The Role of the Dalton Plan-Based Instruction in Enhancing Learner Autonomy and Reading Proficiency for Chinese College English Students
Bibliographic record
Abstract
This study explored the role of the Dalton Plan-based instruction in improving learner autonomy and reading performance among non-English major university students in China. A quasi-experimental design was utilized to reach the goal. The Dalton Plan-based instruction in this study consists weekly individual sessions and monthly class meetings, which were held on the basis of the problems reported in students’ self-reports in accomplishing their reading assignments. The experiment was undertaken in one university characterized by students from multi-ethnic background in China. The participants were 62 second-year non-English major students from medical college of the university, thirty-two of them makes the experimental group, the rest 30 composes the control group. The experimental group received the Dalton Plan-based instruction and the control group received conventional classroom instruction. The quantitative data of Autonomous Learning Scale and reading tests were collected and analyzed to answer the research questions. The results of this study revealed that the Dalton Plan-based instruction was more conducive to building learner autonomy and improving reading proficiency than conventional instruction, and there’s a moderate positive relationship between the learner autonomy and reading proficiency among College English learners under the Dalton Plan-based instruction.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".