Original article
DOI: 10.15293/1812-9463.2304.05
Olga A. Chikova
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Roman V. Kamenev
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Nadezhda P. Gaar
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Igor V. Sartakov
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Abstract. Domestic research in the field of theory and methodology of teaching artificial intelligence technologies to schoolchildren does not pay sufficient attention to project-based learning as an approach of productive didactics. The basis of the proposed model is the concept of scientific and methodological support for teaching staff in the process of interaction between a pedagogical university and basic schools, implemented through a specialized center that functions as an element of the Unified Federal System of Scientific and Methodological Support for teaching staff and management personnel. Based on a comparative analysis of foreign scientific and methodological literature, a didactic structural model of project-based learning is proposed, which includes seven components: (1) formulating expected learning outcomes, (2) understanding the concept of training materials, (3) developing skills, (4) developing a project topic, (5) submitting a project proposal, (6) completing project objectives, (7) submitting a project report.
Keywords: artificial intelligence technologies, productive didactics, project training, didactic model, productive competence.
For Citation: Chikova O. A., Kamenev R. V., Gaar N. P., Sartakov I. V. Didactic Model of Project-based teaching of Artificial Intelligence Technologies to Schoolchildren. Journal of Pedagogical Innovations, 2023, no. 4 (72), pp. 59–76. (In Russ.) DOI: https://doi.org/10.15293/1812-9463.2304.05
Funding. The study was carried out within the framework of the project “Improving the model of interaction between pedagogical universities and basic schools and organizing their methodological support (based on the center for scientific and methodological support of teaching staff)”, which is implemented with the financial support of the Ministry of Education of the Russian Federation within the framework of state task no. 073-03-2023-027 from 27.01.2023.
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Information about the Authors
Olga A. Chikova – Doctor of Physical and Mathematical Sciences, Professor of the Department of Information Systems and Digital Education, Novosibirsk State Pedagogical University, Novosibirsk, Russia, https://orcid.org/0000-0002-3347-9148, chik63@mail.ru
Roman V. Kamenev – Candidate of Pedagogical Sciences, Associate Professor of the Department of Information Systems and Digital Education, Novosibirsk State Pedagogical University, Novosibirsk, Russia, https://orcid.org/0000-0002-9367-3997, romank54.55@gmail.com
Nadezhda P. Gaar – Candidate of Technical Sciences, Head of the Laboratory “Technologies of Artificial Intelligenceˮ of the Technopark of Universal Pedagogical Competences, Novosibirsk State Pedagogical University, Novosibirsk, Russia, https://orcid.org/0000-0001-8517-658X, lianelas@mail.ru
Igor V. Sartakov – Candidate of Pedagogical Sciences, Associate Professor of the Department of Information Systems and Digital Education, Novosibirsk State Pedagogical University, Novosibirsk, Russia, https://orcid.org/0000-0002-1406-9442, nsk@bk.ru
Authorsʼ contribution: Authors have all made an equivalent contribution to preparing the article for publication.
The authors declare no conflict of interest.
Received: 03.09.2023; approved after peer review: 20.10.2023; accepted for publication: 02.11.2023.
