It is mid-semester, and you are excited as you have spent a lot of time creating content for your course and designing online activities to engage students. You are wondering whether and how students are ...
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It is mid-semester, and you are excited as you have spent a lot of time creating content for your course and designing online activities to engage students. You are wondering whether and how students are using these materials. Below, I highlight six types of readily available data that can give you a glimpse into students’ engagement with course material. These learning analytics can provide useful insights for both you and your students as well as help you support your students.
Course logins. The learning management system (LMS) records data regarding student logins, including how often each student has accessed the course site and the duration of each visit, when they login, where they spend their time, what resources and tools are accessed the most and least, and whether some students don’t log in at all.
An examination of this data can quickly reveal students’ study habits and patterns for accessing course resources. For example, if students are accessing the course site only on certain days, then you may want to align assignment and reading due dates with peak access dates. If you notice that students are accessing only a few resources, then you can make little-used ones more prominent in the instructions. Login analytics can identify students who might be at risk of failing, and you can email these students to ask whether they are struggling with the course. All these actions can improve student success.
Viewing video lectures and other instructional resources. Analytics from video lectures and other instructional materials can help you determine whether and when students have accessed a resource. All video platforms provide detailed analytics regarding usage. The data tells you whether or not students viewed a video, how much time they spent watching the video, and how much they engaged with interactive activities embedded within the video. If students are spending a lot of time on topic, it may indicate that it is difficult to understand. Conversely, if students are not spending time on certain topics, then they may be just skimming the information. If the data include viewing time for individual students, you can see whether students who view the videos do better on assessments. If not, you might want to rethink the assessments or learning material.
Data from library sources—e-books, articles, and other resources. Library materials are an important component of instructional materials, and faculty put in considerable effort to select these materials for their courses. In addition to the LMS usage data, faculty can get data regarding the usage of library materials from their library staff. If the data suggests that students are not using the resources, then faculty can communicate to students the importance of these materials and also make sure that students are not having any difficulty finding or accessing these resources.
Performance data. Your LMS gives you access to student performance data, such as scores on quizzes, exams, and other assignments. Examining this data for performance patterns can lead to insights about whether students are struggling collectively with certain topics. If they are, then you may want to rethink how you presented or sequenced materials. You might add to the explanations, examples, or tutorials related to that concept.
You can also provide “just in time” teaching to explain the concepts students struggle with. If many students miss a certain quiz question, you might make a short video explaining the concept in a different way to students. If the engagement patterns suggest that students are viewing the instructional videos and materials only right before the exams and not regularly, consider making recommendations to students on how to study effectively and add more low-stakes assessments to ensure that students engage with the materials regularly.
These analytics can also illuminate the behaviors of students who are succeeding in the course. Presenting the practices of students who do well in the course as models of effective learning can motivate other students to do the same.
Engagement and participation in discussion forums. Discussion forums play an important role in student learning. You can compare the number of posts for different questions to determine whether some engage students more than others. You can not only modify the questions that do not do well but also identify particular types of questions that do better than others and use that information to modify all the questions. If there is low engagement overall, consider examining how the discussions are integrated with the overall grading system and if the expectations for participation have been communicated clearly to students.
Students’ views of their grades. Research suggests that students who track their progress tend to be more successful than those who don’t (Ambrose et al., 2010). Making grades available in the grade book along with comments on assignments and encouraging students to track their progress can enhance student learning. Examining the data on students’ views of their grades thus tells you who is monitoring their progress. You can then reach out to students who are not monitoring their progress and recommend monitoring as a learning behavior.
Using these simple analytics can give you insights into
students’ learning behaviors and help you understand where students might be
struggling. That way you can provide them with timely support.
Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: 7 research-based principles for smart teaching. Jossey-Bass.
Poonam Kumar, EdD, is the director of the Center for
Academic Innovation and Online Learning at Saginaw Valley State University in