Preview

Informatics and education

Advanced search

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

https://doi.org/10.32517/0234-0453-2018-33-10-21-30

Abstract

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

About the Authors

M. G. Koliada
Donetsk National University
Ukraine

Mykhailo G. Koliada, Doctor of Sciences (Education), Professor, Head of the Engineering and Computational Pedagogic Department

283100, Ukraine, Donetsk, ul. Shchorsa, 17



T. I. Bugayova
Donetsk National University
Ukraine

Tetyana I. Bugayova, Candidate of Sciences (Education), Docent, Associate Professor at Engineering and Computational Pedagogic Department

283100, Ukraine, Donetsk, ul. Shchorsa, 17



References

1. Lurie S. Ya. Demokrit: Teksty, Perevod, Issledovaniya [Democritus: Texts, Translation, Research]. Leningrad, Nauka,1970. 664 p. (In Russian.)

2. Disterveg А. Izbrannye pedagogicheskie sochineniya [Selected pedagogical works]. Moscow. Uchpedgiz, 1956. 378 p. (In Russian.)

3. Glushko I. V., Zueva T. M. Monitoring kachestva obrazovatel’noj deyatel’nosti v vuze: teoretiko-pravovoj i prakticheskij aspekty [Моnitoring the quality of educational activities in higher educational establishment: theoreticallylegal and practical aspects]. Perspektivy Nauki i Obrazovaniya — Perspectives of Science and Education, 2018, no. 4, p. 26–32. (In Russian.) Available at: https://pnojournal.files.wordpress.com/2018/08/pdf_180404.pdf

4. Koliada M. G. Komp’yutatsionnaya pedagogika [Computational pedagogic]. Donetsk, Noulidzh, 2013. 321 p. (In Russian.)

5. Koliada M. G., Bugayova T. I. Vychislitel’naya pedagogika [Computational pedagogic]. Rostov-on-Don, SFEDU, 2018. 270 p. (In Russian.)

6. Beecher K. Computational thinking. BCS, The Chartered Institute for IT, 2017. 306 p.

7. Oancea B., Dragoescu R., Ciucu S. Predicting students’ results in higher education using neural networks. International Conference on Applied Information and Communication Technologies, 2013, is. 6, p. 190–193. Available at: https://llufb.llu.lv/conference/AICT/2013/Oancea_AICT2013.pdf

8. Romero C., Ventura S., Pechenizkiy M., Baker R. S.j.d. Handbook of educational data mining. New York, CRC Press, 2011. 526 p.

9. Osman Y. Computational pedagogy: fostering a new method of teaching. 2016 Annual Conference on Engineering Education. https://www.researchgate.net/publica-tion/305114627_Computational_Pedagogy_Fostering_a_New_Method_of_Teaching?enrichId=rgreq-8133e1b0254c-8cff5a9387d9163 0baaa-XXX&enrichSource=Y292ZXJQYWdlOzMwNTExNDYyNztBUzozODI4 NTQ0NzYzODYzMTFAMTQ2ODI5MTAyODIxNQ%3D%3D&el=1_x_2&_esc=publicationCoverPdf

10. Yasar O., Veronesi P. Computational pedagogical content knowledge (CPACK): integrating modeling and simulation technology into STEM teacher education. Proc. SITE 2015 — Society for Information Technology & Teacher Education Int. Conf. Las Vegas, AACE, 2015, p. 3514–3521. Available at: https://www.learntechlib.org/primary/p/150489/

11. Yasar O., Maliekal J. Computational pedagogy: a modeling and simulation approach. Computing in Science & Engineering, 2014, vol. 16, no. 3, p. 78–88. DOI: 10.1109/MCSE.2014.60

12. Berry D. The computational turn: Thinking about the digital humanities. Culture Machine, 2011, vol. 12. Available at: http://sro.sussex.ac.uk/id/eprint/49813/

13. Patarakin E. D., Yarmakhov B. B. Vychislitel’naya pedagogika: myshlenie, uchastie i refleksiya [Computational pedagogy: thinking, participation and reflection]. Obrazovatel’nye tekhnologii i obshhestvo — Educational Technologies and Society, 2018, vol. 21, no. 4, p. 502–523. (In Russian.)

14. Baker R. S., Inventado P. S. Educational data mining and learning analytics. Learning Analytics, 2014, p. 61–75. DOI: 10.1007/978-1-4614-3305-7_4

15. Dutt A. A., Ismail M. A., Herawan T. A systematic review on educational data mining. IEEE Access, 2017, vol. 5, p. 15991–16005. DOI: 10.1109/ACCESS.2017.2654247

16. Huebner R. A. A survey of educational data-mining research. Research in Higher Education Journal, 2013, vol. 19. 13 p. Available at: https://www.aabri.com/manuscripts/121328.pdf

17. Romero C., Ventura S. Educational data mining: a review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2010, vol. 40, is. 6, p. 601–618. DOI: 10.1109/TSMCC.2010.2053532

18. Kitaj sozdast tekhnologiyu predskazaniya prestuplenij [China will create crime prediction technology]. (In Russian.) Available at: http://4teller.com/kitay-sozdast-tehnologiyu-predskazaniya-prestupleniy-0

19. Podlasy I. P. Diagnostika i ehkspertiza pedagogicheskikh proektov [Diagnostics and examination of pedagogical projects]. Kiev, Ukraina, 1998. 343 p. (In Russian.)

20. Student’s guide to microteaching. Ottawa, 1978. 72 p.

21. Zajonc R. B. Styles of explanation in social psychology. Special issue: Controversies in social explanation of psychological behavior. European Journal of Social Psychology. Albany, 1989, vol. 19, is. 2, p. 345–368.

22. Bronfenbrenner U. Two words of chіldhood: U.S. and U.S.S.R. New York, Russell Sage Foundation, 1970. 190 p.

23. Korneva L. V. Psikhologicheskie osnovy pedagogicheskoj praktiki [The psychological basis of teaching practice]. Moscow, Vlados, 2006. 157 p. (In Russian.)

24. Curtis R. C., Miller K. Believing another likes or dislikes you: behavior making the beliefs come true. Journal of Personality and Social Psychology, 1986, vol. 51, p. 284–290. DOI: 10.1037/0022-3514.51.2.284

25. Smith B. O., Meux M. O. A study of the logic of teaching. USOE Cooperative Research Project No 258. Urbana: University of Illinois, 1962.

26. Hel I. Kholodnaya vojna za iskusstvennyj intellekt: ugroza vsemu chelovechestvu? [The Cold War for artificial intelligence: A threat to humanity?]. (In Russian.) Available at: https://hi-news.ru/research-development/xolodnaya-vojna-za-iskusstvennyj-intellekt-ugroza-vsemu-chelovechestvu.html


Review

For citations:


Koliada M.G., Bugayova T.I. Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic. Informatics and education. 2019;(10):21-30. (In Russ.) https://doi.org/10.32517/0234-0453-2018-33-10-21-30

Views: 952


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0234-0453 (Print)
ISSN 2658-7769 (Online)