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Scrutability, Control and Learner Models: Foundations for Learner-Centred Design in AIED Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Evaluating the Impact of Research-Based Updates to an Adaptive Learning System

Authors : Jeffrey Matayoshi, Eric Cosyn, Hasan Uzun

Published in: Artificial Intelligence in Education

Publisher: Springer International Publishing

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Abstract

ALEKS is an adaptive learning system covering subjects such as math, statistics, and chemistry. Several recent studies have looked in detail at various aspects of student knowledge retention and forgetting within the system. Based on these studies, various enhancements were recently made to the ALEKS system with the underlying goal of helping students learn more and advance further. In this work, we describe how the enhancements were informed by these previous research studies, as well as the process of turning the research findings into practical updates to the system. We conclude by analyzing the potential impact of these changes; in particular, after controlling for several variables, we estimate that students using the updated system learned 9% more on average.

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Metadata
Title
Evaluating the Impact of Research-Based Updates to an Adaptive Learning System
Authors
Jeffrey Matayoshi
Eric Cosyn
Hasan Uzun
Copyright Year
2021
Book
Artificial Intelligence in Education

Print ISBN: 978-3-030-78269-6

Electronic ISBN: 978-3-030-78270-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-78270-2_80

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