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Artificial intelligence in teaching programming to students of pedagogical university

Authors: I. A. Yashina;

Artificial intelligence in teaching programming to students of pedagogical university

Abstract

The purpose of the study. Modern education is undergoing significant changes. Artificial intelligence technologies are being introduced into the educational practice of universities, including pedagogical universities. These technologies have great opportunities. However, there is a need for a deeper study of the influence and role of artificial intelligence not only in the educational process of the university as a whole, but also in the specifics of teaching individual disciplines, including programming for future teachers of computer science The problem of using artificial intelligence in teaching students of pedagogical universities is urgent. The article is devoted to the substantiation of the role of artificial intelligence in the process of teaching programming to students, future teachers of computer science and the study of the possibility of its effective application in the real educational process.Materials and Methods. The analysis of scientific publications in the field of using artificial intelligence in the educational process of higher education institution and the analysis of scientific and methodological literature on teaching programming to students of pedagogical universities were performed. Artificial intelligence tools used in professional software development have been analyzed. The experiment of using the online development environment Replit with artificial intelligence technology in Python programming course for students of pedagogical university was carried out. A questionnaire survey of students at the beginning and after the completion of the course was carried out.The results of the study. Traditionally, the author's e-learning course developed in the Moodle environment, programming simulator with automated solution checking, IDLE Python and online compilers are used in teaching programming to 1st year students of Krasnoyarsk State Pedagogical University. These learning tools were supplemented with Replit online development environment with artificial intelligence technology. According to the results of the experiment it is shown that the use of online development environment Replit with artificial intelligence technology in teaching programming to students of pedagogical university helps in writing and debugging code, makes the course less complex, this is confirmed by the results of questionnaire survey of students, also showing that most students give their preference to this development environment. At the end of the students' mastering of the programming course there is a significant growth in self-assessment of the programming level, which is confirmed by the learning results.Conclusion. The role of artificial intelligence in the process of teaching students programming can be significant and useful both for the instructor and the students. In particular, the use of artificial intelligence helps the student in writing and debugging code, simplifies the process of explaining to the instructor the ways of algorithm development and program compilation. The example of the integrated online environment Replit, which has built-in artificial intelligence, shows its possibilities for effective teaching students programming.As a result, the article confirms the need for further research and development of methodological support for the successful integration of artificial intelligence in the process of teaching students of pedagogical universities in the field of programming

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Keywords

LC8-6691, programming teaching methodology, replit development environment, artificial intelligence in teaching programming, Special aspects of education, artificial intelligence in programming

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold