Special Issue "Humanized Computing and Reasoning in Teaching and Learning"

Submission Deadline: 01 March 2022
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Guest Editors
Prof. Xinguo Yu, Central China Normal University, China
Dr. Jun Shen, University of Wollongong, Australia
Dr. Yuan Sun, National Institute of informatics, Japan
Dr. Yalin Zheng, The University of Liverpool, United Kingdom 

Summary

Traditional digital education is indifferent and rigid as it mainly is the outcome of technology applying into education, which is far from the humanized digital education. Humanized computing and reasoning technology includes the methods and algorithms that can conduct computing and reasoning tasks as people do. Some studies have shown that humanized computing and reasoning technology, such as knowledge transform based problem solving, knowledge network based diagnosis, knowledge network based education evaluation can be applied to many scenarios of educational artificial intelligence and make the teaching and learning interaction more humanized and personalized. It is more and more evident that humanized computing and reasoning technology has great research potential and application value in the future digital education. For example, automatic problem solving can generate the humanoid solution and humanoid teaching video for exercise problems based knowledge extraction and knowledge inference; diagnosis system can report the learning outcome of an individual student in terms of knowledge points by mining learning data; AI teaching support system can provide smart teaching help to teachers based on modelling educational situations. Since the great potential of humanized computing and reasoning technology, many teams from many countries work on it. This special issue will also receive a good batch of submissions from TALE 2021: http://tale2021.org/index.html


Keywords
AI Education, Modelling Education, Educational Computing, Humanized Computing, Humanized Reasoning