Auxiliary profession teaching system based on machine visual sense technology

Abstract

The invention discloses an auxiliary profession teaching system based on the machine visual sense technology, comprising an auxiliary profession teaching system and an auxiliary profession teaching method wherein the auxiliary profession teaching system comprises an image acquiring hardware sub-system and a self-learning software sub-system and the auxiliary profession teaching method comprises the following steps: 1) the login of a learner; 2) the setting of a scale value; 3) the self-measurement; and 4) the result check. The system of the invention crosses over the limit between falsehood and reality in real training teaching, creates the time-space environment for favorable self-learning, integrates the digitalized evaluations with the actually practical operations and realizes the integration of the falsehood and reality, overcoming the technical barriers against self-learning, turning and customized learning. In addition, the score and the evaluation result can be fed back in real time. This greatly increases the precision and the timeliness of evaluation, and realizes the unification of learning and evaluating.

Description

technical field [0001] The invention relates to the field of teaching practice, in particular to an auxiliary system for autonomous learning and professional teaching based on machine vision technology. Background technique [0002] Machine vision technology involves many fields such as computer science, image processing, and pattern recognition. It is a technology that digitizes real things and real events. Machine vision technology has been widely used in the actual production of primary, secondary and tertiary industries. But in the field of teaching practice, it has not been widely used. This achievement uses this technology to carry out the research and exploration of machine vision technology-assisted professional teaching, and has achieved good teaching effects in terms of students' skill level and professional quality. [0003] With the industrial upgrading and the implementation of the idea of ​​"China's smart manufacturing", the requirements for work efficiency, ...

AI Technical Summary

Problems solved by technology

[0008] First, there are too few teachers and many students, it is difficult for teachers to effectively monitor and guide the students' training process, which leads to low training efficiency

[0009] Second, teachers are dominant, students are passive, and it is difficult for teachers to carry out personalized teaching, which forms a strong conflict with the individual characteristics of practical operations

[0010] Third, the training cycle is long and the evaluation method is single. Teachers often can only evaluate the results of the training, but cannot effectively monitor and evaluate the long training process, especially the quality of students.

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