Multivariate statistical methods: a primer
Multivariate statistical methods: a primer
Mining LMS data to develop an "early warning system" for educators: A proof of concept
Computers & Education
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Data analytics has been employed in the business world to predict outcomes relating to processes such as sales and product trends for over a decade. More recently, data analytics have emerged as a tool for educational institutions to use in order to recruit, retain, and help students to graduate successfully. The pilot study we conducted, which uses data analytics to explore the relationships between the habits of non-traditional students in an online course, is expressed in student activity variables captured from the learning management system (LMS) activity logs and their learning outcomes as expressed in their final grade. The two primary goals of this pilot study conducted are; 1) identify which LMS variables have the highest rate of predicting student success, and 2) identify and propose a framework for larger scale "big data" analysis of real-time student LMS evaluation. The results of this pilot study show that there are positive correlations between student activity in an LMS system and their final grade. The primary variables identified as having the strongest correlation for success were assignment, grade views and rubrics. A proposed framework, which includes collecting and analyzing data from several courses, drawn from various disciplines to be used in further data analysis is discussed.