Article originally published on E-Learn Magazine on Feb 02, 2018 – Click here for the Spanish version
Learning analytics turns raw data into valuable strategic information, offering insights to improve teaching, learning, and the environments in which they occur. We’ve gathered 10 reasons why learning analytics has the power to improve the educational experience.
1. Promote Reflection and Self-regulated Learning
Student-facing reports help learners increase their performance by providing them with information about their course activity and performance compared to others. Systems like this one can provide students with signals about how well they are doing in general, as well as information about specific areas they need to work on. By making learning analytics available to students, institutions can promote self-regulated learning. This practice not only improves student outcomes, but also fosters a mindset that may help learners increase their post–graduation success.1
2. Identify Students at Risk of Poor Performance
By using data to identify students who are likely to struggle in a course, proactive advising can help students in a timely manner. Learning analytics surfaces relevant information about student engagement and performance that is key for academic advisors and student success specialists.¹ This way, professionals can reach out and intervene at an earlier stage than would otherwise be possible and help learners persist in spite of challenges.2 For example, using predictive analytics tools like Blackboard Predict, faculty and advisors can start identifying at-risk students before the second week in the semester.⁸
3. Understand the Impact of Instructional Design Patterns on Student Performance
Learning analytics can help identify the most successful instructional design style by program and course. By correlating tool use by faculty and students with specific learning outcomes, institutions can identify and scale high-impact practices to assist specific program and curriculum goals. ¹⁰
4. Increase Reporting Efficiency
Colleges and universities must fulfill a wide variety of institutional reporting requirements. Many of these concerns’ educational quality and the impact of educational technology investments. By capturing data on learning activity and automating report creation, learning analytics technology can increase the accuracy and efficiency of institutional reporting in a way that frees analysts to think beyond mere reporting, and use the same data in support of other strategic initiatives on campus. For example, California Baptist University Online used Analytics for Learn to automate an attendance tracking process that was otherwise labor-intensive and prone to error.¹¹ Because of an increase in institutional efficiency, CBU Online is also able to start using that same information to identify at-risk students and intervene with targeted interventions to keep more students on track for graduation.
5. Optimize Assessments
Learning analytics allows instructors to identify assignments that are highly associated with a student’s final grade and those that tend to correlate with a sudden drop in performance and course withdrawals. Instructors can quickly identify the assessments that are working and those that might need revision.
6. Measure Tool Adoption and Impact
With access to data on learning environment activity, institutions can get a realistic picture of how the system is being used and increase its adoption where it is likely to make the biggest impact.¹² Institutions can also assess the use of third-party tools, which in some cases might only be used by a few faculty members and do not justify their high costs. This process is important to establish an educational technology investment value, and for instructional designers and faculty developers to look for evidence that supports assumptions about best practices. ²
7. Improve Faculty Development
With access to student engagement information, LMS usage and instructional design practices, learning analytics helps faculty developers provide evidence in support of high-impact instructional practices. Access to information about faculty behavior before and after professional development activities also helps institutions to evaluate the impact of their faculty development initiatives.¹³ Instructors are also able to identify and promote effective teaching practices, as they can immediately address gaps and challenges and adjust their courses accordingly.³ Data can also help identify areas in need of improvement by the instructor in order to facilitate enhanced instructor-student interactions in the educational environment. ⁹
8. Nudge Students to Improve Learning Behaviors
Learning analytics can be used to improve student success by providing students with relevant performance information and alerting them in advance whether they are at risk of not passing a course. When students can see how they are performing, it increases their sense of agency over their own learning and empowers them.8 Blackboard Learn Ultra has the ability to automate notifications embedded directly within the course. This way, students can receive more detailed information as well as a suggested action, allowing them to keep their performance on track and improve the areas in which they are having difficulties. ⁴
9. Understand the Impact of Assignments on Discussion Board Engagement
Learning analytics can help instructors understand individual learners’ discussion forum activity, as well as critical thinking and the originality of their contributions. They can also test the impact that specific discussion board assignments have on the amount and quality of student participation in the online environment. With insights gained from learning analytics tools like Blackboard Analytics for Learn and Blackboard Predict, instructors can create activities to keep students engaged.⁵
10. Identify and Eliminate Sources of Systematic Inequity
Access to longitudinal data about relative student outcomes across different sections of the same course can help institutions identify areas in which the course environment itself is creating barriers to success. For example, institutions often see significant grade variance between sources taught online and in person. At many institutions, faculty grading patterns differ widely between course sections. Pierce College⁶ and Indian River State College⁷ are examples of institutions that have benefited from access to this kind of data.
1 Blackboard. Nine things you can do with Blackboard Analytics for Learn [PDF].
2 Harfield, Timothy. From LMS Reporting to Learning Analytics: Exciting updates to Analytics for Learn. Retrieved November 17, 2017, from http://blog.blackboard.com/from-lms-reporting-to-learning-analytics-exciting-updates-to-analytics-for-learn.
3 Everhart, Deb. Learning Analytics: The Future is Now. Retrieved November 17, 2017, from https://edtechdigest.wordpress.com/2012/05/10/learning-analytics-the-future-is-now.
4 Whitmer, John. Do notifications get noticed? New study finds that embedded alerts to students promote action at high rates. Retrieved November 17, 2017, from http://blog.blackboard.com/new-study-notifications-promote-student-action.
5 Blackboard. X-Ray Learning Analytics. Retrieved November 17, 2017, from http://www.blackboard.com/resources/pdf/datasheet-xray-rev20170228_002_.pdf.
6 Osborn, Eliana. Dashboards for Success. Retrieved November 17, 2017, from https://www.insidehighered.com/digital-learning/article/2017/03/15/pierce-college-uses-data-dashboards-improve-graduation-rates.
7 Blackboard. Learn how Indian River State College grew their online enrollments by 35% in two years. Retrieved November 17, 2017, from http://pages.blackboard.com/campaign/analytics/indian-river-state-college-case-study.aspx.
8 Rattiner, Marlen. Walking the line of predictive analytics in higher education. Retrieved December, 2nd 2017, from http://blog.blackboard.com/walking-the-line-predictive-analytics-higher-education/.
9 John, A., Mansureh, K., Sandra, N., & Theresa, K. (n.d.). Learning Analytics Methods, Benefits, and Challenges in Higher Education: A Systematic Literature Review. Retrieved November 16, 2017, from http://files.eric.ed.gov/fulltext/EJ1105911.pdf
10 Harfield, Timothy. Analytics for Learn: Using data science to drive innovation in higher education. Retrieved December 4, 2017, from http://blog.blackboard.com/analytics-for-learn-data-science-innovation-higher-education/
11 Simpson, Rich. Using analytics to track non-attending students. Retrieved December4 2017, from http://blog.blackboard.com/using-analytics-to-track-non-attending-students/
12 Harfield, Timothy. Analytics From LMS Reporting to Learning Analytics: Exciting updates to Analytic. Retrieved December 4, 2017, from http://blog.blackboard.com/from-lms-reporting-to-learning-analytics-exciting-updates-to-analytics-for-learn/
13 Mead, M. (Director). (2017, June 13). Learning analytics and faculty development [Video file]. Retrieved December 4, 2017, from https://www.youtube.com/watch?v=BSJKVU6Ltys
Illustration: Triibu Studio