Promoting Students' Learning in Student-Centered Classrooms: Positive Teaching Experiences of Middle Years Teachers in China and Canada
Bibliographic record
Abstract
The purpose of this study was to explore the selected middle years teachers’ experiences of promoting student learning in student-centered classrooms, and how these recalled experiences might affect their own future teaching and assist other teachers to promote student learning. Based on social constructivism as the epistemological foundation, I chose Appreciative Inquiry (AI) as the research methodology. AI values people’s positive experiences and emphasizes the importance of the positive core of change (Cooperrider & Whitney, 2000). In total, there were 53 middle years teachers in China and Canada who responded to an online survey. Four Chinese education experts were interviewed online, and 12 Canadian education experts participated in an interpretation panel. The findings showed that both Chinese and Canadian participants believed that engaging students in their learning was the core of creating student-centered classrooms. They regarded group study as the most popular instructional strategy that was used to promote student-centered learning. Most participants stated that they had changed or planned to change their teaching practices because they had positive teaching experiences in student-centered classrooms. Chinese participants stated that they had shared their positive teaching experiences with other teachers at three levels: school divisions/districts, schools, or grades/subjects. The main activities for communication among Chinese teachers included group discussion, collective lesson planning, and classroom visits. Canadian participants reported that they usually shared their educational ideas and teaching experiences with other teachers in both formal and informal ways, such as chatting with each other during breaks, developing learning projects together, and communicating with each other through school networking websites. In addition, findings also showed that most Chinese middle years teachers teach a single subject, but many Canadian middle years teachers teach multiple subjects. Based on this research, I suggested that teachers should apply multiple instructional strategies in their classrooms, serve students, and collaborate with parents/families. School boards and schools should make more efforts to encourage their teachers to communicate with each other, formally and regularly by providing policy, technical, and financial supports for relevant programs and activities. Teachers should choose either a single subject or multiple subjects to teach according to their own willingness and abilities. Future researchers may benefit by using Appreciative Inquiry to explore people’s positive experiences in education, and should be more open-minded by conducting cross-cultural and inter-cultural research to facilitate educators to communicate with each other and learn from each other.
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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 | 0.001 | 0.002 |
| 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 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".