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Record W3161981615 · doi:10.5539/res.v13n2p57

Implications of the Digital Divide for the Learning Process During the COVID-19 Crisis

2021· article· en· W3161981615 on OpenAlexvenueno aff
Gila Cohen Zilka, Idit Finkelstein, Revital Cohen, Ilan Daniels Rahimi

Bibliographic record

VenueReview of European Studies · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetFeelingPsychologyUploadCoronavirus disease 2019 (COVID-19)Internet accessDigital divideInternet privacyProcess (computing)Public relationsBusinessPolitical scienceSocial psychologyComputer scienceWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

With the outbreak of the COVID-19 crisis, higher education institutions organized for online learning. The aim of the present study was to examine the implications of online learning for students with limited access to information and communication technology (ICT), content infrastructures, and digital environments, assuming that such limited access may impair their ongoing learning process when instruction moves online, and cause situations of stress and frustration, as well as a desire to drop out of school. The mixed-method study involved 639 students studying at institutions of higher education in Israel, who completed a questionnaire containing open and closed questions. The findings show that 13% of participants reported that they had limited access, difficulties, and malfunctions resulting from a weak connection to the Internet, and numerous disconnects, especially during synchronous lectures. They reported having difficulties downloading content from the Internet and uploading materials. It has been shown that limited access to the Internet has implications for the learning process, motivation, self-efficacy, as well as for feelings and emotions. It is liable to lead to the widening or the creation of gaps between students who have full and those who have limited access to the Internet. The findings show that little use is made of forums (10%). A more extensive use of the forums is recommended in courses where students have limited access to the Internet, to create a supportive learning community.

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)0.002
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.864
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.179
GPT teacher head0.494
Teacher spread0.315 · 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
GenreReview

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

Citations11
Published2021
Admission routes1
Has abstractyes

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