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Record W4320729496 · doi:10.5430/wjel.v13n2p248

Multiple Choice Test-Taking Strategies, Test Anxiety, and EFL Students’ Achievement

2023· article· en· W4320729496 on OpenAlexvenueno aff
Mansoor S. Almalki

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)Test anxietyPsychologyAnxietyEnglish languageAchievement testMathematics educationForeign languageCompetence (human resources)English as a foreign languageMultiple choiceForeign language anxietyLanguage proficiencySignificant differenceSocial psychologyStandardized testStatisticsMathematics

Abstract

fetched live from OpenAlex

Successfully taking a multiple-choice test requires understanding the testing situation and knowing how to take the test efficiently. This study analyses the relationship between multiple-choice test-taking strategies (MCTTSs), test anxiety and the English language achievement of English as a Foreign Language (EFL) students. A mixed-methods approach – quantitative and qualitative – is used by collecting data using a questionnaire and interviews, to increase the research validity. The MCTTS questionnaire of Nguyen (2003), and the test anxiety scale of Aydin et al. (2006) and Burgucu et al. (2011), were used. A total of 727 male and female students from different academic levels and tertiary colleges at an English language centre were chosen as samples. The results broadly show a positive correlation between MCTTSs and English language achievement and a negative relationship between MCTTSs and test anxiety. However, the results revealed significantly higher English language achievement by the female students than the male students. However, there was no difference in the MCTTSs and the degree of test anxiety according to gender. The results suggest raising teachers’ and students’ awareness of the importance of using test-taking strategies. Furthermore, the results can help English language instructors to explain test scores from a different viewpoint, to provide a reliable assessment of language students’ true competence and to reduce the likelihood of measurement errors.

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 score0.074
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.348
Teacher spread0.318 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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