Analyzing Entrepreneurship Skill Levels of the 3rd Grade Primary School Students in Life Sciences Course Based on Different Variables
Bibliographic record
Abstract
The purpose of this study is to investigate Life Sciences course entrepreneurship skills of the 3rd grade primary school students as evaluated by their parents. The study was conducted with the screening model. The participants of the study were the parents (47 mothers and 23 fathers) of the students (32 girls, 38 boys) who study in the center of the province of Adiyaman, Turkey, in the academic year of 2017-2018. In order to collect the data, “entrepreneurship skill condition” survey form, which evaluates the entrepreneurial gains from the 1st and 2nd grade Life Sciences course, was used. According to the findings, the entrepreneurship skill level of the students was found 98.81 out of 130, which is “good”. The entrepreneurship skill level of the students showed a significant difference depending on the parent variable, where mothers evaluated their children more favorably compared to fathers. The entrepreneurship skill level of the students did not show a significant difference depending on their gender. Depending on their success in the school and the Life Sciences course, however, there was a significant difference (p<0.05) in their entrepreneurship skill level. A positive correlation was detected between the entrepreneurship skill level and the success in the school and the Life Sciences course. The entrepreneurship skill level of the students also varied significantly (p<0.05) depending on their self-confidence level. High self-confidence and the entrepreneurship skill level were found to be positively correlated.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".