Scientometrics helps learning?
The Institute of Educational Systems Science
The 3rd International Conference on Data-driven Knowledge Discovery (CDKD2021)
Presentation goals
- Share some progresses on merging scientometrics and teaching/learning
- concept networks from textbooks and papers
- usage frequency from papers
- algorithms for learning orders and tests
- Inspire your critical input
Outlines
- Motivation
- Network of Chinese characters and algorithms for teaching/learning
- Concepts network of physics and some prelimenary results
- Concepts Network of scientometrics
- The author-paper-concept network of scientometrics
- Call for collaborations
Motivation
- Research can be seen as evolution of concept network and we scientometricians, in principle, know a lot about it
- How this network and its evolution can help the development of science
- as a researcher
- as a research administrator/policy makers
- as a student/teacher
- To make scientometrics relevant to researchers, research administrators, students and teachers
Network of Chinese characters
An algorithm for learning order
- Matrix $a^{i}_{j}=1$, $i$ is used in $j$, from the network (knowledge base)
- Vector $W$ represents usage frequency
- Vector $\tilde{W}$ the learning order \begin{equation} \tilde{W}= \left(1-A\right)^{-1}W= W + AW+A^{2}W+A^{3}W + \cdots \end{equation}
- integrates usage frequency and structural role of each concept in the network
An algorithm for tests
- probability graph model, (not) knowing ($i$)$j$ means very likely also (not) knowing ($j$)$i$ when $a^{i}_{j}=1$
- combined with the above to form personalized learning orders
- more efficient than random sampling
Results on learning orders
Summary on network of Chinese characters
- A concept network
- A vector of usage frequency
- Algorithms for learning orders and tests
- Currently working on experimental tests
- Can this be extended to other fields and how?
Other fields
- English words
- Mathematics
- Physics
- Scientometrics
Concept network of Quantum Mechanics
Learning Quantum Mechanics
Concept network of scientometrics
Concept network of scientometrics
The 3-layer network for scientometrics
Nodes and connections
- The concept layer: concepts, logically connected
- The paper layer: papers, connected by citations
- The author layer: Authos, connected as mentor-mentee
- Intralayers: author-writes-paper, paper-works on (makes use of)-concept
What can this 3-layer network framework offer?
- As a unified scientometrical data descriptor
- As a platform for asking and answering scientometrical questions
- science map
- research activities
- evaluations
- teaching and learning
Call for collaborations
- The concept network of scientometrics by and for the research community
- Even the concept network of each discipline by scientometricians and for researchers in the discipline
- Making scientometrics to be a fundamental tool for researchers and students/teachers of each discipline
Question time
- Thank you for your attention
- Take-home: via the author-paper-concept network for scientometrics and the algrithms over the network, scientometrics can help researcher, research adminstrator, students and teachers
- Let’s make it happen all together