Kangxi Li
Biographic Data
| ID | 6091098 |
|---|---|
| NAME | Kangxi Li |
| GIVEN NAMES | Kangxi |
| FAMILY NAME | Li |
| SIGNATURE | LI K |
| AFFILIATIONS | Hefei University of Technology |
| ORCID | 0009-0002-6442-6695 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
GAI vs. AWE in writing feedback
This study compared the effects of generative artificial intelligence (GAI) feedback (ChatGPT) and automated writing evaluation (AWE) feedback (Pigai) on student engagement from behavioural, affective, and cognitive perspectives. Using a quasi-experimental design with 105 Chinese EFL learners, data were collected from pre- and post-intervention questionnaires, supplemented by immediate attitudinal ratings, revision analyses, and time-on-task reco…
Test fairness of the in-house College English examination for Chinese non-English major undergraduates
Introduction The in-house College English examination is a high-stakes assessment for College English, a compulsory course for most non-English major undergraduates in China. However, the fairness of such examinations has not received due attention. Methods This paper employs Kunnan’s Test Fairness Framework to investigate common issues of test fairness related to the in-house College English examination, using a university in East China as an ex…
Student Engagement With AI Feedback
This study explored the behavioral, cognitive, and affective engagement of 11 ethnic minority students with AI writing feedback at a Chinese research university. Using a qualitative approach, the research collected data from student drafts, screen recordings of revision processes, AI user logs, and follow‐up interviews with participants, including two Kazakh, two Uyghur, three Mongolian, and four Tibetan students. Findings revealed diverse studen…
Variability in Article Use Among Chinese EFL Learners
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Variability in Article Use Among Chinese EFL Learners
Test fairness of the in-house College English examination for Chinese non-English major undergraduates
Introduction The in-house College English examination is a high-stakes assessment for College English, a compulsory course for most non-English major undergraduates in China. However, the fairness of such examinations has not received due attention. Methods This paper employs Kunnan’s Test Fairness Framework to investigate common issues of test fairness related to the in-house College English examination, using a university in East China as an ex…
Student Engagement With AI Feedback
This study explored the behavioral, cognitive, and affective engagement of 11 ethnic minority students with AI writing feedback at a Chinese research university. Using a qualitative approach, the research collected data from student drafts, screen recordings of revision processes, AI user logs, and follow‐up interviews with participants, including two Kazakh, two Uyghur, three Mongolian, and four Tibetan students. Findings revealed diverse studen…
GAI vs. AWE in writing feedback
This study compared the effects of generative artificial intelligence (GAI) feedback (ChatGPT) and automated writing evaluation (AWE) feedback (Pigai) on student engagement from behavioural, affective, and cognitive perspectives. Using a quasi-experimental design with 105 Chinese EFL learners, data were collected from pre- and post-intervention questionnaires, supplemented by immediate attitudinal ratings, revision analyses, and time-on-task reco…
Cognition (2 works) · Computer Science (2 works) · Higher education (2 works) · Psychology (2 works) · Student Assessment and Feedback (2 works) · Student engagement (2 works) · Academic achievement (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · China (1 work) · College English (1 work)