How to Present Example-based Support to Improve Learning in ITSs? - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (ICCE, 2015)

Do Novices and Advanced Students benefit from Erroneous Examples differently? - Xingliang Chen; Tanja Mitrovic; Moffat Mathews (ICCE, 2016)

Do Erroneous Examples Improve Learning in Addition to Problem Solving and Worked Examples? - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (ITS, 2016)

Does Adaptive Provision of Learning Activities Improve Learning in SQL-Tutor? - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (AIED, 2017)

How Much Learning Support Should be Provided to Novices and Advanced Students? - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (ICALT, 2017)

A multistate model of wind farm in mountainous land considering ice coating. - Shu Wang; Ye Chen; Wenxia Liu; Zongqi Liu; Xingliang Chen; Qi Chen (IECON, 2017)

Exploring Adaptive Strategies for Providing Learning Activities. - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (UMAP, 2018)

Investigating the Effect of Agency on Learning from Worked Examples, Erroneous Examples and Problem Solving. - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (Int. J. Artif. Intell. Educ., 2019)

Learning From Worked Examples, Erroneous Examples, and Problem Solving: Toward Adaptive Selection of Learning Activities. - Xingliang Chen; Antonija Mitrovic; Moffat Mathews (IEEE Trans. Learn. Technol., 2020)

Detecting cerebral microbleeds via deep learning with features enhancement by reusing ground truth. - Tianfu Li; Yan Zou; Peng-Fei Bai; Shi-Xiao Li; Huawei Wang; Xingliang Chen; Zhanao Meng; Zhuang Kang; Guofu Zhou (Comput. Methods Programs Biomed., 2021)

An efficient multi-task forest fire and smoke detection model. - Cong Chen; Yunfei Liu; Chenyu Zhang; Junhui Li; Xingliang Chen (Eng. Appl. Artif. Intell., 2025)