Coded Clues: Unraveling Learning at High Resolution

Intelligent technologies have gained widespread traction, also in the field of our children’s learning. Andreas Bjerre-Nielsen and his team will examine the potential of Intelligent Tutoring Systems in improving student learning, measuring progress, and assessing potential learning inequities. 

The team will use digital learning platforms and systems for school children in Copenhagen Municipality and will focus on data from the "MatematikFessor" learning platform.

Workpackages

The project will consist of three work packages.

• WP1 focuses on measuring students' knowledge and ability using machine learning prediction methods and examining the models' fairness and bias. The other work package measure causal effects.
• WP2A investigates how children learn mathematics in- and outside of class and how exposure to teaching affects their progression
• WP2B focuses on measuring the long-term and individual effects of the tutoring systems.

This project will contribute to the development and ethical use of intelligent learning technology in education.

The objective of this instrument is to develop the qualifications and competencies of the best research talents, both nationally and internationally.

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