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Information Technologies for Teaching Children with ASD

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Advances in Computer Science for Engineering and Education II (ICCSEEA 2019)

Abstract

At the education of children with autistic spectrum disorder, special attention should be paid to the correction and maintenance of certain skills. In a variety of assistive technologies and application for students with autism, there is a problem of choice of the relevant product that will fully satisfy users’ needs. Such IT product should have appropriate educational characteristics, as well as take into account users’ needs and strengths. A recommender system to support such decision making is one of the approaches to deal with the problem. The modeling of such a system is the first stage of its design.

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References

  1. Sailers, E., Coopin, M., Marden, J.: iPhone, iPad and iPod touch Apps for (Special) Education. https://emedea.it/centro-ausili/images/pdf/24470331-iPhone-iPad-and-iPod-touch-Apps-for-Special-Education.pdf

  2. Aresti-Bartolome, N., Garcia-Zapirain, B.: Technologies as support tools for persons with autistic spectrum disorder: a systematic review. Int. J. Environ. Res. Public Health 11(8), 7767–7802 (2014). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143832/

    Article  Google Scholar 

  3. EdTech. https://edtechmagazine.com/k12/article/2016/08/3-ways-technology-can-help-students-autism

  4. HUFFPOST. https://www.huffingtonpost.com/2015/04/20/teaching-technologyautism_n_6865030.html

  5. FutureLearn. https://www.futurelearn.com/courses/supporting-autism

  6. AutismSpeaks. from https://www.autismspeaks.org/

  7. Kindy Segovia’s AT Tidbits. https://dart.ed.ac.uk/app-wheel-update/

  8. The University of Edinburgh. www.kindysegovia.com/318-2/

  9. AssistiveWare. from https://www.assistiveware.com/products/proloquo2go

  10. ClaroSoftware. from https://www.claro-apps.com/

  11. Aacorn. https://www.aacornapp.com/

  12. He, Z., Peng, L., Han, H., Xu, M., Wang, G., Bao, X., Yu, H., Hou, Z., Wang, H., Zhu, L., Zhang, Z.: Design and implementation of augmented reality cloud platform system for 3DEntity objects. In: 8th International Congress of Information and Communication Technology (ICICT-2018). Procedia Comput. Sci. 131, 108–115 (2018)

    Google Scholar 

  13. Bhatt, S.K., De Leon, N.I., Al-Jumaily, A.: Augmented reality game therapy for children with autism spectrum disorder. Int. J. Smart Sensing Intell. Syst. 7(2) (2014). https://augmentedrealitynews.org/games/augmented-reality-helps-children-with-autism/

  14. University of Cambridge. https://www.enterprise.cam.ac.uk/news/the-land-of-make-believe/

  15. Autism Spectrum Australia. https://www.autismspectrum.org.au/school/aspect-hunter-school

  16. Sphero. https://www.sphero.com/

  17. Didehbani, N., Allen, T., Kandalaft, M., Krawczyk, D., Chapman, S.: Virtual reality social cognition training for children with high functioning autism. Comput. Hum. Behav. 62, 703–711 (2016)

    Article  Google Scholar 

  18. Aina, O.: Application of holographic technology in education. Bachelor’s thesis of Degree Programme in Business Information Technology. Tornio University of Applied Sciences, 67 p. (2010)

    Google Scholar 

  19. HoloStudy. http://www.holo.study/

  20. AutismApps. https://www.autismapps.org.au/making-it-work/

  21. Dattolo, A., Luccio, F.L.: A review of websites and mobile applications for people with autism spectrum disorders: towards shared guidelines. In: Gaggi, O., Manzoni, P., Palazzi, C., Bujari, A., Marquez-Barja, J. (eds.) Smart Objects and Technologies for Social Good, GOODTECHS 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 195. Springer, Cham (2017)

    Google Scholar 

  22. Pasichnyk, V., Shestakevych, T., Kunanets, N., Andrunyk, V.: Analysis of completeness, diversity and ergonomics of information online resources of diagnostic and correction facilities in Ukraine. In: Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume I: Main Conference, pp. 193–208 (2018)

    Google Scholar 

  23. ISO. https://www.iso.org/standard/58625.html

  24. Shestakevych, T., Pasichnyk, V., Kunanets, N., Medykovskyy, M., Antonyuk, N.: The content web-accessibility of information and technology support in a complex system of educational and social inclusion. In: 2018 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), Lviv, pp. XXVI–XXXI (2018)

    Google Scholar 

  25. Adam, N.L., Zulkafli, M.A., Soh, S.C., Kamal, N.A.M.: Preliminary study on educational recommender system. In: 2017 IEEE Conference on e-Learning, e-Management and e-Services (IC3e), pp. 97–101 (2017)

    Google Scholar 

  26. Rawat, B., Dwivedi, S.K.: An architecture for recommendation of courses in e-learning system. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 9(4), 39–47 (2017). https://doi.org/10.5815/ijitcs.2017.04.06

    Article  Google Scholar 

  27. Fetaji, B., Fetaji, M., Ebibi, M., Kera, S.: Analyses of impacting factors of ICT in education management: case study. Int. J. Modern Educ. Comput. Sci. (IJMECS) 10(2), 26–34 (2018). https://doi.org/10.5815/ijmecs.2018.02.03

    Article  Google Scholar 

  28. Ehimwenma, K.E., Crowther, P., Beer, M.: Formalizing logic based rules for skills classification and recommendation of learning materials. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 10(9), 1–12 (2018). https://doi.org/10.5815/ijitcs.2018.09.01

    Article  Google Scholar 

  29. Chyrun, L., Kis, I., Vysotska, V., Chyrun, L.: Content monitoring method for cut formation of person psychological state in social scoring. In: Proceedings of 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2018, vol. 2, pp. 106–112 (2018)

    Google Scholar 

  30. Vysotska, V., Lytvyn, V., Hrendus, M., Kubinska, S., Brodyak, O.: Method of textual information authorship analysis based on stylometry. In: Proceedings of 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2018, vol. 2, pp. 9–16 (2018)

    Google Scholar 

  31. Khan, A., Madden, J.: Active learning: a new assessment model that boost confidence and learning while reducing test anxiety. Int. J. Modern Educ. Comput. Sci. (IJMECS) 10(12), 1–9 (2018). https://doi.org/10.5815/ijmecs.2018.12.01

    Article  Google Scholar 

  32. Abduganiev, S.G.: Towards automated web accessibility evaluation: a comparative study. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 9(9), 18–44 (2017). https://doi.org/10.5815/ijitcs.2017.09.03

    Article  Google Scholar 

  33. Veretennikova, N., Lozytskyi, O., Kunanets, N., Pasichnyk, V.: Information and technological service for the accompaniment of the educational process of people with visual impairments. In: ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer (ICTERI 2018). Volume I: Main Conference, pp. 290–301 (2018)

    Google Scholar 

  34. Nosenko, Y., Matyukh, Z.: The implementation of multimedia technology in ukrainian inclusive pre-school education. In: ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer (ICTERI 2017), pp. 459–466 (2017)

    Google Scholar 

  35. Lytvyn, V., Vysotska, V., Dosyn, D., Lozynska, O., Oborska, O.: Methods of building intelligent decision support systems based on adaptive ontology. In: Proceedings of the 2018 IEEE 2nd International Conference on Data Stream Mining and Processing, DSMP 2018. pp. 145–150 (2018)

    Google Scholar 

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Correspondence to Tetiana Shestakevych .

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Andrunyk, V., Shestakevych, T., Pasichnyk, V., Kunanets, N. (2020). Information Technologies for Teaching Children with ASD. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education II. ICCSEEA 2019. Advances in Intelligent Systems and Computing, vol 938. Springer, Cham. https://doi.org/10.1007/978-3-030-16621-2_49

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