Mentorship as a professional development tool: Addressing early childhood female teachers' lived experiences and perceptions
Bibliographic record
Abstract
In this article, I explore mentorship as a crucial professional development tool for novice teachers in Early Childhood Education (ECE), focusing on its role in identifying challenges and highlighting the lived experiences and perceptions of novice teachers, as well as those of school principals. I explore how structured mentorship and induction can provide essential support to novice teachers, particularly in a developing, inclusive, diverse, and transformative professional development program to support the contexts in which mentorship frameworks are inconsistent. Grounded in the Positioning Theory, Bosadi Theory, and in Ubuntu Theory, I report on how power dynamics, hierarchical structures, and collective responsibility shape mentorship experiences of novice teachers in ECE. I use a triangulation of the Positioning Theory to help explain how novice teachers navigate professional identity and relationships with mentors and school leadership, the Ubuntu Theory to emphasise the importance of communal support and shared responsibility in teacher development, and Bosadi Theory to narrate the lived experiences of female novice teachers in ECE. I used a qualitative methodology in an interpretivist paradigm, so the semi-structured interviews with six novice ECE teachers and two principals provided insights into their professional experiences. The findings reveal significant challenges related to mentorship; issues such as work overload, power dynamics, time management, and emotional support or the lack thereof emerged as critical. This article contributes to the limited South African literature on novice teacher support, and it advocates for formal mentorship programmes rooted in equity, collaboration, and collective growth. The findings also hold global relevance, in emphasising the need for structured, community-driven mentorship to improve teacher retention worldwide. Keywords: mentorship, induction, professional development, novice teachers, early childhood education
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 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".