Chinese university students’ conceptions of feedback and the relationships with self-regulated learning, self-efficacy, and English language achievement
Bibliographic record
Abstract
In China, under the influence of examination-driven culture and teacher-centered ways of learning, students' self-regulated learning (SRL) capabilities, self-efficacy, and actual English proficiency are greatly hindered. Given this situation, the Chinese Ministry of Education has promulgated the use of formative assessment in the College English curriculum at the tertiary level since 2004. Feedback, as an integrated part of formative assessment, takes up the largest proportion of the Chinese College English classroom assessment and intends to facilitate SRL and learning. However, whether feedback could facilitate students' SRL and learning has not been fully investigated in this context in China. Therefore, this study first explored how students self-reported their conceptions of feedback, SRL, and self-efficacy, and second, the relationships among these constructs and their English language achievement in the College English course. A questionnaire was used to collect data on students' conceptions of feedback, SRL, self-efficacy, and self-perceived English language proficiency. Their English test scores as an indicator of English language achievement were also collected. A total of 538 participants from a university in Northern China participated in this study. Data were analyzed using descriptive statistics, exploratory factor analyses, Pearson correlation analyses, and multiple regression analyses. The results found that Chinese students from the College English course reported a high level of conceptions of teacher and peer feedback, SRL, and self-efficacy, yet a low level of Teacher/Peer Feedback Ignored. For the relationships among these variables, students' conceptions of feedback contributed to SRL and self-efficacy. Besides, self-efficacy was found to be the strongest predictor for self-perceived English language proficiency and standardized English test scores, both indicators for English language achievement. From the theoretical perspective, this study addressed the research gap in the literature by examining four constructs together, that is, students' conceptions of feedback, SRL, self-efficacy, and English language achievement within a university context in China. From the pedagogical angle, the results can also support teachers in their feedback practices to facilitate students' SRL, self-efficacy, and learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".