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Visualization of the content of information technologies: supporting the education of students with autism

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Języki publikacji
EN
Abstrakty
EN
Psychologists, teachers of inclusive education (for example, a teacher's assistant), parents, and IT specialists are involved in the process of teaching students with autism. Modern information technologies of education support can help paraprofessionals to perform their functions. Virtualization of educational content, namely avatars in the mode of augmented (virtual) reality, will allow taking into account the personal learning opportunities and needs of students with autism. The semantic differential method should be used to understand how the proposed virtual assistant satisfies the individual characteristics of such a student.
Twórcy
  • Lviv Polytechnic National University, Lviv, Ukraine
Bibliografia
  • 1. Gheta A., et.al. 2018. Modern ICT technologies to support inclusive education, Poltava (in Ukrainian).
  • 2. Shestakevytch T. 2017. The method of education format ascertaining in program system of inclusive education support, Proceedings of the 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2017, 1, art. no. 8098786, pp. 279-283.
  • 3. Andrunyk V., Shestakevych T., Pasichnyk V. 2018. The technology of augmented and virtual reality in teaching children with ASD. Econtechmod: scientific journal, Lublin. Vol. 7, No 4, pp. 59-64.
  • 4. Vasyliuk V., Shyika Y., Shestakevych T. 2020. Information system of psycholinguistic text analysis (2020) CEUR Workshop Proceedings, 2604, pp. 178-188.
  • 5. Andrunyk V., Pasichnyk V., Kunanets N., Shestakevych T. 2019. Multimedia educational technologies for teaching students with autism. 2019. CEUR Workshop Proceedings. Vol. 2533: Proceedings of the 1st International workshop on digital content & smart multimedia (DCSMart 2019), Lviv, Ukraine, December 23–25, 2019. Vol., pp. 237–248.
  • 6. Andrunyk V., Shestakevych T., Pasichnyk V., Kunanets N. 2018. Information technologies for teaching student with autism, Lviv Polytechnic National University bulletin, , Lviv, vol. 901, pp. 76–88.
  • 7. Syahputra M. F., Arisandi D., Lumbanbatu A. F., Kemit L. F., Nababan E. B., Sheta O. 2018. Augmented reality social story for autism spectrum disorder. 2nd International Conference on Computing and Applied Informatics. 2017 IOP Publishing IOP Conf. Series: Journal of Physics: Conf. Series 978, 012040 doi :10.1088/1742-6596/978/1/0120
  • 8. Jorge Brandão, Pedro Cunha, José Vasconcelos, Vítor Carvalho and Filomena Soares. 2015. An Augmented Reality GameBook for Children with Autism Spectrum Disorders, ICELW 2015 June 10th-12th, New York, NY, USA
  • 9. Tellagami labs, URL: https://tellagami.com
  • 10. Persefoni Karamanoli, Avgoustos Tsinakov, Charalampos Karagiannidis. 2017. The Application of Augmented Reality for Intervention to People with Autism Spectrum Disorder / IOSR Journal of Mobile Computing & Application (IOSR-JMCA), e-ISSN: 2394-0042. Volume 4, Issue 2 (Mar.-Apr. 2017), pp. 42-51.
  • 11. Andrunyk V., Shestakevytch T., Pasichnyk V. 2018. The technology of augmented and virtual reality in teaching children with ASD, ECONTECHMOD 2018, Vol. 07, No. 4, pp. 59–64.
  • 12. Trofimov A., Miliutina K., Drobot O., Lyuta L., Otych D., Pustovyi S., Karamushka T. 2019. A study on psychological capital by a method of semantic differential, Humanities and Social Sciences Reviews, 7 (5), pp. 387-392.
  • 13. Jylhä H., Hamari J. 2019. An icon that everyone wants to click: How perceived aesthetic qualities predict app icon successfulness, International Journal of Human Computer Studies, 130, pp. 73-85.
  • 14. Andrunyk V., Yaloveha O. 2020. Information System for Monitoring the Emotional State of a Student with Special Needs Using AI, 2020 IEEE 15th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2020 - Proceedings, 1, art. no. 9321933, pp. 66-69.
  • 15. Andrunyk, V., Bekesh V., Chyrun L. 2014. Structural modeling of technical text synthesis and analysis, Lviv Polytechnic National University Bulletin, vol. 805, pp. 237–257.
  • 16. Farinazzo Martins, V., Amato, C.A.H., Eliseo, M.A., Silva, C., Herscovici, M.C., Oyelere, S.S., Silveira, I.F. 2019. Accessibility recommendations for creating digital learning material for elderly, Proceedings - 14th Latin American Conference on Learning Technologies, LACLO 2019, art. no. 8995129, pp. 81-86.
  • 17. Radianti J., Gjøsæter T., Chen W. 2019. Universal design of information sharing tools for disaster risk reduction, IFIP Advances in Information and Communication Technology, 516, pp. 81-95.
  • 18. Pasichnyk V., Shestakevych T., Kunanets N., Andrunyk V. 2018. Analysis of completeness, diversity and ergonomics of information online resources of diagnostic and correction facilities in Ukraine, CEUR Workshop Proceedings, pp. 193-208.
  • 19. Manheim R., Reech R. 2003. Polytology: Methods of analysis, Moscow.
  • 20. Balin V., Ghayda V., Gerbachevskyy V. 2003. Practicum on basic, experimental and applied psychology, StPetersburg, 2003 (in Russian).
  • 21. Eger L., Egerová D., Pisoňová M. 2018. Assessment of school image [Ocena šolske podobe], Center for Educational Policy Studies Journal, 8 (2), pp. 97-122.
  • 22. Kyshtymova I.M., Rozhkova N.A. 2019. Public standing of a teacher and its adjustment, European Journal of Contemporary Education, 8 (2), pp. 294-302.
  • 23. Freeman V. 2018. Speech intelligibility and personality Peer-ratings of young adults with cochlear implants, Journal of Deaf Studies and Deaf Education, 23 (1), pp. 41-49.
  • 24. Leavy S., Keane M.T., Pine E. 2019. Patterns in language: Text analysis of government reports on the Irish industrial school system with word embedding, Digital Scholarship in the Humanities, 34, pp. I110-I122.
  • 25. Tolston M.T., Riley M.A., Mancuso V., Finomore V., Funke G.J. 2019. Beyond frequency counts: Novel conceptual recurrence analysis metrics to index semantic coordination in team communications, Behavior Research Methods, 51 (1), pp. 342-360.
  • 26. Zavushchak I., Burov Y., Pasichnyk V. 2018. Context Modelling In Process of Developing Employment Solutions ECONTECHMOD, Vol. 07, No. 3, pp. 47–52.
  • 27. Rybchak Z., Basystiuk O. 2017. Analysis of methods and means of text mining ECONTECHMOD. Vol. 6, No. 2, pp. 73–78.
  • 28. Duduciuc Alina. 2015. Advertising Brands By Means Of Sounds Symbolism: The Influence Of Vowels On Perceived Brand Characteristics, Studies and Scientific Researches. Economics Edition, Vasile Alecsandri University of Bacau, Faculty of Economic Sciences, issue 21, pp. 112-119.
  • 29. Zavuschak I. 2017. The context analysis and the process of its formation ECONTECHMOD, Vol. 6, No. 2, pp. 67–72
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-adbf193a-8834-41d1-a84f-306bab50ec82
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