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Record W4224284710 · doi:10.5539/ells.v12n2p67

Undergraduate EFL Students’ Perceptions About Their Experiences Attending Online Classes During the COVID-19 Pandemic at a Saudi University

2022· article· en· W4224284710 on OpenAlexvenueno aff
Mohammad Alghamdi

Bibliographic record

VenueEnglish Language and Literature Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Strengths and weaknessesMedical educationPsychologyHigher educationSWOT analysisDistance educationThe InternetPandemicFlexibility (engineering)Coronavirus disease 2019 (COVID-19)Internet accessPerceptionMathematics educationMedicineComputer sciencePolitical scienceGeographyWorld Wide WebSocial psychologyBusiness

Abstract

fetched live from OpenAlex

The purpose of this study was to examine undergraduate EFL students’ perceptions about their experiences attending online classes at a Saudi higher education institute during the COVID-19 pandemic. Random sampling was used to obtain the subjects of the study, twelve undergraduate EFL students who attended online classes for the first time at Al-Baha University, Saudi Arabia. A SWOT analysis was used to process the collected data. The main strengths of using online classes in the EFL context were time/place flexibility, promoting a more active/interactive learning style, and the availability of recorded sessions, all of which helped the students when they were reviewing the asynchronously-delivered content. The weaknesses were all related to technical issues (access to an adequate internet connection and an appropriate device on which to access the internet). This study is expected to generate new insights into the process of implementing online classes or blended classes to teach the English language in the Saudi context, and to examine the potential strengths, weaknesses, opportunities, and threats to such an adoption at the target university during the shift to online classes during the COVID-19 pandemic. These findings may be beneficial for other higher education institutions with a similar context in Saudi Arabia and may benefit higher education policymakers in Saudi Arabia.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.026
GPT teacher head0.351
Teacher spread0.325 · 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

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