Abstract
English Language Learners (ELLs) are a substantial portion of the students who enroll in MOOCs. In order to fulfill the promise of MOOCs – i.e., making higher education accessible to everyone with an internet connection – appropriate interventions should be offered to students who struggle with the language of course content. Through the analysis of clickstream log data gathered from two MOOC courses deployed on Coursera, Introduction to Psychology and Statistical Thermodynamics, we show that compared to native English speakers, ELL students have distinct behavioral patterns in how they engage with MOOC content including increased interaction with content that contains text, increased seeking away from content without visual support, and decreased video play rates. These patterns are expressed differently in response to different types of course content and domains. Our findings not only suggest more fine-grained methods for automatically identifying students who need language interventions, but also have further implications for the design of language support interventions and MOOC videos.
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More From: International Journal of Artificial Intelligence in Education
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