This chapter addresses how an attention-management system can provide personalized support for self-regulated learning and what the effects of this support are on learning. An attention-management system can provide personalized support by capturing and interpretating information from the student's environment. A framework is proposed that will interpret the information and provide dynamic scaffolding for the learner. The essential elements are diagnosing, calibrating and fading scaffolds to the context of the learner. An intervention model supports self-regulated learning processes. In two studies, we have found evidence that an attention-management system can effectively give form to dynamic scaffolding. Dynamic scaffolding has a small- to medium-sized effect on students' performance and a small effect on students' metacognitive knowledge acquisition.

Introduction

E-learning has incrementally changed education in recent decades. Many new tools and instruments have been introduced to support existing educational practices. Yet only on a small scale have we seen transformative processes in schools. The large changes which have taken place in other sectors have not yet been achieved in education. This can partially be explained by the fact that e-learning solutions are not yet flexible enough to cater for learners' individual needs and demands. We see personalization in many sectors today, but education still seems to hold on to the ‘one size fits all’ paradigm, even though we know that personalized education is more effective than standardized education (Bloom 1984).