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In Order to LearnHow the sequence of topics influences learning$
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Frank E. Ritter, Josef Nerb, Erno Lehtinen, and Timothy O'Shea

Print publication date: 2007

Print ISBN-13: 9780195178845

Published to Oxford Scholarship Online: April 2010

DOI: 10.1093/acprof:oso/9780195178845.001.0001

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The Necessity of Order in Machine Learning: Is Order in Order?

The Necessity of Order in Machine Learning: Is Order in Order?

(p.41) Chapter 3 The Necessity of Order in Machine Learning: Is Order in Order?
In Order to Learn

A. Cornuéjols

Oxford University Press

This chapter provides a detailed introduction to, and overview of, the theories from machine learning, and introduces some of the basic theoretical concepts and models from computational studies of learning from the machine learning area of computer science. It presents ideas and directions of research which can answer questions that arise from order effects, and shows that some of the results of how these models work may have significance for, and counterparts in, related disciplines that have an interest in learning and education. It also notes some interesting new approaches in machine learning, including the concepts of helpful teachers and active learners. The chapter concludes with a discussion of open research avenues, as well as questions designed to be used for class projects related to order-effects in machine learning.

Keywords:   machine learning, order effects, training, sequencing effects

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