MétaCan
Menu
Back to cohort
Record W4313326014 · doi:10.5430/wjel.v12n7p335

The Educational Impact of Distance Learning during the COVID-19 Pandemic on Students' Interaction in the Educational Process

2022· article· en· W4313326014 on OpenAlexvenueno aff
Faisal Bin Shabib Mosleet Alsubaie

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmLikert scaleDistance educationMathematics educationDescriptive statisticsPandemicCoronavirus disease 2019 (COVID-19)PreferencePsychologyProcess (computing)Computer scienceMedical educationMathematicsStatisticsSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Due to the widespread impact of the Covid 19 pandemic, teachers and students were driven to relocate their teaching learning practices to the safety of their own homes. The goal of this research was to learn how Saudi students felt about distance learning online during the lockout of the College of Science and Humanities at Sulail, Prince Sattam Bin Abdullah University. Multiple methods were used to complete the study. Researchers collected data from 152 degree students of Management,Computer Science, English, Islamic Studies, Arabic department to rate their satisfaction with online learning settings using a Likert scale ranging from one to five points. A mixed research strategy was chosen for the study's purposes, with descriptive analysis used for the quantitative data analysis and content analysis used for the qualitative data analysis. Although some respondents expressed enthusiasm for online distance learning, the vast majority reported difficulties with the format and stated a preference for traditional in-person classes. Some students have expressed enthusiasm for this form of distance education. The study concluded that the findings can help policymakers and professors construct effective or efficient teaching ways to overcome difficult situations or pandemics, which is a summary of the study's main points.

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)0.001
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 score0.133
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.325
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; 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of English LanguageSame topicOrganizational and Employee PerformanceFrench-language works237,207