Assessment for learning in a chinese university context: a mixed methods case study on english as a foreign language speaking ability
Bibliographic record
Abstract
This study investigates the effectiveness of Assessment for Learning (AFL) in improving oral English skills and explores students' and teachers' perceptions of AFL.The study took place at a university in China and involved both students and teachers of English at the institution.Chinese university level students were reported to be facing difficulties in their oral skills learning and were not satisfied with the oral English instruction they were receiving because it is related too much to large-scale tests administered in China (He, 1999;Liao & Qin, 2000;Wen, 2001).Classroom-based assessment, known as the alternative assessment approach, has attracted increased interest from researchers since the end of the last century (Genesee & Upshur, 1996;Gipps 1999; Shepard, 2000; Turner, in press).One approach to classroom-based assessment, Assessment for Learning (AFL), has proved a significant influence on language performance by encouraging learners' participation, identifying learners' weaknesses, providing instructors with useful feedback for learners' further development, and turning learners into autonomous learners (Black & Wiliam, 1998ab;Black, Harrison, Lee, Marshall, & Wiliam, 2003;Winne & Butler, 1994;Topping, 2009).In this study, a mixed methods design incorporating both quantitative and qualitative methods (Creswell & Plano Clark, 2009) is used to examine the effectiveness of AFL and to explore teachers' (n = 9) and students' (n = 74) perceptions of AFL.There are three phases in this study: the preparation phase, and Phases One and Two.In the preparation phase, second year students' and their préparation et la phase un et deux.Dans la phase de préparation, les étudiants de deuxième année ainsi que l'interaction des enseignants avec leur classe pour aider à la sélection des participants à l'étude.Dans la phase un, les questionnaires des enseignants, les questionnaires des étudiants ex-ante et ex-post et trois tâches de l'AFL ont été employés et leur données ont été collectés et analysé quantitativement en utilisant une analyse statistique descriptive de façon à déterminer l'efficacité de l'AFL.Dans la phase deux, les enseignants et les étudiants ont été interviewés de façon à collecter leurs opinions sur l'AFL.Les interviews ont été traduits du chinois à l'anglais, ils ont été transcrits et leur contenu à par la suite été analysé.Les résultats des trois phases ont été intégrés de façon à pouvoir interpréter les résultats de l'étude.Les résultats indiquent que l'AFL peut en effet augmenter la capacité d'apprentissage de l'anglais oral des élèves de niveau intermédiaire et élevé.De plus, les résultats montrent que les enseignants et les étudiants réagissent positivement à l'ALF.v viii Student participants.................
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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 | 0.014 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".