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Record W4225283804 · doi:10.19173/irrodl.v23i2.6082

Are K–12 Teachers Ready for E-learning?

2022· article· en· W4225283804 on OpenAlexvenueno aff
Elif Polat, Sinan Hopcan, Ömer Yahşi

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender and Technology in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCompetence (human resources)Psychological interventionSignificant differenceMathematics educationTechnology integrationScale (ratio)Medical educationEducational technologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

Readiness is important for the success of the e-learning process. The purpose of this study was twofold: to develop a scale to measure K–12 teachers’ e-learning readiness, and to examine their readiness to teach online. The participants were 3,295 K–12 teachers working in Izmir, Turkey. First EFA, then CFA-SEM was performed. Additionally, teachers’ e-readiness in terms of gender, years of service, school level, and daily device usage time were examined. Teachers are ready for e-learning considering their overall scores. A significant difference was found in favor of males in the “technical competence” factor and in favor of females in the “colleague, content, and pedagogical and ethical competence factors”. The readiness of younger teachers is generally higher. On a factor basis, there is only a significant difference in the factors of computer self-efficacy and student readiness according to educational level. As the use of devices increases, technology-related readiness increases. The readiness of teachers plays an important role in determining future strategies, measures, and interventions that need to be taken to advance e-learning.

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)0.010
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.204
GPT teacher head0.515
Teacher spread0.312 · 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 designNot applicable
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

Citations14
Published2022
Admission routes1
Has abstractyes

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