Open AccessUsing Learning Analytics to Assess Student Learning in Online Courses
Author(s) -
Florence Martin,
Abdou Ndoye
Publication year - 2016
Publication title -
journal of university teaching and learning practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.258
H-Index - 8
ISSN - 1449-9789
DOI - 10.53761/1.13.3.7
Subject(s) - learning analytics , computer science , analytics , instructional design , data science , online learning , student engagement , visualization , multimethodology , qualitative property , educational technology , data analysis , mathematics education , multimedia , psychology , artificial intelligence , data mining , machine learning
Learning analytics can be used to enhance student engagement and performance in online courses. Using learning analytics, instructors can collect and analyze data about students and improve the design and delivery of instruction to make it more meaningful for them. In this paper, the authors review different categories of online assessments and identify data sets that can be collected and analyzed for each of them. Two different data analytics and visualization tools were used: Tableau for quantitative data and Many Eyes for qualitative data. This paper has implications for instructors, instructional designers, administrators, and educational researchers who use online assessments.