"She kinda kookie but she is a sweet lady" : How student evaluations on a professor-rating website reveal the students’ concerns about English language education

This study used a corpus-informed approach to identify students’ key concerns regarding their English language education. To address the complexity of key elements in student evaluations, the data collection involved students’ comments from 2012 to 2022, regarding their English language professors across different English-related departments at several institutions on Ratemyprofessors.com. These comments were treated as a corpus which covered more than 1,200 comments with over 70,000words. The data analyses involved two stages. First, using the KeyBNC software, keyword analysis was performed to identify keywords which suggests the students’ areas of concern regarding their English language education. Second, through the USAS tagging system, Wmatrix was implemented to indicate the areas of concern through semantic domains. The findings in both analyses clearly indicated that the students’ concerns involved a wide range of areas, with an emphasis placed on grading and course evaluation issues. Overall, this study argued that, despite some comments that appeared superficial, it is important for professors to critically and judiciously consider all aspects of the evaluations as they can be valuable for improving teaching practices.