e-Learning Ecologies MOOC’s Updates
Essential Update #4 - Learning Analytics
Learning analytics are a common factor in the usage of any well equipped modern learning system. The analytics cover student progress through a course using factors such as lesson completion, quiz completion and scoring, typically to measure student performance. It can be differentiated from the similar method of educational data mining by the fact that rather than machine intelligence making conclusions based on the data, Learning Analytics present the data openly for human scrutiny and conclusions.
The basic analytics available today are primarily reactive, in that they report when a student finished a lesson or test, which is useful for knowing if a particular student has completed a course successfully, but it doesn’t give us much help in terms of understanding why a student was successful or unsuccessful in a particular learning path.
Only recently has learning analytics on some platforms expanded to reporting data such as at what point in a video did a student stop watching, or at what step in an assignment or quiz did the student give up. These are extremely important metrics in modern eLearning because they can show us if there is a specific problem within the activity itself that is affecting a majority of learners rather than just making assumptions as to the student’s dedication or needing to guess as to why the course in question seems to be not well tolerated.
Another often overlooked form of analytics is feedback from direct surveying in-app. This is differentiated from the typical surveying that is usually sent by email after a course is complete by being a simple popup within the course itself that catches a student mid-activity with a simple question about how they are finding the activity itself. This method can be invaluable as it captures a student’s thoughts as they are engaged in the activity in question, rather than long after they have moved on and are being asked to think back to a single point of engagement in the entirety of the course. There are a number of modern technology companies that specialize in this kind of proactive in-app engagement such as Pendo or UserIQ. Typically these are employed by businesses as a training tool for technical applications, however I would argue that the same approach to proactive engagement is a valuable tool in a pure educational environment that is seldom used.
Sources:
https://www.northeastern.edu/graduate/blog/learning-analytics/
https://rusc.uoc.edu/rusc/ca/index.php/rusc/article/view/v12n3-calvet-juan/2746.html
thank you
Thank you for this summary of learning analytics! I hadn't heard of in-app surveying (I think I've only experienced something similar when browsing or shopping on a website, when a pop-up appeared asking for to rate my experience), but being able to learn students' thoughts in the moment as they are working on something sounds valuable. One drawback I can see is students being stressed to be interrupted while working on something, particularly a quiz or anything timed; we'd have to let them know to expect it at the beginning of the semester; students, unlike staff members completing training modules, are being graded, and they are often concerned about their grades as it is. But if we could incorporate this in our classes in a way that isn't too disruptive, or perhaps allow students to opt out of it at any point, or retake a quiz if it threw them off, it would be really helpful. Thank you again for sharing this.
I see learning analytics as an fundamental component of learning instruments; Particularly presently that digitization has gotten to be a prerequisite.
Very interesting thoughts in trying to capture student thoughts through quizzes while studying or doing a course. Maybe the quiz submission could be graded to motivate the students to submit thoughts.
Thank you for sharing.