In my last post I provided a link to a video on AltSchool for a glimpse into the future of learning analytics in education.  This vision was spearheaded by a former Google executive and funded by Facebook and PayPal founders.  In spite of AltSchool's promise to revolutionize education they are actually closing schools as a result of dwindling class sizes.  Disgruntled parents have reported that the school's primary focus seemed to be creating educational software that could be licensed for sale. (Robinson, 2017)  While this could be a missed opportunity for learning analytics in education, it is a reminder that the motives of all parties must be considered when adopting technology--particularly technology that collects so much data.

This led me to an article titled, "Learning Analytics: Avoiding Failure" for reassurance that my chosen emerging technology would not go the way of Beta Max video tapes. Learning analytics experts from around the world meet at an annual Learning Analytics and Knowledge (LAK) conference.  "Overall, the message of learning analytics experts was clear.  In order not to fail it is necessary to have a clear vision of what you want to achieve with learning analytics...". (Clow, 2017)  Whether designing a lesson, a unit, or an entire course the first start is always identifying the learning objectives.  Maybe the reason AltSchool failed was because their objective was profit instead of learning.

The second takeaway from the LAK experts, that AltSchool may have missed, is that learning analytics should use data in a way that works for the teachers and students in a logical and meaningful way.

Check out this great video by George Siemens, a leader in learning analytics!

One of the exciting possibilities in learning analytics is biometric eye-tracking.  By measuring what people look at and how long they look at it can tell educators a lot, such as what keeps attention or what parts of texts a student struggles with. Research indicates that humor maintains attention. (Hooijdonk, 2016) While this may seem intuitive, imagine a lesson matched to a student's sense of humor to maximize engagement.

Although it may be a long while before schools have room for biometric eye-tracking in their budgets, there are current and practical solutions.  Response Clickers, for example, can be a great way to track student data and measure learning and deliver instruction based on the results.

Truth be told, this is blog about learning analytics.  Data and statistics are often considered dull but one only need look at the popularity of the many Fitbit-style products available to see otherwise.  These products are enabling individuals to collect unprecedented amounts of information and make data driven decisions about their health objectives.  Learning analytics will enable educators to collect unprecedented amounts of information on learners to make data driven decisions about learning objectives.  While it lacks the excitement of virtual reality, learning analytics has the potential to drastically minimize the labor-intensive, time-consuming channels of traditional feedback while maximizing student learning in the 21st century.

Learning Analytics Infographic

Feedback and assessment are powerful components of an overall instructional strategy and meaningful feedback requires prompt and balanced delivery. (Dick, 2009)  This can be extremely challenging to do considering the realities of teaching.  Learning analytics has the potential to reduce many of these roadblocks and enable teachers to deliver more personalized instruction.

One of my favorite learning analytics tools is www.vocabulary.com.  This program enables teachers to quickly and easily track traditional assessment data such as percentage of commonly missed words but more importantly the program is adaptive.  This means that the program adapts to the learner.  For example, if Student A answers the questions correctly, Student A will complete the activity relatively quickly because they're demonstrating mastery of the content.  If Student B answers the question incorrectly, the program will continue asking various questions until the student demonstrates.  This personalizes learning to the individual in a way that no individual teacher could ever do for an entire class simultaneously.  This also eliminates the frequent problem of less motivated students mindlessly clicking their way to the end.  A terrific technology that is here today.

The Future of Big Data and Analytics in K-12 Education

What technology do you use to gather data for instructional decision-making?