Factorial Validation of Teachers’ Self-Efficacy Scale using Pre-Service Teachers: Implications for Teacher Education Curriculum
Bibliographic record
Abstract
Teachers’ beliefs in their ability to effectively handle the tasks that are related to their professional activity are an issue of concern for pre-service teachers. Many of them have low self-efficacy which can affect their output in future, and this can influence important academic outcomes on learners. The main purpose of this study was to factorially validate teachers’ self-efficacy scale (TSES) using pre-service teachers in public colleges of Education in Enugu State. A sample of 218 year three students in the schools of sciences and social sciences was drawn from a population of 2,127 students of public colleges of Education in Enugu State. Simple random sampling technique was used to draw two schools from the five schools in each of the colleges. Accidental sampling was used to draw the participants. The study adapted the teacher self-efficacy scale developed by Ma, Trevethan and Lu (2019). The instrument was construct validated using factor analysis while the internal consistency and stability reliability indices were estimated using Cronbach alpha method and Pearson correlation. The exploratory and confirmatory factors analyses were done using principal component matrix with Varimax rotation, while data model fit was tested using root mean square error of approximation (RMSEA) and confirmatory factor index (CFI). Statistical Package for Social Sciences (SPSS) and Analysis of a Moment Structures (AMOS) software were used to conduct the statistical analysis. The results showed that the scale was found to be valid and reliable and as well demonstrated a good model fit (RMSEA = .043, CFI = .943). The study has implication for teacher education training institutions in that the scale can be used as an effective instrument for determining the teaching self-efficacy of the pre-service teachers. Thus, it was recommended that various higher institutions for teacher education should make effective use of TSES in ascertaining the teaching self-efficacy of the pre-service teachers, especially during teaching practice exercises.
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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 | 0.013 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".