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Record W2164384023 · doi:10.5539/ies.v5n1p181

Demotivating Factors Affecting EFL Learning of Iranian Seminary Students

2012· article· en· W2164384023 on OpenAlexvenueno aff
Omid Tabatabaei, Ahmad Molavi

Bibliographic record

VenueInternational Education Studies · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningTest (biology)Mathematics educationPsychologyIslamTeaching methodTheology

Abstract

fetched live from OpenAlex

In the present study, an attempt has been made to determine the demotives affecting EFL learning of Iranian Islamic seminary students and also to distinguish the motivated and demotivated EFL learners in terms of their EFL learning as the major focus of this study. Fifty Iranian EFL seminary students were investigated using two validated questionnaires. First a modified version of The Attitude/Motivation Test Battery Questionnaire (AMTB) originally developed by Gardner (2004) was used to determine the degree of learners’ motivation. Second a modified version of Warrington's (2005) questionnaire was administered to determine the demotivating factors from the students' point of view. Then, the IOPT (Interchange Objective Placement Test) was administered to measure the general proficiency of the subjects under study. The comparison of the IOPT score means of the two groups revealed a significant difference in the results of IOPT of students with higher scores in the AMTB and those with lower scores. That is, the more motivated the students were, the higher their IOPT scores were. Furthermore, factors such as the improper method of English teaching, frequency of classes in a week, problems in understanding listening materials and lack of use of English in students’ real life were found to be the essential demotivating factors among Iranian seminary students. Having known the barriers of learning, the teachers and Islamic Propagation Office materials developers can organize their activities so that they would lead to better understanding of the lessons and improvement of teaching programs.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.425

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)0.0000.000

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 head0.102
GPT teacher head0.403
Teacher spread0.301 · 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 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

Citations25
Published2012
Admission routes1
Has abstractyes

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