Collective intelligence and web tools in the educational process

The priority direction of modern education around the world is to ensure its high quality, based on the fundamental nature of knowledge and the development of students’ creative competencies. Simultaneously, the factors determining new requirements for the assessment and measurement of the quality of education are becoming more obvious and relevant. The setting of such tasks today is aggravated by the processes of globalization, which require collective intelligence, the consolidation of knowledge and world experience, considered as one of the effective ways of developing national educational systems. In this regard, a master’s program for measuring and evaluating the quality of education in a network form was implemented with the participation of the Moscow City University and Abai Kazakh National Pedagogical University. It is worthy of highlighting that Kazakhstan needs specialists in the field of education quality assessment and pedagogical measurements. The Institute of System Projects at Moscow City University. has enough experience and is also known to be an expert in this industry. Therefore, an agreement on the exchange of this experience was signed bilaterally. Thus, the master’s program has changed the educational process of the main pedagogical university of the country. New aspects of cooperation between the two major universities have been opened.

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REINFORCEMENT OF TEACHER-STUDENT-KNOWLEDGE RELATIONSHIPS THROUGH THE USE OF LOW-COST WEB TOOLS AND THE USE OF SOCIAL NETWORKS AS A SUPPORT FOR COLLECTIVE INTELLIGENCE

ICERI2018 Proceedings ◽

10.21125/iceri.2018.1413 ◽

2018 ◽

Author(s):

Miguel Ángel Muñoz-García ◽

Adolfo Moya ◽

Guillermo Moreda ◽

Fernando Ruiz Mazarrón ◽

Lourdes Lleó ◽

...

Keyword(s):

Social Networks ◽

Collective Intelligence ◽

Low Cost ◽

Student Knowledge ◽

Teacher Student ◽

Web Tools

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Collective Intelligence Algorithms in Pedagogical Practice

Journal of Siberian Federal University Humanities & Social Sciences ◽

10.17516/1997-1370-0724 ◽

2021 ◽

pp. 327-340

Author(s):

Mykhailo G. Koliada ◽

Tatyana I. Bugayova

Keyword(s):

Collective Intelligence ◽

Educational Process ◽

Ant Algorithm ◽

Training Methods ◽

Pedagogical Practice ◽

High Productivity ◽

Intelligence System ◽

The One ◽

A Minor ◽

Efficiency And Productivity

The article considers the ideas of using artificial intelligence algorithms in pedagogics. It presents the methodology of the so-called collective pedagogical megasystem. The introduction of such an ephemeral construct is necessary only to understand the collective pedagogical intelligence system, formulate it in a model, find out its operation patterns and the laws it obeys. It would contribute to predicting pedagogical processes and phenomena and formulating new laws. The objective of the article is to demonstrate the application of collective intelligence algorithms in pedagogical practice for effective didactic decision-making. The matter is that in a real educational process, besides the well-known set of pedagogical conditions, there are some random and unpredictable reasons and factors that are hard to foresee or anticipate. Due to their stochastic nature, they occur spontaneously. These single reasons make a minor impact on the teaching methods selection, but in aggregate their influence gets so strong that they can upturn some prognostic conclusions. The problem also focuses on identifying the factors that would ensure the highest efficiency and productivity of studies among the known (expected) and random (unexpected) reasons. For these purposes, the most suitable algorithm for the selection training methods is the so-called ant algorithm which, on the one hand, considers the randomness of the influence parameters, and on the other, ensures steady and high productivity. A certain example was selected to demonstrate the process of applying the ant algorithm to reveal the best hierarchy of the pedagogical conditions (factors) that determines the optimum choice of the training method. The authors conclude that human intelligence is distributed and integrated at the same time, and the application of collective intelligence algorithms in pedagogical practice can yield some effective didactic decisions

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