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Brain Function Assessment in Learning

Overview of attention for book
Cover of 'Brain Function Assessment in Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Affective Learning: Principles, Technologies, Practice
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    Chapter 2 Understanding How Learning Takes Place with Neuroscience and Applying the Results to Education
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    Chapter 3 Tracing and Enhancing Serendipitous Learning with ViewpointS
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    Chapter 4 Online Brain Training Programs for Healthy Older Individuals
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    Chapter 5 Evaluating Active Learning Methods for Bankruptcy Prediction
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    Chapter 6 A Prognosis of Junior High School Students’ Performance Based on Active Learning Methods
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    Chapter 7 The Effects of Working Memory Training on Cognitive Flexibility in Man
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    Chapter 8 Computers Cannot Learn the Way Humans Do – Partly, Because They Do not Sleep
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    Chapter 9 Modeling Animal Brains with Evolutive Cognitive Schemas
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    Chapter 10 Neural Knowledge Tracing
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    Chapter 11 Game Experience and Brain Based Assessment of Motivational Goal Orientations in Video Games
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    Chapter 12 Real-time Brain Assessment for Adaptive Virtual Reality Game : A Neurofeedback Approach
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    Chapter 13 Event-Related Brain Potentials from Pictures Relevant to Disaster Education
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    Chapter 14 Real-time Spindles Detection for Acoustic Neurofeedback
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    Chapter 15 Examining the Efficiency of Feedback Types in a Virtual Reality Educational Environment for Learning Search Algorithms
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    Chapter 16 Virtual Sophrologist: A Virtual Reality Neurofeedback Relaxation Training System
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    Chapter 17 Different Frequency-Dependent Properties Between Dorsal and Ventral Hippocampal Synapses
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    Chapter 18 Using Electroencephalograms to Interpret and Monitor the Emotions
Overall attention for this book and its chapters
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2 tweeters
1 Wikipedia page


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Brain Function Assessment in Learning
Published by
Springer International Publishing, September 2017
DOI 10.1007/978-3-319-67615-9
978-3-31-967614-2, 978-3-31-967615-9

Frasson, Claude, Kostopoulos, George

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 23%
Researcher 5 13%
Student > Ph. D. Student 4 10%
Student > Bachelor 4 10%
Student > Postgraduate 3 8%
Other 7 18%
Unknown 8 20%
Readers by discipline Count As %
Computer Science 7 18%
Engineering 6 15%
Psychology 4 10%
Neuroscience 4 10%
Unspecified 2 5%
Other 6 15%
Unknown 11 28%