Assessment of Psychological Readiness Situation of Students Starting to Primary School
Bibliographic record
Abstract
There are important responsibilities expected from primary school students. The most important of these are the learning of reading, writing and arithmetic. There is a “psychological readiness” aspect besides reading, writing and arithmetic in order to be ready for the school. In this study, among the first-grade students, those who were academically ready were compared with those who were psychologically ready. In this research, screening model is used from quantitative research methods. Screening surveys allow the answers of questions such as “what, where, when, how often, at what level, how” (Wellington, 2006). The population of the research was composed of the children who started to the first class of primary schools in the provincial center of Ankara and the provincial center of Agri in the 2016-2017 academic year. The sample group of the study consisted of 327 students. 80 girls and 75 male students out of 322 students are chosen from the schools in the provincial center of Ankara, and 87 girls and 80 boys are chosen from the schools in provincial center of Agri. While the number of literate students at the basic level is 95 before the school starts, only 46 students are able to link shoe laces. While a total of 255 students knew all the main colors before the school started, only 31 students knew their home address. In addition, 90 students were found to have problems complied with the school rules. 39 students are shy in the classroom.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".