Knowledge State Networks for Effective Skill Assessment in Atomic Learning

The goal of this paper is to introduce a new framework for fast and effective knowledge state assessments in the context of personalized, skill-based online learning. We use knowledge state networks - specific neural networks trained on assessment data of previous learners - to predict the full know...

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Veröffentlicht in:	arXiv.org 2021-05
Hauptverfasser:	Rasch, Julian, Middelbeck, David
Format:	Artikel
Sprache:	eng
Schlagworte:	Customization Distance learning Machine learning Neural networks Questions
Online-Zugang:	Volltext
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