Applying the principles of metadesign in the educational platform development

Modern requirements for educational technologies are flexibility and adaptability, with the consideration of the student’s individual characteristics, learning style and basic competencies. The most important resource is time, therefore, shortening the training time and obtaining the most useful and complementary professional competencies and knowledge is an urgent and important task. The article discusses the concept of metadesign as a means for building learning paths, and examines the design and platform application based on its principles. Implementing metadesign principles is demonstrated on the example of the educational trajectory while training software developers. Forming the learning paths within the trajectory using the created educational platform is considered. The functional requirements for the educational platform are stated. The principles of building an educational trajectory within the framework of the platform using modern educational trends and simulators are described.

Skills and fuzzy knowledge structures

In knowledge space theory (KST), knowledge structure is an effective feature to evaluate individuals’ knowledge and guide future learning. How to construct knowledge structures is one of the key research problems in KST. At present, the knowledge structure has been generalized to the polytomous knowledge structure. This article mainly focuses on the special polytomous knowledge structures delineated by Skills, which are called fuzzy knowledge structures. We consider how to construct fuzzy knowledge structures based on the relationship between items and skills, and how to find the learning paths for specific knowledge domains. First, we construct knowledge structures in four models, which are the conjunctive model of skill maps, the disjunctive and conjunctive models of fuzzy skill maps, and the competency model of fuzzy skill multimaps. Second, we assess individuals’ skills and find the learning paths for the specific knowledge domains in the first three models. Finding the learning paths for a specific knowledge domain can guide learning and improve the learning efficiency of individuals. Finally, we analyze some data sets to show that the algorithms proposed are effective and applicable. These works can be applied to adaptive learning systems, which bring great convenience for assessing individuals’ knowledge and guiding future learning.

Collaborative Approaches for Self-Organized Competence Development

The ongoing digital transformation is changing work processes and production environments. Particularly small and medium-sized enterprises (SMEs) in the European textile industry are confronted with numerous related challenges. Among these, demand-oriented development and efficient use of employee competences are becoming ever more important for success. New decentralized and situationally adaptable solutions that enable self-organized learning paths and informal competency development are becoming a necessity for the participants in production processes to acquire the essential competences. Approaches to support self-organized learning paths and dynamic, role- and actor-based models for collaborative knowledge generation already exist and have proven especially worthwhile in the SME environment of the textile industry and its innovation processes. This paper presents challenges of collaborative competence development and approaches to solve them on different levels of the organization. In addition, it explains specific implementations based on project examples from the textile industry and outlines needs for further research.