Correlations Of Student Grades And Behavior While Using A Course Management System Under Different Contexts

As the Internet is in widespread use by engineering faculty, the opportunity exists to collect measures of student learning behavior based on their use of the Internet learning tools. One such tool is a course management system (CMS). Data on student use of a CMS is readily available from login records and the web server log file. It has been shown that this data, paired with contextual information about the CMS, such as which files are related to course content or to assignments, can be used to generate measures of student behavior that significantly correlate with the students’ final grades in the course. These measures can add a typically unobtainable set of information about student behavior outside the classroom to the instructor’s overall efforts in evaluating a course. However, measures of student interaction with a CMS must be examined in context of how that CMS is used with the class. Patterns of student interaction may be very different if the CMS is used as a database of information or as an interactive learning tool. A previous study of two courses delivered by a CMS where one was used as a database of information and the other as an interactive learning tool in addition to a database showed that measures had different results and had different correlation patterns with student grades. To further examine patterns of student interaction with a CMS in relation to grades, data were collected for individual students on six measures of student behavior over the entire semester from seven courses delivered by a CMS. These measures are total time logged in to the CMS, average length of visits, total number of logins, total hits on any course content file, total hits on the main course page, and total hits on the course assignments page. The seven courses are categorized according to how the CMS is used in supporting their courses and what functions were employed. For each course, the six measures were paired with final grades for each student and examined in a correlation analysis. The patterns of correlations between courses are discussed in the paper along with implications for making general guidelines for interpreting measures of student behavior as measured through a CMS.