Novice Early Childcare Educators’ Experiences Applying Pre-service Education Knowledge and Theories in Practice at Childcare Centers
Bibliographic record
Abstract
Some novice early childhood educators (ECEs) experience barriers to applying knowledge gained during their pre-service education in practice and experimenting with their roles at childcare centers. The purpose of this basic qualitative study was to explore novice ECEs’ experiences of barriers to applying knowledge gained during their pre-service education in practice at childcare centers. Mezirow’s transformative learning theory grounded this study by describing adult learners’ personal transformation from obtaining and understanding new knowledge to applying it in practice. For this study, eight adult learners who completed an early childhood education program, had up to 5 years’ experience, held a current license to practice, and were currently working at a licensed childcare center in Canada were recruited through professional early childhood educator networks. The data from the semistructured interviews were analyzed thematically with the following themes emerging: insufficient training, misaligned values, inadequate educator-to-child ratios, poor leadership, toxic environments, poor intrapersonal and interpersonal skills and communication, and lack of opportunity. The results support positive social change by helping curriculum developers, early childcare education leaders, and licensing policymakers understand the barriers novice ECEs experience. This insight can inform improvements to pre-service education curriculum, enhance practicum placements, strengthen industry leadership practices, and guide licensing regulation revisions. Such knowledge equips leaders to strengthen early childhood education systems, helping novice ECEs grow into confident, competent educators who foster healthy child development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".