour ceux qui s’interessent a la conception de programmes de type professionnel. Par ces travaux, nous en sommes venus a croire que la technologie educative est une discipline qui deborde de potentiel pour repondre aux besoins des chercheurs academiques et des praticiens professionnels par l’elaboration de programmes doctoraux qui se differencient selon les objectifs de carriere et les contextes.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.697
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.202
GPT teacher head0.523
Teacher spread0.321 · 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 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

Citations17
Published2011
Admission routes1
Has abstractyes

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