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Record W1971379933 · doi:10.5539/ies.v4n2p13

Constraints in Teacher Training for Computer Assisted Language Testing Implementation

2011· article· en· W1971379933 on OpenAlexvenueno aff
Jesús García Laborda, Mary Frances Litzler

Bibliographic record

VenueInternational Education Studies · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
FundersUniversidad de Alcalá
KeywordsChristian ministryTest (biology)Mathematics educationFocus groupProcess (computing)PsychologyTraining (meteorology)PedagogyMedical educationComputer scienceSociologyPolitical science

Abstract

fetched live from OpenAlex

Many ELT examinations have gone online in the last few years and a large number of educational institutions have also started considering the possibility of implementing their own tests. This paper deals with the training of a group of 24 ELT teachers in the Region of Valencia (Spain). In 2007, the Ministry of Education provided funds to determine whether it would be possible to implement an online University Entrance Examination (P.A.U.) in Spain at the national level. The project was to address three main areas: the technology, the students and the teachers. In relation to the teachers, the focus of this paper, the project was to investigate whether there were any changes in their routines, teaching methodology and attitudes towards assessment using technology. This brief study focuses on one of the last tasks in the preparation stage for implementation of the computerized exam, and it is intended to predict and observe the teachers’ reactions towards computer assisted language testing, the new test and the new test design. The findings shed light on the teachers’ internal changes and their changes in attitude throughout the process.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.566
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.325
GPT teacher head0.427
Teacher spread0.102 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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