Abstract-Unlike doctors, teachers are not able to carry out personality analysis and teaching diagnosis via using various tools and data. So how can we build the exact teaching environment, collect the data of study process, and perform the evidence-based teaching? To answer the question, computers are introduced to observe study activities, which will surely become an important trend just as in other fields. By designing the cognition process oriented novel study observation software system based on Computer-Human Interaction (CHI) to realize the online observation of study process, massive amount of information that can hardly be obtained by traditional education and psychology is able to be efficiently collected. According to dynamics, data of study process was analyzed to obtain the variables of cognitive dynamics such as study speed, acceleration, average speed, key points, learning kinetic energy and so on. All these parameters reflected the personalities of the learners, which will provide useful information for teaching, training and diagnosis.

The system point of view, the human-computer interaction (HCI)

Raising, analyzing and solving problems are the core competitiveness factors of innovative talent. However, to date the mechanism for problem cognition has not been elucidated and still needs to be studied. A problem space is the representation of the sum of cognitive conditions, cognitive objectives, cognitive rules, cognitive impairment, and cognitive situation, and is a high-dimensional manifold. The observation and dimensionality reduction of problem spaces are considered as problem areas. Human-computer coupled cognitive observation is a new method for studying the brain at the information level, and can also be used in the observation of problem spaces. In this paper the human-computer coupled cognitive environment is established and a problem situation is constructed. Additionally problem objects are marked, data for raising problems are collected to establish a set of problem objects, and a tree topology is selected as the structure of the low-dimensional problem space to reconstruct a problem space. It is felt that the observation, dimensionality reduction, visualization, and topologization of problem spaces provide foundations for evidence-based and dynamic studies on problem spaces, as well as providing support for teaching.

No abstract

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.