Generative Artificial Intelligence in Language Assessment | 15th Harvard-China Education Symposium

In this video, I will talk about Applying Generative Artificial Intelligence in Language Assessment. This video is a part of the 15th Harvard-China Education Symposium.
See the following paper for more information about eye tracking:
Hu, X.; Aryadoust, V. A Systematic Review of Eye-Tracking Technology in Second Language Research. Languages 2024, 9, 141. doi.org/10.3390/languages9040141
See the following paper for information about neuroimaging:
Aryadoust, V., Foo, S., & Ng, L. Y. (2022). What can gaze behaviors, neuroimaging data, and test scores tell us about test method effects and cognitive load in listening assessments? Language Testing, 39(1), 56-89. doi.org/10.1177/0265532221102...
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[@Claire_luo]

I think we already encounter much AI-generated text, which could soon become part of norms and be part of the constructs, but the thing is that the ability of AI to convey cultural depths needs further investigation.
Learners could be exposed to AI-generated text if potential biases brought by AI could be reduced. It’s critical that testers have the literacy to recognize and correct such biases (especially in their local tests) to avoid negative impacts on learners' understanding of diverse cultures, languages, and communities.

[@VahidAryadoust]

nicely said.

[@SahraSteps]

🙌🏼🩵