Dr Guanliang Chen

Award category: Research

Guanliang's research applies state-of-the-art language technologies to leverage textual data collected in various educational settings and construct a more fair and inclusive learning environment.

Early in his PhD, Guanliang began investigating how computational technologies can help disadvantaged students access education. One notable example was his proposal to connect online education and online work at scale, enabling learners to apply the knowledge and skills they gained from massive open online courses (MOOCs) to earn money while studying.

He pointed out that MOOCs were limited in serving disadvantaged students, such as those from developing countries without a post-secondary degree. These learners often suffered from poor financial conditions and the need to earn an income limited the amount of time they could invest in their studies.

In a recent study published in the premier conference AI in Education, Guanliang also argued it was critical to investigate the algorithmic fairness of Machine Learning models in building automatic classifiers for educational forum posts. This was due to the important role of discussion forums in modern online learning management systems and the wide adoption of computational techniques to help instructors distinguish between educational forum posts.