Learning Dynamics Analysis Based on Computer-Human Interaction

Yang, Songfan; Guo, Lei; Yu, Wang; Changyong, Liu; Shimin, Meng

doi:10.3991/ijet.v8i5.3028

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…If an incorrect answer is submitted, all questions keep on falling; otherwise, the corresponding question disappears on the screen. The remaining time and training score are displayed at the top right corner of the screen [11].…”

Section: Analysis Of Bsm-based Cognitive Mechanicsmentioning

confidence: 99%

A Study of Cognitive Orbits based on Man-Machine Interactions

Cheng¹,

Changyong²,

Shimin³

2015

TOCSJ

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Representation-Computation is one of the topics consistently focused by researchers in the field of cognitive science. The representation of cognitive structures in the advanced cognition is an important part of research. How to observe and empirically validate the cognitive structures is meaningful. Based on man-machine interaction environments, a novel "Brain cognitive body-coupling Situations-information Manifolds (BSM)" cognition observation platform has been created, which allows users to observe and analyze cognitive processes and structures, selecting tree-based networks and other networks to represent low-dimensional cognitive topological manifolds, and to restructure the cognitive structures and processes. Based on cognitive manifolds and cognitive dynamics, a cognitive process can be abstracted as a dynamical orbit in a low-dimensional cognitive manifold. The behaviors of the cognitive orbit are observed, related data are collected and the process is restructured in a low-dimensional cognitive manifold. The cognition is also analyzed by introducing mathematical methods, such as calculus and topology.

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Section: Analysis Of Bsm-based Cognitive Mechanicsmentioning

confidence: 99%

A Study of Cognitive Orbits based on Man-Machine Interactions

Cheng¹,

Changyong²,

Shimin³

2015

TOCSJ

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show abstract

“…The human-machine interaction environment allows us to collect more accurate cognitive information and create the digital environment which can be modulated [7,8]. It can also provide accurate laboratories for studying the cognitive dynamics [9,10].…”

Section: Introductionmentioning

confidence: 99%

Visual Analysis of Cognitive Structure based on the Human-Machine Interaction

Cheng¹,

Changyong²,

Shimin³

2015

TOCSJ

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Learning is a process that changes the cognitive structure, which is the important representation of advanced cognition. Due to the difficulties in observing cognition, the empirical and visual researches of cognitive structure are significant. To realize the empirical research, the first issue is how to observe the cognitive structures. Based on the humanmachine interaction, we have established a new "Brain cognitive body-cognitive coupling Situations-information Manifolds" (BSM) cognition observation platform. This platform allows the users to observe the cognitive processes and structures, collect and restructure the cognitive activity information. Additionally, the cognitive structure imaging, the empirical and visual analysis and the dimension reduction for high-dimensional cognitive manifolds can be realized on this BSM platform. Here, we have selected the tree-based network to represent the low-dimensional cognitive manifolds to develop a visual and vectorial model of layered cognitive structure. The digital model of cognitive structure is able to provide the basis for studying the empirical research, mathematics and dynamics of the cognitive structure, and the new ways for the advanced cognitive research.

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“…It is reasonable for us to believe that computers can replace humans to complete most of the investigations into the problem spaces. It is a trend for problem space and cognitive science studies to develop related software systems [3,4] so as to enable computers to become observation equipment for problems spaces and collect the activities of students' cognitive psychological world. Following the idea of the research paradigm of empirical science, how to reconstruct the collected data for problem spaces?…”

Section: Introductionmentioning

confidence: 99%

Vector Analysis of Problem Spaces Based on Human-Machine Interaction

Changyong¹,

Cheng²,

Shimin³

2015

TOAUTOCJ

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As a problem, space is the implicit world of cognition, it is difficult to observe and collect its data. From the new perspective of cognitive philosophy, human-machine cognitive coupling is the coupled state of the intelligent agent and the information system. The extension of a problem space inside the brain makes observation possible. The data for a problem space constitutes a set and forms a tree topology according to the level of cognitive abstraction. On the basis of mathematical paradigms, the metric specifications of problems are built on problem topology. Vector analysis is carried out on the problem space. The size, direction, hierarchy, and vector addition and subtraction of objects of a problem space are defined. On the basis of topological dynamic theory, the topological dynamic orbit of a problem space is defined. The topological reconstruction and vector analysis of problem spaces provides new methods for the refined detection of the structure of problem spaces.

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Learning Dynamics Analysis Based on Computer-Human Interaction

Cited by 5 publications

References 4 publications

A Study of Cognitive Orbits based on Man-Machine Interactions

A Study of Cognitive Orbits based on Man-Machine Interactions

Visual Analysis of Cognitive Structure based on the Human-Machine Interaction

Vector Analysis of Problem Spaces Based on Human-Machine Interaction

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