Voices from the Field: Perspectives of First-year Teachers on the Disconnect between Teacher Preparation Programs and the Realities of the Classroom
Bibliographic record
Abstract
The purpose of this qualitative phenomenological study was to explore common themes emerging from lived experiences of first-year secondary school teachers regarding their expectations of teaching prior to entering the teaching profession, as well as the realities in the classroom environment. In addition, factors influencing their decision to stay or leave the profession of teaching were also explored. A modified van Kaam method by Moustakas (1994) with in-depth, semi-structured interviews was employed to explore the lived experiences of 20 first-year teachers in the Delta, North Okanagan-Shuswap, and Kelowna school districts in British Columbia, Canada. The implications derived from this study suggest that curriculum developers of preparation programs and school district leaders can help improve retention and lessen disconnect by providing first-year teachers with the survival skills necessary to meet the demands of the classroom. The knowledge gained from this study may offer a clear understanding of reasons first-year teachers experience disparities between expectations of teaching and realities of the classroom, and how such disparities affect retention rate.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| 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".