Analysis of Self and Peer Evaluation in Basic Volleyball Skills of Physical Education Teacher Candidates
Bibliographic record
Abstract
It might be of vital importance that teachers, who are the backbones of education system, should obtain their skills related to educating students who are in harmony with modern life in their process as teacher candidates. Physical education teachers should obtain features of quality teaching and using alternative methods of measurement during their bachelor’s degree education. Thus, the aim of this study is to analyze efficiency of teacher candidates in movement analysis, self-evaluation and peer evaluation for four basic volleyball skills (forearm pass, setting, underhand serve and overhand serve). In the process of obtaining data, four observation forms were used. In the evaluation of forearm passing and overhand serve, observation forms developed by Ghorbanzadeh Koshki (2013) were used as evaluation tools. For overhand pass and underhand serve, observation forms developed by the researcher and experts were used. Also, information related to genders and ages of the teacher candidates was recorded. In the analysis of the data, t test, Pearson correlation and partial correlation tests were used. In the reliability analyses, interclass correlation coefficient (ICC) and Cronbach Alpha analyses were used. As a result, the teacher candidates’ scores for self-evaluation of their skills and their peers’ scores were found to be correlated. No significant difference was found between the two evaluations. The findings were discussed in the frame of the importance for physical education teacher candidates to learn to analyze moves and to use alternative measurement techniques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 teacher head, 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".