Topology Analysis of Learning Cognitive Flow for Human-Computer Interaction

Shi, Guimin; Yang, Songfan; Liu, Changyong; Luo, Zhiming; Shimin, Meng; Li, Shaozi

doi:10.1109/itme.2018.00156

2018 9th International Conference on Information Technology in Medicine and Education (ITME) 2018

DOI: 10.1109/itme.2018.00156

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Topology Analysis of Learning Cognitive Flow for Human-Computer Interaction

Guimin Shi

Songfan Yang

Changyong Liu

et al.

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Cited by 2 publications

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An HCI-Based Cognitive Architecture for Learning Process Observation

Shi¹,

Yang²,

Chang-yong³

et al. 2020

International Journal of Distance Education Technologies

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In this article, a cognitive framework for observing learning activities based on human-computer coupling is proposed. The observation is based on the vectorization of a learning situation along with human-computer interaction factors. An evolutionary high-dimensional topology of learning cognitive flow is introduced for human-computer interaction. In addition, the authors have selected a tree topology as the topological structure of a low-dimensional learning space to process the observations for online learning. Furthermore, the mechanism for the BSM (brain cognitive body-situation of coupling-manifold of information) the coupling morphism is presented. The principle for the coupled observation of objects in a cognitive or learning manifold is proposed. Finally, a special system for teaching and learning is programmed to observe and evaluate learning and mental arithmetic training processes. This system not only provides students with a new ergonomic learning model but also records the students' learning processes. Thus, the teachers can summarize the knowledge points automatically rather than manually.

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An HCI-Based Cognitive Architecture for Learning Process Observation

Shi¹,

Yang²,

Chang-yong³

et al. 2020

International Journal of Distance Education Technologies

Self Cite

View full text Add to dashboard Cite

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Insights on Implications of Cognitive Computing in Leveraging Online Education Systems

Prasad

Aluvalu

Maheswari³

et al. 2022

International Journal of Online Pedagogy and Course Design

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Cognitive computing offers a good range of technological platforms that enhance the performance of online learning systems and is meant for assisting both instructors as well as students in leveraging the delivery of enriched content. In comparison to conventional e-learning systems, the inclusion of cognitive computing can escalate the performance efficiency of online learning. As a result, natural language processing and machine learning have generated a lot of interest in the research community. At present, it is an ongoing exploration towards finding the best possible means to use cognitive computing. The manuscript proposes a tentative plan for the next level of implementation using contextual analysis in order to improve the interaction between the computational model and user, as well as a proposition of using the network for analyzing massive educational data. This manuscript offers insights into the strength of using cognitive computing in an educational system and offers a future plan to and integrate it for an optimal learning experience by each learner/student.

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Topology Analysis of Learning Cognitive Flow for Human-Computer Interaction

Cited by 2 publications

References 4 publications

An HCI-Based Cognitive Architecture for Learning Process Observation

An HCI-Based Cognitive Architecture for Learning Process Observation

Insights on Implications of Cognitive Computing in Leveraging Online Education Systems

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