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Record W4288073730 · doi:10.21608/jftp.2021.78946.1144

معتقدات وتحدیات مدرسی اللغة الانجلیزیة کلغة أجنبیة تجاه الفصول الدراسیة عبر الإنترنت المدمجة بالتکنولوجیا أثناء جائحة کورونا (کوفید- 19) بجامعة الأهرام الکندیة

2021· article· ar· W4288073730 on OpenAlexaboutno aff
هدی علی علی

Bibliographic record

Venueمجلة کلیة التربیة بورسعید · 2021
Typearticle
Languagear
FieldSocial Sciences
TopicE-Learning and COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

The Covid-19 pandemic has offered us a challenging opportunity to pave the way for introducing digital learning. The unexpected shift of teaching the English language from face-to-face classroom to online learning activities through digital platforms has raised significant challenges for English teachers and students. Thus, the current study aims to investigate the EFL teachers' beliefs towards the effectiveness of technology-integrated online classrooms and the challenges they experienced during the Covid-19 pandemic. The study adopts an exploratory sequential design whereby online questionnaire and interviews were used to come up with a comprehensive report on the impact of technology-integrated online classrooms during the Covid-19 pandemic and the EFL teachers' challenges faced in online teaching. For data collection, 48 instructors at the English language department, Ahram Canadian University, participated in the study. Due to the pandemic lockdown, the study took place in the spring semester of the academic year 2020. The current study focused on addressing the following questions: Is technology-integrated online classroom beneficial during the Covid-19 pandemic?

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.447
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.007
Science and technology studies0.0070.004
Scholarly communication0.0030.002
Open science0.0050.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0160.024

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 head0.044
GPT teacher head0.357
Teacher spread0.313 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueمجلة کلیة التربیة بورسعیدSame topicE-Learning and COVID-19French-language works237,207