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Inge Molenaar

Radboud University

Assistant Professor
Behavioral Science Institute
The Netherlands

PhD, Educational Sciences, 2011, University of Amsterdam
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Research Focus

Inge Molenaars’ research focusses on:

  1. designing, developing, and investigating innovative learning technologies that use data, Learning Analytics and Artificial Intelligence,
  2. examining how learning technologies used at scale affect learning and teaching practices in schools.

Her main research focus is on advancing measurement and support for self-regulated learning. She has developed innovative measurement techniques and translates them into personalized support to help young learners develop self-regulated learning skills. She has also investigated the impact of learning technologies on teachers and learners in schools, resulting in reports for schools, award winning scientific publications and advice to national and international governmental bodies.

My plans for the fellowship period

During my fellowship, I will develop Hybrid Human-AI Regulation within existing learning technologies to advance learners’ Self-Regulated Learning (SRL) skills. Hybrid systems combining artificial and human intelligence hold great promise for training human skills. My work targets young learners (8-14) for whom self-regulated learning skills are critical in today’s society. Many of these learners learn with learning technologies every day in school to learn mathematics and languages. These technologies optimize learning based on learners’ performance data, but even the most sophisticated technologies fail to support self-regulated learning. In fact, most technologies take over control and monitoring from learners. My work aims to develop a learning technology that gradually transfers from AI-regulation to self-regulation. Learners will increasingly control their own learning while moving through different stages of hybrid regulation. This approach focusses on learner’s individual development and adapts to variability in learners’ SRL skills as detected by advanced AI techniques. This work is innovative in developing the first hybrid system to train human self-regulated learning skills with Artificial Intelligence.

How will my work change children’s and youth’s lives?

During my fellowship, I will change young learners lives by helping develop important self-regulated learning skills. This is important because:

  1. when learners regulate their own learning, they learn more and transfer what is learned to new contexts, the deep learning argument; and
  2. the ability to self-regulate is a key skill for successful lifelong learning, the future learning argument.

These skills are deemed essential for humans in the context of the upcoming AI era. Human intelligence will increasingly be augmented by artificial intelligence. Today’s young learners will be confronted with artificial intelligence solutions throughout their lives. Human agency and oversight are needed to take a leading role in these transitions and self-regulation skills are a critical human skill in these contexts.

For these reasons, there is strong consensus that technologies should not regulate learners, but learners should develop the self-regulated learning skills to regulate themselves.

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