A growing number of institutions, faculty, and administrators now see the value of better leveraging the enormous and continuously mounting collection of data from their learning management system (LMS). This data often sits unused on servers and databases, while it has the potential to advance a range of practical and theoretical needs for a variety of potential stakeholders.
Learning analytics, as well as related concepts such as academic analytics, educational data mining, etc., explores the relationship between learning system usage with a range of outcomes that can positively impact students, faculty, administrators, researchers, and learning system designers.
Benefits to Students
Analytics related to online education programs have the potential to provide students with more detailed information about their performance. For instance, learning analytics can help students see and reflect on their behavior in constructive ways to help them manage their progress toward their learning goals. Similar to a “Fitbit” or an “Apple Watch,” a student-directed analytics framework has the potential to help students monitor their behavioral patterns, track changes over time, and compare their progress toward learning goals against both absolute and normative standards based on peer data.
A student with access to strong learning analytics data should be able to ask and answer:
- What am I doing?
- How am I doing relative to my own expectations?
- How and I doing relative to faculty expectations?
- How am I doing relative to my peers?
Benefits to Instructors
By utilizing learning analytics data, faculty can better monitor students and understand how course resources are being used. Some of the more obvious questions instructors ask and may find answers to via analytics include:
- How are students doing in my class? Are any at risk?
- What resources are they using the most?
- Who is using the resources I’ve made available to help them?
These are common applications of simple analytics and tracking systems often embedded in LMS systems. Analytics may also help answer less obvious questions. Take this question for instance: how does variation in the use of course resources impact learning outcomes? This is more complicated. It requires not only that the tracking systems monitor student resource utilization, but that it be connected with learning outcomes data, such as grades. If variation in the use of certain learning resources are not associated with expected learning outcomes, perhaps we need to reconsider the use of such resources.
Analytics will allow instructors to reflect on their own performance and seek better evidence for guiding instructional improvement.
Benefits to Administrators
Learning analytics allows program directors, or other administrators, to more easily see how well their program is performing. In addition to the potential need to drill down into specific faculty, students, and course-level data, learning analytics can allow for meaningful comparisons across courses.
Learning analytics can help administrators answer questions such as:
- Which courses are students finding the most engaging?
- Where are “hot spots” that need attention where learning outcomes are weak or engagement is low?
- Are there student characteristics or engagement patterns that are associated with program retention?
Some of these are tricky, and like other questions raised, may require that different systems talk to each other to be able to answer important questions.
Benefits to Researchers
Learning analytics provides new approaches to answering fundamental questions about factors associated with learning outcomes, especially as analytic approaches are able to examine micro and macro patterns of student and instructor behavior and their relationships with desired learning outcomes.
Studies in online learning often make generalizations, not taking into consideration factors such as content, student populations, and disciplinary conventions. Large-scale learning analytic approaches have the potential to better investigate the influence of multiple variables on key learning outcomes, as well as complex interactions among those variables, to provide increasingly nuanced views of how online environments influence learning.
Benefits to Learning System Designers
As analytics advance, learning system designers will also benefit from this data. Analytics can inform developers on how individuals are interacting with their systems, how that interaction impacts a host of other outcomes, and how changes to the environment impact outcomes. Other industries routinely use data mining approaches and experimentation with their own systems to improve the user experience. Facebook, Google, Amazon, and others continually experiment with subtle and not so subtle changes to the functionality and design of their products and examine the impact of those changes on user behavior. Learning system designers have similar opportunities.
Overall, there is potential for learning management systems, such as Wiley’s IMS Caliper compliant Engage LMS analytics platform, to move analytic efforts forward in significant ways. These efforts will work to answer the questions we have outlined in this article, and ultimately build more engaging learning experiences for students and faculty.
Authored by Bart Collins
Clinical Professor; Director of Graduate Studies at Purdue University; Wiley Faculty Fellow