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Record W3199649793 · doi:10.5539/ies.v14n10p40

Evaluation of Students’ Remote Learning Experience of Learning Arabic as a Second Language During the Covid-19 Pandemic

2021· article· en· W3199649793 on OpenAlexvenueno aff
Sultan Almelhes

Bibliographic record

VenueInternational Education Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLikert scalePsychologyEducational technologyBlended learningThe InternetHigher educationMultimethodologyPandemicMathematics educationLanguage acquisitionComputer-mediated communicationExperiential learningMedical educationPedagogyCoronavirus disease 2019 (COVID-19)MedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The emergence of the Covid-19 global pandemic was followed by restrictions on social contact and interaction. Online remote learning was implemented all levels of school and universities in Saudi Arabia. In tertiary education, where Arabic is taught as a second language (ASL) with extensive interaction between the teacher and students, remote learning has specific advantages and disadvantages. This study aimed to investigate the success of remote learning, its influence upon learners’ attitudes, and its potential difficulties in implementation. Quantitative research was conducted on a sample of 236 students who had combined experiences of offline and online study during 2020 in their second semester at the Arabic Language Institute for Non-Native Speakers’. An online survey was administered consisting of three domains: students’ satisfaction with remote learning, obstacles faced, and students’ perceptions towards evaluation; students’ responses were measured using a Likert scale. The results demonstrated that there was hesitation about student satisfaction, as the result was moderate in general. Moreover, the study revealed difficulties included internet connection issues, the access and availability of remote learning, insufficiency in personal expression, and difficulties with technological devices. The results also showed that the students were dissatisfied regarding to the evaluation and assessment methods used in remote learning.

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)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.120
GPT teacher head0.520
Teacher spread0.400 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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