Investigating the Relationship between Tolerance of Ambiguity, Individual Characteristics and Listening Comprehension Ability among Iranian EFL Learners
Bibliographic record
Abstract
This study investigated the relationship between tolerance of ambiguity, individual differences and the listening comprehension ability of university students. The study was carried out at Azad University of Ahvaz, Foreign Languages Teaching Centre. It involved 150 MA and BA students in the Faculty of language teaching center in university (78 females, 72 males) with the age range of 18-40. At first the Persian version of the questionnaire of tolerance of ambiguity provided by Ely (1995) was distributed among students of each class. Then the second questionnaire which was listening comprehension one was given to the students to collect the data on the base is of these hypotheses: H01: There is no significant relationship between university students’ tolerance of ambiguity and their listening comprehension ability. H02: Gender has no effect on tolerance of ambiguity of the students. H03: There is no significant relationship between age and student’ tolerance of ambiguity. H04: There is no significant relationship between academic level and students’ tolerance of ambiguity Findings showed that there is a significant relationship between tolerance of ambiguity and listening comprehension. To answer second hypothesis, independent samples t-test was run. The results showed that gender did not have any significant impact on the students’ ambiguity tolerance. The results one-way ANOVA depicted that there is significant difference between three different age groups (below 25, between 25-29, and above 29) (p<0.05) in terms of tolerance of ambiguity (F=4.291), p=0. 015. And at last, the results of the independent sample t-test showed that there is a significant difference between these two academic levels in tolerance of ambiguity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".