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Record W2252659566 · doi:10.19173/irrodl.v17i1.2182

If You Build It, Will They Come? Predictors of Teachers’ Participation in and Satisfaction with the Effective Classroom Interactions Online Courses

2016· article· en· W2252659566 on OpenAlexvenueno aff
Jennifer LoCasale‐Crouch, Bridget K. Hamre, Amy Roberts, Kathy Neesen

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyEarly childhoodClass (philosophy)Early childhood educationMassive open online courseMathematics educationOnline coursePersistence (discontinuity)Medical educationPedagogyDevelopmental psychologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

<div class="WordSection1"><p>The <em>Effective Classroom Interactions</em> (ECI) online courses were designed to provide an engaging, effective and scalable approach to enhancing early childhood teachers’ use of classroom practices that impact children’s school readiness. The created courses included several versions aimed at testing whether or not certain design aspects could increase participation and subsequent learning outcomes. The purpose of this study was to examine the extent to which early childhood teachers accessed the courses and varied in their a) participation in the core course content and b) optional discussion board as a result of the course experience they were assigned to as well as individual characteristics that may be associated with participation. Findings indicated that early childhood teachers accessed the course often on nights and weekends and reported high levels of satisfaction with their experience. Both persistence in the ECI courses and overall completion of activities were higher than those reported in other studies of online learning. Whether or not the participant was in the course that had regular interactions with the instructor, comfort with technology and took the course for credit consistently predicted participation, but not always in expected ways. Implications for exploring online learning as a feasible option for early childhood educators are discussed.</p></div>

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.434
Teacher spread0.388 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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