Concept of Automated Support to Problem: Modular Vocational Training

Concept of Automated Support to Problem: Modular Vocational Training

Andrey Igorevich Vlasov (Bauman Moscow State Technical University, Russia), Ludmila Vasilievna Juravleva (Bauman Moscow State Technical University, Russia) and Vadim Anatolievich Shakhnov (Bauman Moscow State Technical University, Russia)
Copyright: © 2019 |Pages: 14
DOI: 10.4018/978-1-5225-3395-5.ch010

Abstract

The chapter deals with the concept of training for technicians, able to adjust to ongoing changes in the manufacturing environment. It is proposed to apply the systematic approach with a targeted use of collected methods and acmeological planning in a learning process when extra time is found owing to interdisciplinary integration and increased self-learning. Such planning is done with crosscutting design and problem-modular training with cross-rated instruction materials and learning outcomes. Education information systems are recommended as tools (like those based on modular object-oriented dynamic learning environment according to shareable content object reference model standard) together with automated information systems for self-learning, business and role plays with methods to rate career guidance and multimedia aids as learning tools.
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Problem-Modular Engineering Training

Analysis of Processes and Methods of Transfer of Knowledge

Against the background of profound social change, the education system in Russia is in search of new ways to improve the learning process through fundamental and holistic student training. The learning process takes place during sessions in classrooms, laboratories, workshops, and extramural self-learning. Professors act as trainers, tutors, and supervisors students are active subjects within the learning process. Training facilities (or instruction materials) require different tools to present and visualize knowledge and information (Yudin, Kolesnikov, Vlasov, & Salmina, 2017). For the generalized scheme of encapsulated objects in training and education, see Figure 1).

Figure 1.

Relationship between types of training and education

In training competent experts at the college level, improvements to the training quality are possible with the applied new educational technologies, developed learning routes, process plants (public-private partnership), and experienced professionals from process plants involved in the learning process. Other ways include launching art workshops under joint supervision of college teaching staff and leading professionals from core enterprises and establishing the social learning environment close to the working environment. These environments developstudents’ abilities to work as a team, make independent decisions, and solve management problems in individual work.

Tools for learning methods and approaches include:

  • Project-based approach,

  • Problem-based learning,

  • Crosscutting design,

  • Problem-modular training,

  • Cognitive learning,

  • Competence-based approach,

  • Profession and activity-related approach,

  • Value and activity-related approach,

  • Process approach,

  • Developmental teaching,

  • Distance learning,

  • Integrative and innovative learning,

  • Person-centered learning,

  • Qualitative approach,

  • Context-sensitive approach, and

  • Elkonin-Davydov system.

Key Terms in this Chapter

EUROBOT: An international amateur robotics contest for teams of young people. This is organized through student projects or independent clubs.

LCMS: Learning content management system.

VLE: Virtual learning environments.

Data Mining: A computer process that uses artificial and machine learning methods to discover hidden information or relations in large amounts of data.

R&D: Research and development.

BMSTU: Bauman Moscow State Technical University.

Commercial Software: Developed software for commercial purposes and that a price a license.

RTE: SCORM run-time environment.

LMS: Learning management system.

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