Predicting Academic Performance Based on Students' Blog and Microblog Posts
نویسندگان
چکیده
This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal anal‐ ysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in the context of a project-based learning scenario run on our eMUSE platform. Data is collected from six student cohorts, from six consecutive installments of the Web Applica‐ tions Design course, comprising of 343 students. A significant model was obtained by relying on the textual complexity and longitudinal analysis indices, applied on the English contributions of 148 students that were actively involved in the undertaken projects.
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