Analysing the Listening Texts in the Textbooks Used in Teaching Turkish to Foreigners in Terms of Word Types: New Istanbul Turkish for International Students Course Book A1
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Bibliographic record
Abstract
The purpose of this study is to examine the vocabulary included in listening texts in the textbooks used in teaching Turkish to foreigners according to their types. The study was limited to New Istanbul Turkish For International Students Course Book—A1 level. Accordingly, a total of eighteen listening texts in six units were analyzed. The document analysis method was used in the study. For this purpose, the words in the listening texts were analyzed as nouns, verbs, and phrases according to the distinction in the word list in the source of the study. In the analysis of the texts, the word types in the listening texts were compared with the word list shared with the reader at the end of each unit, and this ratio was reflected in the word types of tables with numerical values. Accordingly, a total of 592 words were included in eighteen listening texts. Of these, 429 are nouns, 129 are verbs and 34 are phrases. While a total of 957-word types are included in the word lists given in the book, 754 of them are nouns, 179 of them are verbs and 24 of them are phrases. When the word types within the listening texts in the book were analyzed, it was found that 149 out of 592-word types were used again. Another comparison is related to common uses. The word types in the listening texts were compared with the word lists in the textbook and 137 common word types were found. When at the distribution of word type preferences in the listening texts from the first unit to the last unit, it is observed that nouns, verbs, and phrases are partially distributed in a balanced way.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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