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Record W3005764007 · doi:10.5430/elr.v9n1p8

A Cross-Cultural Comparison of Study Skills and Learning Strategies Between Saudi and American Students

2020· article· en· W3005764007 on OpenAlexvenueno aff
Nasser Alasmari, Zeineb Amri

Bibliographic record

VenueEnglish Linguistics Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsStudy skillsPsychologyCognitive skillSkills managementCognitionMathematics educationMedical educationPedagogyMedicine

Abstract

fetched live from OpenAlex

Study skills and learning strategies are essential in organizing and facilitating learning for academic purposes. Meanwhile, differences in the use of these skills among students coming from distinct cultures are usually based on stereotypes and prejudices.This paper examined the study skills and learning strategies of 236 university students coming from two universities in Saudi Arabia and in the USA by means of the Study and Learning Strategies Inventory (LASSI), a follow up interview and a study diary. To investigate differences in study skills and learning strategies’ use among university students, origin, as Saudi or American, was taken as the independent variable in this study. Results revealed that American students employ study skills and learning strategies other than those used by Saudi students when it comes to the cognitive skills. However, as far as the affective skills are concerned, both groups had difficulties. Such a finding suggests the possibility that study skills’ use varies across cultures. The results of this study could be implemented, first, in raising the awareness of students, teachers, policy makers and counselors about the role of culture in study skills and learning strategies’ use and second in offering training and counseling for incoming foreign university students.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
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 communication0.0010.000
Open science0.0000.000
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 head0.131
GPT teacher head0.531
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

Citations0
Published2020
Admission routes1
Has abstractyes

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