DeepEdu: Deep Learning and Education
Preface
1
Introduction
1.1
A Future
1.2
A Comparison
1.3
Knowledge Ecosystem
2
Primary Concerns
2.1
Passive Consumption and Untested Knowledge
2.2
Knowledge Ecosystem Example
2.3
The Problem of Knowledge Representation
3
Concepts
3.1
Knowledge Footprint
3.2
Knowledge Journeys
3.3
Collective Human Knowledge Graph
3.4
DeepEdu Network
3.5
Knowledge Ecosystem by Example
3.6
Problem Formulation
3.6.1
Before we start…
3.7
Learning + Feedback [DeepEdu]
3.7.1
Problem Formulation
3.7.2
The Approach
3.7.3
QG and QA Overview
3.7.4
Question Generation (QG)
3.7.5
Question Answering (QA)
3.7.6
Summary of Learning and Feedback Networks
3.7.7
Datasets and Annotation Suggested
3.8
Knowledge Graph
3.8.1
What is a graph?
3.8.2
What is a Knowledge Graph(KG)?
3.8.3
Problem Formulation
3.8.4
Automatic Knowledge Graph Construction
3.8.5
Case Studies
3.8.6
Summary
3.8.7
Datasets and Annotation Suggested
3.9
Knowledge Journeys
3.9.1
Problem Formulation
3.10
Knowledge Footprint
3.10.1
Possible Next Steps
4
Next Steps
4.1
Overview
4.2
Challenges
4.3
DeepEdu dataset
4.4
Education Partners
4.5
Educator Enrichment
4.6
Minimum Viable Dataset (Benchmark)
4.7
Call for collaborators
4.8
Conclusion
5
About the Authors
5.1
Haohan Wang
5.2
Fanli Zheng (Christian Ramsey)
5.3
Contact Us
6
References
Online Paper
Github
DeepEdu - Deep Learning and Education
DeepEdu - Deep Learning and Education
Fanli (Christian) Zheng
dyad x machina
thechristianramsey@gmail.com
Haohan Wang
dyad x machina
haohan723@gmail.com
[DRAFT] 2018-11-21
Preface
Knowledge Ecosystem
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