Paying Lip Service to Education: An investigation of Teacher Candidates' Perceptions of 21st Century Learning
Bibliographic record
Abstract
This thesis is a study of beginning teachers’ concept of self at the precarious juncture between teacher education and a career in the classroom. Given that the practice of teaching sits at the juncture of past methods and proposed “new” models for teaching and learning, the ways preservice teachers take up the history of teaching in Ontario, their past learning experiences, and personal memories was of significance in understanding how they see themselves as future educators. Situated within curriculum studies, and using currere (Pinar, 1975) as a methodology, this inquiry focuses on the experiences of four Bachelor of Education students at a university in Ontario, Canada. Interviews were structured around the four stages of currere (regressive, progressive, analytic, and synthetic) and sought to unpack how the autobiographical free-associative utterances of teacher candidates might be read with and against the larger context of “21st century teaching and learning” competencies published by the Ontario Ministry of Education which are meant to guide their careers. Using rhetorical analysis to identify the repetitions, ambivalences, metaphors, detours, free associations, and symbolizations in the interviews, the teacher candidate narratives were coded for repetitions and meanings using a psychoanalytic stylistic. Looking at the ways the unconscious performs consciously provides insight into the ways teachers take up existing societal discourses and return to childhood experiences and traumas to forge their emerging teacher identities. The findings of this study indicate that preservice teacher candidates are ambivalent about both the language and implementation strategy of 21st century competencies even as they struggle with their own personal identity formation as educators in relation to the expectations placed upon them from the Ministry. As well, the participants return, in their free associative narratives, to scenes of learning and not-learning in childhood to guide them in their understanding of what it means to be a good teacher in the present moment. Weaving memories of childhood learning with new knowledge acquired in teacher education, each participant defines 21st century learning and its necessary knowledge and appropriate emotional register differently. Th multiplicity of subjectivities that emerges lends rich insight into the differences in teacher identities even as students emerge from the same undergraduate program. Furthermore, this study lays the groundwork for future examination of 21st century learning objectives in a post-COVID-19 context and what the implications might be for new teacher identities as historical discourses of what it means to learn and succeed invariably need to change as students move out of the brick-and-mortar schoolhouse to remote and virtual learning.
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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 | 0.004 | 0.013 |
| 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 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".