Intentional Vocabulary Learning Vs Incidental Vocabulary Learning for Beginner Students: Tishk International University Preparatory School Case
Why this work is in the frame
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Bibliographic record
Abstract
Incidental vocabulary learning takes place during reading texts extensively while intentional learning requires extra studies on words. Although incidental learning is very effective in the long run, it does not help students much to learn different lexical features of the words. Even more, it is mostly not possible to guess the correct pronunciation of the words in English. What is more, the words get different prepositions from the native language of the learners, which causes overgeneralization and goes wrong. In this study, two groups of students were given a story to read, and intentional vocabulary study was done with them. For the next group, they just read the story and took the exam. The result showed that the group which did intentional study gave out better results than the other group although the latter was more successful in general.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it