Learning Analytics, Educational Data Mining, Adaptive Learning

Educators at Summit Prep in Redwood, California use data to shape classroom instruction. From regular surveys, teachers are able to find out the best way to adapt lessons to meet students’ needs. The Summit approach views collecting data as important no matter how that information is gathered. Surveys can be as simple as a thumbs up/thumbs down or as tech-dependent as a Google form. While assessments are the differentiating factor at this school, the focus is on the results of these surveys to shape instruction.

As higher education institutions deploy learning analytics platforms to better optimize student learning, the question of what data are collected and in which contexts arises. To fully understand the total student experience, data about student interactions with rec and wellness centers, student support services, and certainly academic advising centers are being collected and analyzed as they're added to the traditional classroom attendance and engagement model.

Yet, when institutions look at potential factors that might impact academic success, libraries may be overlooked.

Blackboard is planning to introduce a new feature in its learning management system later this year to help instructors grade students’ participation in class discussions online. The feature, called the “discussion forum recommended grade,” will use computer algorithms to analyze students’ posts in class discussion forums.
John Whitmer, learning analytics and research director at Blackboard, said that instructors want to use discussion forums to judge students’ participation, but that doing so is time-consuming and difficult since the forums were designed for discussion rather than assessment. These discussion forums are often underused by students, said Whitmer, since there is often little incentive for students to engage

Key Takeaways

The current learning data ecosystem is a chaotic, increasingly complex jumble that is producing vast amounts of usage data that are poorly understood and poorly utilized.

To accelerate the move to the Next Generation Digital Learning Environment, we need widespread adoption of learning data standards across institutions.

Early proof-of-concept implementations by two universities illustrate the current maturity of learning data standards and how they address real-world problems.

To achieve standards adoption at a broader scale — and reap the considerable benefits NGDLE promises — key challenges must be understood and addressed.

The rise of analytics in higher education raises questions about the responsible use of student data. Here are some of the issues and how institutions are dealing with them.

Panorama is dedicated to collecting data on the whole child, as well as on the whole school, and has created a series of resources to collect data on social-emotional issues that are generally difficult to measure, such as levels of grit, growth mindset, and sense of belonging. Looking at these levels in addition to student scores and grades could help teachers better understand the needs of their students, whether individually or as a group. In addition, Panorama utilizes surveys to measure teacher engagement and family involvement, realizing that these factors are indispensable to school climate.

In today’s climate of prioritizing data-driven practices in education, it is usually teachers and administrators poring over student performance data; rarely is the focus ever on students using data to improve their learning. But recently, researchers conducted a study on two sixth grade science classes in the Midwest, hoping to answer the question of whether middle school students can think metacognitively about their learning and use data about their performance to seek appropriate supports in their learning.

It’s often asserted that some things can’t be measured. But how true is this? And if we can’t measure something, should we stop pretending we can teach or develop it?

Can creativity be measured? What about resilience? Can we measure problem solving? What about ethical reasoning?

We take for granted the measurement of variables such as length, weight and temperature, but it is worth remembering that these variables and their measurement were human inventions. Albert Einstein made this point in the Evolution of Physics when he observed that ‘physical concepts are the free creations of the human mind and are not, however it may seem, uniquely determined by the external world’.

Phil Long is Associate Vice Provost of Learning Sciences at the University of Texas at Austin.

Transcript:  http://er.educause.edu/multimedia/2017/7/video-microcredentials-and-the-evolution-of-badges-to-recognize-learning