Narrative research on Asian students’ interpretations and integrations of their worldviews studying in a Master of Education (MEd) program in Canada
Bibliographic record
Abstract
Canada is one of the favored destinations for Asian students to pursue their postgraduate study in Education. Asian students in this thesis refer to Chinese and Vietnamese students from Sinosphere influenced by Confucianism in East Asia. However, those graduate students often encounter a wide range of language, academic, social, cultural, and employment challenges. These challenges provide them opportunities to digest new experiences, reflect on their own knowledge and values, and integrate that knowledge into their own perspectives. Yet, these transformative experiences are seldom discussed. This thesis describes the experiences of six Master of Education students studying in Atlantic Canada. Utilizing narrative inquiry, important factors and mindsets relating to transformative growth are outlined holistically so that each participant's story can be understood through the context of lived experience. This study took place during the pandemic of COVID-19, so the findings are constrained by and informative of studying during the pandemic. Analyses included grouping participants into two characters, a single female and a female with family. Themes, contextual setting, actions, problems, and solutions were identified. Findings address how participants have interpreted their new experiences and integrated these experiences into their original worldviews studying in Canada and highlight how these events triggered them to internalize their experience and create meaning. Participants found increasing self-understanding and positive attitudes in learning as two experiences toward positive changes. In addition, the findings point to four major difficult experiences faced by participants: a lack of confidence in English speaking, insufficient crosscultural social connections, inadequate critical thinking ability, and limited choices in career. Implications focus on how to provide the total experience for students with the collaboration of the Education faculty, various departments in universities, the provincial governments, and future employers.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.005 |
| 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".