Grades 2.0: How Learning Analytics Are Changing The Teacher’s Role

Educators, have you ever wondered if your students are really learning when you teach? Soon you’ll have to wonder no more.

That’s because learning analytics are here. They’re an emerging area of research that will be able to tell you not only how engaged and how much your students learned – but also suggest ways you can improve your lessons.

Before we go deeper, let’s get the definition straight. According to Educause (PDF), learning analytics is “the use of data and models to predict student progress and performance, and the ability to act on that information”. It differs from other pedagogical theories because it focuses on the learner’s interaction with his or her learning environment.

Learning analytics involve four basic steps (a gross oversimplification, but feel free to click through if you’d like a more technical examination):

1. Collecting large amounts of data from a number of channels – including, but not limited to, online learning environments, social, mobile – and perhaps in the future, games. Couple this data with various learning theories and we can begin to form a more holistic picture of a student’s learning progress than just theories.

2. Translating that data into actionable insights. It may be impossible to track how much a student really absorbed from one lesson but the system CAN track his/her behaviour and use that as a signal. Here are a few examples of behavioural signals:

- Language of frustration in any media.
- Low time on site, relative to the class.
- Long lag between logins.
- Tracking areas of studies in which the student is weak in over years.
- Detecting the TYPE of mistakes that was made – careless or a fundamental lack of understanding?
- Theoretically, learning analytics would even be able to track whether or not a student is guessing in a multiple choice test.

3. Personalization and adaptation. Once the system gets the signal, it can then personalize each student’s learning environment. For example, if a student spends significantly less time attempting to solve a problem compared to other students, the system can display prompts and clues to keep him/her going – in real time.

This is crucial because when a student gets feedback is just as crucial to learning as what feedback the students get. This wasn’t possible in the past, where students have to wait at least a few days for their assignments to be marked.

4. Predicting the best course in the future. As students use the system for a prolonged period of time, educators will be able to track what works and what doesn’t – and adjust accordingly. In fact, it will soon be possible for each student to essentially be working with a custom-built and personalized curriculum that’s unique to them.

Learning analytics is a tool, and like any other tool, it will require a human to wield it. People will be the ones interpreting the data and that means lots of subjectivity. If a particular metric is down, what does that mean exactly?

Teachers, therefore, will no longer be “teachers” per se. But they will be more than just facilitators. They will be analysts, living in what Steve Jobs referred to as the intersection between art and technology.

Are you ready?

Peter Drucker, the man who is often credited for inventing management, once said that “you can’t manage what you don’t measure”. Seems that this is true in the classroom as well.

Andrianes Pinantoan is part of the team behind Open Colleges, a TAFE courses provider in Australia. When not working, he can found writing about psychology in his personal blog, Journey To Earth.