An Autobiographical Narrative Inquiry into my Personal Practical Knowledge: Awakening to Early Childhood Pedagogical Tensions
Bibliographic record
Abstract
My research is an inquiry into how I navigate between external expectations such as programmatic curriculum (Doyle, 1992), requested pedagogies, and internal beliefs and values derived from my personal practical knowledge (Clandinin, 1985). Reflecting on my lived experiences and using Schwab’s conceptualization of curriculum as a tool of analysis, I investigate my personal practical knowledge and how I act on it in my teaching. I employ autobiographical narrative inquiry methodology to explore the tensions and incompatibilities I experienced as an immigrant teacher of early childhood children in Saskatchewan, Canada. As a qualitative research methodology, narrative inquiry foregrounds “how humans make meaning of experience by endlessly telling and retelling stories about themselves that both refigure the past and create purpose in the future” (Connelly & Clandinin, 1988, p. 24). This methodology takes the form of stories (Saleh et al., 2014), presupposing “narrative as a kind of life story” (Connelly & Clandinin, 1988, p. 24). In researching theories to come to understand my unresolved feelings as an early childhood educator (ECE) and teacher of young children, I found that theory and practice do not always sit compatibly with each other (Schwab, 1973). As I shared my lived stories, and introduced the origins of my personal practical knowledge, I became aware of incompatibilities between some curriculum mandates and my own knowing. With that realization, I chose to make my narrative inquiry research methodology autobiographical. Studying my experiences in this autobiographical narrative inquiry, I engage in “telling and retelling, and reliving [to] deal with questions of who [I am] in the field [of education] and who [I am] in the texts that [I] write about my experiences [as a teacher]” (Clandinin & Connelly, 2000, p. 70). As I traced back to my early childhood, upbringing styles, learning experiences, mothering experiences, and my teaching practices, I realized that many of my understandings are rooted in my Confucian upbringing. I realized I also sought to overcome the limitations of this traditional approach by incorporating Western-based play and child-centred pedagogies into my teaching, learning, and mothering experiences. At the end of my thesis journey, I came to understand that a curriculum can represent one’s course of action in life, as the broad sense of curriculum encompasses a person’s life experiences (Connelly & Clandinin, 1988). Therefore, I am not only a curriculum implementer but I create curriculum collaboratively with my students in the classroom every day as we grow together.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 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".