Opinions of Primary Teacher Education Students on Extra-Curricular Activities in Education
Bibliographic record
Abstract
The aim of this study is to reveal the opinions of the Primary Teacher Education students in terms of the Extra-Curricular Activities in Education (ECAE) course. In this study, in which a qualitative research method was used, the case study design was preferred. In this context, the subjects of the research consist of 77 Primary Teacher Education students studying in Sivas Cumhuriyet University, Faculty of Education. Data were collected through a semi-structured interview form consisting of 7 open-ended questions. The content analysis method was employed in the analysis of the data. As a result of the research, it was determined that most of the students did not have an idea on the ECAE course at the beginning of the term. The ECAE course contributed to the students in “Cognitive”, “Social”, “Affective” and “Psychomotor” fields. The ECAE course improved the skills of receiving support, increasing self-confidence in public, and establishing an ability to communicate about communication with stakeholders. While preparing the activities related to the ECAE course, the students encountered problems related to the activity, personal, intra-group, technical, material related, time, official procedure, and place problems and they offered solutions to these problems. The ECAE course enabled students for learning material properties, developing handicraft skills, developing creativity, improving imagination, augmenting one’s willingness to utilize materials, increasing the frequency for utilizing materials, and ensuring ideas to be put into practice regarding students’ skill to utilize materials. Finally, the ECAE course positively affected the students’ skills to use educational technology. The students stated that they learned to use a computer, to make use of the internet, how to use technology more effectively, and that they became practical in utilizing the technology.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".