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A Periodic Table of Computing Education Learning Theories

Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, 2019
Computing education research is built on the use of suitable methods within appropriate theoretical frameworks to provide guidance and solutions for our discipline, in a way that is rigorous and repeatable. However, the scale of theory covered extends well beyond the CS discipline and includes educational theory, behavioural psychology, statistics ...
Claudia Szabo, Nickolas J. G. Falkner, Andrew Petersen 0001, Heather Bort, Cornelia Connolly, Kathryn I. Cunningham, Peter Donaldson, Arto Hellas, James Robinson, Judy Sheard   +9 more
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Learning Theories in Computer Science Education

2009 Sixth International Conference on Information Technology: New Generations, 2009
College instruction may be primarily concerned in most cases with the content of their academic lessons, and not very much with their instructional delivery. However, the effective application of learning theories in higher education has an impact on student performance.
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Elements of Computational Learning Theory

2019
PAC learning theory is the foundation of computational learning theory. VC-dimension, Rademacher complexity, and empirical risk-minimization principle are three concepts for deriving a generalization error bound for a trained machine. The fundamental theorem of learning theory relates PAC learnability, VC-dimension, and empirical risk-minimization ...
Ke-Lin Du, M. N. S. Swamy
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Computational Learning Theory

Lecture Notes in Computer Science, 2001
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A View of Computational Learning Theory

2007
The distribution-free or “pac” approach to machine learning is described. The motivations, basic definitions and some of the more important results in this theory are summarized.
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Learning Theory and Computer Environments

2005
This entry is a brief survey of the learning-theory field as it relates to educational technology, primarily focused on behavioral and constructivist educational theorists. According to some scholars, both have praised technology and perhaps exaggerated its promise (Berg, 2002; Duffy & Jonassen, 1994).
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Computational Learning Theory

ACM SIGACT News, 1995
Michael J. Kearns, Umesh V. Vazirani
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Confident Iterative Learning in Computational Learning Theory

2017
Let us assume that we have a class of sets. Now, if we have a machine that, fed information on one of these sets, tells us which set the information belonged to, then the machine underwent some sort of learning. This act of learning can happen in various forms.
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Humanlike computational learning theory. A computational semiotics perspective

AFRICON 2009, 2009
Focussing on the development of smart interfaces for smart environments one has to meet the challenge that these interfaces need a kind of intelligence which resembles human intelligence sufficiently. Part of this humanlike intelligence is the ability to learn from an environment those properties which are relevant for human persons and to be able to ...
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From Computational Learning Theory to Discovery Science

1999
Machine learning has been one of the important subjects of AI that is motivated by many real world applications. In theoretical computer science, researchers also have introduced mathematical frameworks for investigating machine learning, and in these frameworks, many interesting results have been obtained. Now we are proceeding to a new stage to study
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