Classroom Teacher Candidates’ Metaphoric Perceptions Regarding the Concepts of Reading and Writing: A Comparative Analysis
Bibliographic record
Abstract
The purpose of this study is to determine and compare candidate classroom teachers’ metaphoric perceptions about reading and writing. The study was conducted with teacher candidates who were studying at Omer Halisdemir University’s Department of Elementary Education in Nigde/Turkey during 2016-2017 academic year. A total of 266 1st, 2nd, 3rd and 4th grade candidate classroom teachers participated in the study. The study design was organized according to phenomenological design. According to the study findings, teacher candidates created 23 metaphoric categories in reading, 17 in writing and 15 in both reading and writing. The most categories developed by classroom candidate teachers on the concept of reading is necessity. As to writing; the most categories developed by classroom candidate teachers on the concept of writing is on expressing feelings. The category with the least metaphor about writing concept is the negativity and watching. The common metaphors used by the classroom teacher candidates regarding the concepts of reading and writing are mostly gathered in the categories of water and its derivatives and life. Whereas the category with the least common metaphors about is infinity. Another result of the research is that the teacher candidates produce a more negative number of metaphorical concepts in the writing concept. Metaphors on the concept of writing are outpouring, effusion and the man himself. As a result, metaphors can be used as a research tool to determine teacher candidates' perceptions and opinions about reading and writing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".