In the digital world we live in today, we all know the endless amount of data that is collected throughout the many interactions that occur in our daily lives. You can see the evidence of this type of data in a variety of ways, including Amazon’s recommendation feature that suggests what products you might find interesting based on your previous purchases and what similar customers also purchased, as well as the Netflix movie recommendations that are created based on your ratings of previous movies you’ve watched. You probably won’t be surprised to know that even one of the large, local companies (where I know I spend too much time and money) uses this technology as well. Wegmans uses the data from Shoppers Club Cards for a variety of purposes, including sending out coupons and making sure the right products are stocked based on store locations. In at least one case, Wegmans even contacted shoppers who purchased a certain brand of soup to let them know about a recall on the product. We all create these kind of data points every day without even noticing it. Companies have found a way to utilize this type of data for marketing, advertising and to create better products and services based on what they have learned about their customers. This strategy of data mining for business purposes has been going on for many years.
With the increased use of technology and web-based tools in education, students have also left data footprints as they travel through their educational activities online. This data often goes untouched by many educators; however, there is a growing trend to make better use of this data to increase student learning. Many educational technology companies are beginning to focus on better utilization of this data and enhanced reporting to allow educators to use the data in more effective ways.
When we hear “Khan Academy”, most people immediately think of a short video with a black background, annotated colorful text and someone talking through a complex math theory. This is a large part of what Khan Academy offers, but a key component of their overall design is the tracking of student progress through a series of these short videos and accompanying activities over time. This data is collected while the student watches videos and completes short practice questions and concept quizzes during and after each skill checkpoint. The data collected includes not only the answer to the quiz questions, but data on how many times a student has viewed a certain video, how long they spent on it, what time of day it was viewed and more. Check out this Khan Academy data reports page for a full list of the reports they offer to educators to track the progress of students.
Knewton is another company innovating new ways to utilize the vast amount of data created by students throughout their learning experiences online to create tailored and more personalized learning environments for each student. Check out the below video from Knewton’s website.
Many publishers, including Pearson, Houghton Mifflin and Wiley, partner with Knewton in order to apply their adaptive learning technology to the large amount of content that publishers have created over the years. The combination of resources, on one side focused on the analytics and the other on high quality content, create innovative, data driven tools that can quickly be used by students and instructors in a variety of course and content areas.
Now that we have discussed the type of data that is tracked and how it has been used in a few examples to create personal learning environments for students and valuable reports for instructors, you might be wondering, “How can I apply this idea to my own courses?”
First of all, both examples listed above, Khan Academy and Knewton, provide content that utilize this type of data collection and reporting to instructors in many disciplines. Check to see what might be available for you. Also, check with your publishers if there are other resources that might give you this type of information. If you are using other technologies in your courses, check to see what type of statistics the tool is tracking already on student usage and if the reports of this data might be useful to you.
If you use Blackboard in any way, even just to post a syllabus document, there is already data available at your fingertips. You can quickly see the last time a student has logged into your course, as well as if they clicked on the file that you uploaded for them to read before the next class. The amount of data available for you to view in reports increases with your use of the variety of Blackboard tools. For example, you can view how many times a user has clicked on a specific content area, as well as other tools like activity in discussion forums and groups. These reports provide the specifics on each student, as well as the common days and times that content is most used in your course overall. Combine this data with the results of a short quiz activity and you would be able to acquire similar data that is made available to users of Khan Academy resources.
Blackboard also provides tools for early warning messages based on predetermined rules. If a student meets a certain criteria identified by the instructor as “at risk” on a certain assignment or overall in the course, the instructor is notified and is prompted to send a notification to the student directly. Blackboard also provides adaptive release tools that allow instructors to control the release of certain course material based on the successful completion of previous items.
A variety of other commonly used tools at Fisher provide similar types of data and reporting features to instructors. Echo360, for example provides instructors with a easy to view report that includes data on how many times a video recording has been viewed by unique viewers and overall, as well as a heat map of the video indicating points that have been viewed most frequently by all students. These points may indicate areas of confusion where content was viewed multiple times. These statistics can be very handy if you are teaching with the flipped classroom model, which we discussed in a previous post, in order to know who is viewing each recording prior to class and to identify areas that might need further clarification in the next face-to-face class session with the larger group. Below shows an example of the Echo360 statistics.
The data provided by a variety of educational tools can be used by instructors to paint a more accurate picture of where students are spending time, where they may be struggling with content and students who may not be fully engaged with the course. The ability to access and utilize this data can help all instructors make more informed decisions in communications with individual students, as well as for course development and planning overall.