Quanlong Guan
Biographic Data
| ID | 9493998 |
|---|---|
| NAME | Quanlong Guan |
| GIVEN NAMES | Quanlong |
| FAMILY NAME | Guan |
| SIGNATURE | GUAN Q |
| AFFILIATIONS | Department of Computer Science Jinan University Guangzhou China |
| ORCID | 0000-0001-6911-3853 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Can AI support human grading? Examining machine attention and confidence in short answer scoring
Large language models built upon artificial intelligence (AI) hold great promises to innovate automatic short answer scoring (ASAS) - significantly alleviating educators’ workload in assessing student answers. However, ASAS systems on such basis have seen limited adoption in authentic teaching environments due to the models’ inability to explain the predictions they generate. To address this, we recruited 32 human graders to comparatively analyse…
When and how biases seep in
The use of predictive analytics powered by machine learning (ML) to model educational data has increasingly been identified to exhibit bias towards marginalized populations, prompting the need for more equitable applications of these techniques. To tackle bias that emerges in training data or models at different stages of the ML modelling pipeline, numerous debiasing approaches have been proposed. Yet, research into state‐of‐the‐art techniques fo…
Students’ experience of online learning during the Covid‐19 pandemic
Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID‐19 pandemic. Even though online learning research has been advancing in uncovering student experiences in various settings (i.e., tertiary, adult, and professional education), very little progress has been achieved in understanding the experience of the K‐12 student population, especially when narrowed down to dif…
No prominent works on this page.
Students’ experience of online learning during the Covid‐19 pandemic
Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID‐19 pandemic. Even though online learning research has been advancing in uncovering student experiences in various settings (i.e., tertiary, adult, and professional education), very little progress has been achieved in understanding the experience of the K‐12 student population, especially when narrowed down to dif…
Can AI support human grading? Examining machine attention and confidence in short answer scoring
Large language models built upon artificial intelligence (AI) hold great promises to innovate automatic short answer scoring (ASAS) - significantly alleviating educators’ workload in assessing student answers. However, ASAS systems on such basis have seen limited adoption in authentic teaching environments due to the models’ inability to explain the predictions they generate. To address this, we recruited 32 human graders to comparatively analyse…
When and how biases seep in
The use of predictive analytics powered by machine learning (ML) to model educational data has increasingly been identified to exhibit bias towards marginalized populations, prompting the need for more equitable applications of these techniques. To tackle bias that emerges in training data or models at different stages of the ML modelling pipeline, numerous debiasing approaches have been proposed. Yet, research into state‐of‐the‐art techniques fo…
Computer Science (3 works) · Psychology (2 works) · AI-based Problem Solving and Planning (1 work) · Analytics (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · China (1 work) · Coronavirus disease 2019 (COVID-19) (1 work) · COVID-19 and Mental Health (1 work) · Data science (1 work)