Why teaching? Perspectives from first-year South African pre-service teachers
Bibliographic record
Abstract
South African initial teacher education institutes are currently experiencing an annual increase in admissions of first-year students. In addition, the increasing attrition rate of newly qualified teachers is of concern globally. This begs the question of why students are opting for teaching as a profession. This study focuses on reasons why first-year students have opted to study teaching at a South African University. The theoretical lens used is linked to the expectancy-value theory of achievement motivation (Wigfield & Eccles, 2000). Five hundred and eighty first year students participated in a mixed methods research study. Data was analysed by using theories of career motivation categories namely altruistic, extrinsic and intrinsic reasons. The findings indicate that more than half (60%) of the participants were motivated to do teaching for altruistic reasons, followed by almost a quarter (23%) choosing teaching for extrinsic reasons and lastly 17% opting to become teachers for intrinsic reason. This paper argues that it would be prudent for initial teacher education institutes to understand students’ rationale for selected teaching to support them to complete their qualification and remain in the profession.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".