Finding a place for AI in science education

A new review published in the Journal of Research in Science Teaching says there is potential for machine learning to revolutionise the assessment aspect of science education. 

Authors of the report initiated a review of 47 studies prior to the COVID-19 outbreak but believe that the pandemic highlights the need to examine cutting-edge digital technologies while we assess and reframe the future of education and learning. 

The researchers developed a framework to conceptualise machine learning applications in science assessment. They authored an article that aims to example how this subset of artificial intelligence has revolutionised the capacity of science assessment in terms of tapping into complex constructs, improving assessment functionality and facilitating scoring automaticity. 

Based on their investigation, the researchers identified various ways in which machine learning has transformed traditional science assessment, as well as anticipated impacts that it will likely have in the future (such as providing personalised science learning and changing the process of educational decision-making).

"Machine learning is increasingly impacting every aspect of our lives, including education," said lead author Xiaoming Zhai, an assistant professor in the University of Georgia's Mary Frances Early's Department of Mathematics and Science Education.

"It is anticipated that the cutting-edge technology may be able to redefine science assessment practices and significantly change education in the future."

A full copy of the paper can be found here. 

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