- Lea's Blog
Jan Synek
09/20/16

The Quantified Learner


Abacus 1680-1117 by Paul Schadler, on Flickr 

From an article by Annie Murphy Paul
https://www.amplify.com/viewpoints/quantified-learner

One of the great boons of educational technology is the quantity and quality of data it generates—data that teachers and administrators are now using to track performance and personalize instruction. But too often there’s one group that doesn’t get to engage with this rich body of knowledge: students themselves. This is a missed opportunity, since research shows that feedback can be a powerful way to build knowledge and skills, increase motivation, and develop metacognitive habits of mind. Here are four principles for helping learners use their own data, drawn from psychology and cognitive science.

1. Offer Information About What Learners Are Doing Right
Research on the powers of feedback by Hattie, Timperley, and others has found that feedback is most effective when it provides information on what the learner is doing correctly, and on what he or she is doing differently (and more successfully) than in previous attempts.

2. Take Care in Your Presentation of Data
The eminent psychologist Edward Deci has identified several conditions under which feedback may actually reduce learners’ motivation. When students sense that their performance is being closely monitored, they may disengage from learning. To counter this impression, the purpose of data collection should be fully explained and students’ consent obtained. Better yet, learners should be involved in collecting and analyzing their own data.

A second risk identified by Deci is that learners will interpret feedback as an attempt to control them—for example, when feedback is phrased as, “This is how you should do it.” Empower learners rather than controlling them by giving them access to their own data and teaching them how to use it.

According to Deci, a third feedback condition that can reduce learners’ engagement is an uncomfortable sense of competition. To avoid this, emphasize that you are sharing results with students not to pit them against each other, but rather to allow them to compete against their own personal bests.

3. Orient Feedback Around Goals
Feedback is most effective, research has found, when it directly addresses the learner’s advancement toward a goal, and not other, less relevant aspects of performance. Once a goal has been clearly specified, data can help students see the progress they’re making toward that target. Find ways to help students represent this progress visually, in a chart or graph that they update regularly.

4. Use Data To Build Metacognitive Skills
The most profound and lasting effect of sharing students’ data with them is to develop their awareness of their own learning. Having access to information about their performance creates opportunities for students to recognize when they’ve made mistakes and figure out what to do to fix them. It also helps them to monitor their own motivation and engagement, and take proactive steps when they feel these flagging. They can learn when to work harder, when to try a different approach, and when to seek help from others. Ideally, as lifelong learners, students will be providing their own self-feedback.

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Lea's Learning Analytics Blog

Learning analytics, educational data mining, formative assessment - all recent buzz words in educational research. In principle, the idea is to find theoretical frameworks, models, procedures, and smart tools to collect, aggregate, analyze, reason on and visualize large scale educational data. LEA’s BOX is a research and development project funded by the European Commission. The project aims at (a) making educational assessment and appraisal more goal-oriented, proactive, and beneficial for students, and (b) at enabling formative support of teachers and other educational stakeholders on a solid basis of a wide range of information about learners. That means, LEA’s BOX is a learning analytics toolbox that is intended to enable educators to perform competence-centered, multi-source learning analytics. More info at http://www.leas-box.eu!

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