Values Education Using Historical-Literary Works: Turkish Language and Literature Course Curriculum (Grades 9-12) and the Work of Şifâyî Entitled “Şerh-i Şebistân-ı Hayâl”
Bibliographic record
Abstract
Literary works, apart from being written with an artistic purpose, contribute to the transfer of some universal values to the reader. Thus, “values” continue to exist as they are transferred from generation to generation, similar to a context where the curriculum of a teaching process may work in the same way. The act of transferring universal values not only makes the existing work constant but also the value attempted to be taught in the same manner. The effective involvement of such works, which contain important information and the characteristics of the society of that period, has an important effect on the learning and teaching process of values. “Şebistân-ı Hayâl” is an advising work with a mixture of verse and prose written by Persian poet Fettâhî (d. 852/1448-49 or 853/1449-50) from which modern readers can also benefit. The text tries to convey universal values via using Islamic elements as a concrete base. Since Şebistân-ı Hayâl is written in the style of riddle, the advice that adorns the morality inside the text is difficult to understand. For this reason, according to the current information, Şebistân-ı Hayâl was expounded by Sürûrî in the 16th century and by Dervîş Muhammed Şifâyî in the 17th century. In this study, sample texts selected from Şerh-i Şebistân-ı Hayâl, written by Dervîş Muhammed Şifâyî, are examined in terms of basic “values” (p. 6); justice, friendship, honesty, self-control, patience, respect, love, responsibility, benevolence that takes place in the Secondary Education Turkish Language and Literature Course Curriculum (9-12 Grades). As it is stated in the curriculum (MEB, 2019, p. 6), these values will come to life in teaching and learning process, not only by themselves, but also by the sub-values they are related to and also with other basic values as well.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".