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Hur, Paul; Lee, HaeJin; Bhat, Suma; Bosch, Nigel – International Educational Data Mining Society, 2022
Machine learning is a powerful method for predicting the outcomes of interactions with educational software, such as the grade a student is likely to receive. However, a predicted outcome alone provides little insight regarding how a student's experience should be personalized based on that outcome. In this paper, we explore a generalizable…
Descriptors: Artificial Intelligence, Individualized Instruction, College Mathematics, Statistics
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Henricks, Genevieve; Bhat, Suma; Perry, Michelle – Grantee Submission, 2020
Students' language in discussion forums in online courses can influence their participation and course outcomes. We examined aspects of gendered language to gain insight into men's and women's participation and success in two online science courses. Results revealed that women and men did not differ in their language use along traditionally…
Descriptors: STEM Education, Online Courses, Electronic Learning, Language Usage
Bhat, Suma; Chinprutthiwong, Phakpoom; Perry, Michelle – International Educational Data Mining Society, 2015
Instructional content designers of online learning platforms are concerned about optimal video design guidelines that ensure course effectiveness, while keeping video production time and costs at reasonable levels. In order to address the concern, we use clickstream data from one Coursera course to analyze the engagement, motivational and…
Descriptors: Video Technology, Electronic Learning, Learner Engagement, Student Motivation