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Record W2560963012 · doi:10.1515/mlt-2014-0013

Do Group Exams Support English as an Additional Language Student Learning?

2015· article· en· W2560963012 on OpenAlexaffabout
Marion Caldecott, Esma Emmioğlu Sarıkaya

Bibliographic record

VenueMulticultural Learning and Teaching · 2015
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPsychologyMathematics educationPerceptionClass (philosophy)English languageQualitative propertyQualitative researchPedagogyComputer scienceSociology

Abstract

fetched live from OpenAlex

Abstract Team-based learning (TBL) has been shown to improve many aspects of student learning, but no previous research has systematically examined the effects of group exams on English as an Additional Language (EAL) students in university classrooms. This study is a small-scale action research examining the role of students’ English language status in their perceptions of and performance in group exams within TBL. The data were collected from 29 students – (13 EAL) and 16 English as a first language (EL1) – attending a third-year university linguistics class in Vancouver, Canada. Qualitative and quantitative methods were used for the data analysis. Results of the study revealed no statistically significant differences between the two groups in terms of perceptions or performance. Both groups had positive perceptions about group exams and the increase in their performance over the course of the semester was statistically significant. Qualitative results showed that students found group exams helpful for learning and reducing exam anxiety. Students also enjoyed the experience of taking group exams and stated that their attitudes toward the group exams were more positive at the end of the semester.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.397
Teacher spread0.360 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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