Kudos: Article by Xiaoming Zhai featured on Wiley

A research article authored by Xiaoming Zhai, an assistant professor in the Department of Mathematics and Science Education, was recently featured on Wiley as the most newsworthy research article across the company’s journals.

Zhai’s article, “From substitution to redefinition: A framework of machine learning‐based science assessment," highlights the potential of machine learning—a subset of artificial intelligence—in science education. In the article, Zhai and his colleagues examine how machine learning has revolutionized the capacity of science assessment in terms of tapping into complex constructs, improving assessment functionality, and facilitating scoring automaticity. They developed a framework to conceptualize the use and evolution of machine learning in science assessment, identified various ways in which machine learning transformed traditional science assessment, and anticipated impacts on science education.

The article was published in the Journal of Research in Science Teaching, the flagship journal of the National Association of Research in Science Teaching.