Predictors of Language Learners’ Preferences for Isolated/Integrated FFI: Big Five NEO-FFI Personality Traits
Bibliographic record
Abstract
With regard to increasing attention to focus on form in English language teaching, there has been a call for an integration of meaning-focused and form-focused instruction in the second language (L2) classroom. In this regard, this study is an attempt to examine the cross-relationship between Big Five personality traits (namely Neuroticism, Extraversion, and Openness to Experience, Agreeableness, and Conscientiousness) and EFL leaners’ preferences for two types of form-focused Instruction (FFI). The data is collected from 236 Iranian male and female who were EFL learners of different language institutes in Tehran, Iran. Participants were supposed to fill out the adopted Persian version of NEO-FFI personality trait inventory and Students’ preferences questionnaire. To substantiate a correlation between participants’ preferences for isolated/integrated FFI and Big Five personality traits, using 16th version of the Statistical Package for Social Sciences (SPSS), the Chi-square analysis was employed. The results indicated a significant relationship (χ2(4, n=236)=44.99, p=.001). The results are discussed in the light of this general findings and the study also provides some suggestions for future research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".