MétaCan
Menu
Back to cohort
Record W4297240837 · doi:10.5539/ies.v15n5p101

When the Cheese Moves: How Arab and Jewish Education Students Perceive the Transition to Distance Practical Teaching During the Covid-19 Crisis

2022· article· en· W4297240837 on OpenAlexvenueno aff
Haifaa Majadly, Daniel Nikritin

Bibliographic record

VenueInternational Education Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDistance educationPsychologyTeaching methodPerceptionHigher educationJudaismComputer-assisted web interviewingMultimethodologyCoronavirus disease 2019 (COVID-19)PedagogyMathematics educationMedical educationPolitical scienceMedicine

Abstract

fetched live from OpenAlex

The goal of the current study was to examine teaching students’ positions and perceptions regarding the transition to an online format for practical teaching during Covid-19, and whether differences exist between Jewish and Arab students’ positions. The study also examines teaching students’ technological and pedagogical self-efficacies for distance teaching and the extent of differences between the Arab and Jewish students’ self-efficacies. In addition, the study examined which background and personality variables predict positions and perceptions. The findings are based on a questionnaire completed by 279 Arab and Jewish teaching students from two Israeli teacher education colleges that transitioned to online practical teaching as a result of the Covid-19 crisis. Semi-structured interviews were also conducted to gain a deeper understanding of the questionnaire findings and to expand on topics not referred to in the questionnaire. The study reveals that teaching students accept the importance of the distance teaching experience during training in order to prepare them for the changing reality. Nevertheless, this cannot fully replace field experience because of the need for support and the limited ability to learn from the distance experience about face-to-face teaching.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.547
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
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 head0.052
GPT teacher head0.454
Teacher spread0.402 · 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 designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Education StudiesSame topicTechnology-Enhanced Education StudiesFrench-language works237,207