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Record W1131087024

The Effect of Dynamic and Non-Dynamic Assessment on Acquisition of Apology Speech Act among Iranian EFL Learners

2014· article· en· W1131087024 on OpenAlexvenueno aff
Arezou Razavi, Omid Tabatabaei

Bibliographic record

VenueJournal of academic and applied studies · 2014
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsDynamic assessmentPragmaticsSpeech actMediationPsychologyTest (biology)LinguisticsComputer scienceMathematics educationDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

The current study has aimed to explore the effect of dynamic and non-dynamic assessment on acquisition of apology speech act among Iranian EFL learners. One-hundred forty-three male and female intermediate Iranian learners, who were selected randomly, were assigned to high and low groups based on their score in OPT. Then, each group was divided into two DA and NDA groups randomly. Both groups participated in pretest and posttest, six treatment tests during fifteen sessions, also an instruction part about different apology strategies based on Olshatain and Cohen (1983). DA groups, the experimental ones, received different types of mediation in tests based on Lantolf and Poehner's (2011) scale and their ZPDs. NDA groups, the control ones, were assessed in traditional method. T-test was used to analyze the data, which revealed that DA group significantly outperformed NDA group. The main result of this study showed that dynamic assessment helps learners to improve their apology speech act acquisition. The findings of this study provide insights to assessment of pragmatics.

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)0.000
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 score0.410
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.016
GPT teacher head0.395
Teacher spread0.379 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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