Abstract
The use of analytics in education provides researchers the opportunity to uncover student engagement habits by utilizing data generated through online platforms such as course learning management systems (LMS). Student engagement has been shown to vary based on student-instructor interaction. We examined LMS usage of first-year engineering students in a large research university in the United States to examine the following three research questions: 1) How do course grades vary based on the students' instructor and the overall number of LMS sessions per student, 2) How do course grades vary based on the students' instructor and the number of LMS sessions per student for different course tools, and 3) How does the timing and frequency of LMS tool usage relate to course grades and vary across instructors? We found a positive relationship between LMS usage and course grades; however, the relationship is dependent upon the instructor of the course, as well as for the specific type of tool used. We also found that the day of the week on which the LMS was used is a strong predictor of student course grades. The results empirically demonstrate that better engagement with a course leads to better outcomes and there are variations in how instructors use an LMS which ultimately influences student usage and performance. We also illustrate an opportunity for researchers and instructors to capture, analyze, and use LMS data to inform and improve teaching practices and policies.
Highlights
The emergence of learning analytics has created excitement about student assessment with respect to the information and new knowledge that can be garnered from the vast amount of student data that have been and continue to be collected [1]
LEARNING MANAGEMENT SYSTEMS In parallel with the increased usage of learning management systems (LMS) to facilitate instructional and learning processes, there has been an increase in published research that has examined how instructors and learners interact with LMS tools and the association of those interactions and learning outcomes
Analyzing learning management system data provided the opportunity to uncover new insights about how learners engaged with course material in a first-year engineering program, how students derived value from its use, and how students’ experiences may have varied across separate lecturers and workshop leaders (WSLs)
Summary
The emergence of learning analytics has created excitement about student assessment with respect to the information and new knowledge that can be garnered from the vast amount of student data that have been and continue to be collected [1]. Within more traditional educational environments, where face-to-face classes are still the norm, colleges and universities find themselves with a myriad of student data collected via learning management systems (LMS), which can be analyzed to uncover new insights about students’ learning processes. Almost 99 percent of postsecondary institutions have reported having an LMS in use and approximately half of faculty members at those institutions reporting using the systems on a regular basis [4]. While these systems have become more pervasive, they tend to be considered transactional warehouses rather than an opportunity to understand student learning and engagement with course materials. With the advent of LMS as a potential instructional resource, many researchers have sought to understand factors behind faculty
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