Why Choose Electrical Subjects? Profiling and Analyzing Motivations of Kuwaiti Pre-Service Teachers
Bibliographic record
Abstract
The aim of this study was to determine factors that influence Kuwaiti pre-service teachers’ choice of Practical Electrical Subjects by profiling and analysing their motivations. Unlike previous studies that focused on the traditional conceptualisations of intrinsic, altruistic, and extrinsic motivations, this study uses the interpretive lens of Expectancy Value Theory which forms the foundation for the Factors Influencing Teacher Choice model to analyse and describe factors that influence the pre-service teachers’ career choice decisions. One hundred fifty-six pre-service teachers enrolled in a teacher education programme completed the Factors Influencing Teacher Choice survey on which they rated 25 motivational factors. T-tests and One-way ANOVA were used to examine differences based on gender and year of study. Self-efficacy beliefs, social utility value, time for family, job security and prior teaching and learning experiences were important career choice determinants. Fall back career was the least important motivational factor. Gender was found to significantly influence their career choice while year of study did not significantly influence their decision. In general, female pre-service teachers appeared to be more motivated to choose teaching electricity as a practical subject than males. The pre-service teachers’ year of the study showed significant variations only regarding social utility values and fallback career. The results of this study would contribute to existing literature on factors influencing pre-service teachers to choose a teaching career that involves vocational or practical subjects’ teachers. Some theoretical and practical implications are drawn for pre-service teacher education.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".