ABSTRACT
This chapter explores the extent to which extent phraseological features are related to human judgements of writing quality in science, technology, engineering, and mathematics (STEM) writing. A corpus of technical progress reports written by engineering students is analyzed based on a group of n-gram measures in the setting of a Hong Kong university. Via the application of regression analyses, the chapter presents that two n-gram measures (i.e., bigrams of spoken English) are strong predictors of writing scores assigned by English teachers in a STEM English course. Since phraseological features have been underexplored in corresponding research, this chapter expands our understanding of the important role of phraseological usage in STEM writing.
