Ph.D. Student Jieun Kim wins 2023 MwALT Best Student Paper Award

Ph.D. Student Jieun Kim won the 2023 MwALT Best Student Paper Award!

The paper is titled “Test takers’ interaction with context videos in a video-based listening test: A conceptual replication and extension of Suvorov (2015)


The present study conceptually replicates and extends Suvorov’s (2015) investigation of visual information and viewing behavior, examining the relationship between foreign language listening anxiety (Elkhafaifi, 2005) and viewing behavior in context-providing videos. In Experiment 1, 49 participants completed the Foreign Language Listening Anxiety Scale (FLLAS) (from Zhang, 2013), watched three academic lectures from Suvorov (2015), while their eyes were tracked, and answered comprehension questions. In Experiment 2, 64 participants were additionally encouraged to take notes, and the order of the videos was counterbalanced. The relationship between viewing time and comprehension was small and non-significant in both experiments, except when considering note-taking. No listening anxiety effect was found in either experiment. Survey responses and interviews with 31 participants revealed variations in test takers’ attitudes toward the videos. The findings indicate that including context videos in listening tests to enhance authenticity does not enhance or compromise comprehension. Additionally, the individual difference factor, namely listening anxiety, did not significantly influence how much individuals look at the videos. The implications for the development of video-based listening tests, at-home testing, and research methodology are discussed.

MwALT is the Midwest Association of Language Testers, a regional language testing association. To learn more about the MwALT, visit their website at:

Fantastic work. Congratulations, Jieun!