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Özel Eğitimde Yapay Zeka ve Yenilikçi Uygulamalar

Year 2023, , 176 - 199, 31.12.2023
https://doi.org/10.52911/itall.1297978

Abstract

Yapay zekâ, görevleri yerine getirmek için insan zekasını taklit eden ve topladıkları verilere göre kendini yinelemeli olarak geliştirebilen sistemler olarak tanımlanabilir. Yenilikçi teknolojiler arasında yer alan yapay zekâ uygulamaları, eğlence, tıp, siber güvenlik, ulaşım, turizm, e-ticaret, bankacılık ve finans gibi birçok farklı alanda olduğu gibi eğitim alanında da yaygın olarak kullanılmaktadır. Yapay zekâ uygulamalarındaki gelişmeler eğitimin diğer alanlarında olduğu gibi özel eğitim alanında da farklı yenilikleri beraberinde getirmiştir. Bu araştırma, çeşitli yapay zekâ uygulamalarının özel gereksinimli bireylerin gereksinimlerini ve isteklerini karşılamadaki rolünü değerlendirmeyi amaçlamaktadır. Mevcut araştırmada, özel eğitimde yapay zekâ uygulamalarına yönelik derinlemesine bir anlayış geliştirmek amacıyla anlatı incelemesi araştırma yöntemi tercih edilmiştir. Araştırma sonuçlarına göre, yapay zekâ uygulamalarının özel gereksinimli bireylerin ihtiyaçlarını ve isteklerini başarılı bir şekilde karşıladığı sonucuna ulaşılabilir. Bireylerin ihtiyaçlarına göre uyarlanan yapay zekâ, eksikliklerini tanımlamak ve gelişimlerini desteklemek için kişiselleştirilmiş yardımlar sunmaktadır. Ayrıca, yapay zekâ uygulamaları özel gereksinimli bireylerin ebeveynleri, öğretmenleri, psikologları ve çevrelerindeki diğer kişilerle daha rahat bir şekilde duygusal etkileşimde bulunmalarına yardımcı olmaktadır.

References

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  • Balling, L. W., Townend, O., Mølgaard, L. L., Jespersen, C. B., & Switalski, W. (2021). AI-driven insights from AI-driven data. Hearing Review, 28(01), 27-29.
  • Barua, P. D., Vicnesh, J., Gururajan, R., Oh, S. L., Palmer, E., Azizan, M. M., ... & Acharya, U. R. (2022). Artificial intelligence enabled personalised assistive tools to enhance education of children with neurodevelopmental disorders—a review. International Journal of Environmental Research and Public Health, 19(3), 1192.
  • Bhattacharjee, D., Kim, W., Chattopadhyay, A., Waser, R., Rana, V. (2018). Multi-valued and fuzzy logic realization using TaOx memristive devices. Scientific Reports, 8(1), 1-10.
  • Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24.
  • Costa, A. P., Charpiot, L., Lera, F. R., Ziafati, P., Nazarikhorram, A., van der Torre, L., & Steffgen, G. (2018). A comparison between a person and a robot in the attention, imitation, and repetitive and stereotypical behaviors of children with autism spectrum disorder. In Proceedings workshop on Social human-robot interaction of human-care service robots at HRI2018 (pp. 1-4).
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  • Elmas, Ç. (2003). Yapay sinir ağları. Seçkin Yayıncılık.
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  • Goggin, G. (2019). Cars and contemporary communication disability, connected cars, and communication. International Journal of Communication, 13, 27-39
  • Granquist, C., Sun, S. Y., Montezuma, S. R., Tran, T. M., Gage, R., & Legge, G. E. (2021). Evaluation and comparison of artificial ıntelligence vision aids: Orcam MyEye 1 and seeing AI. Journal of Visual Impairment & Blindness, 115(4), 277-285.
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  • Jain, K., Manghirmalani, P., Dongardive, J., & Abraham, S. (2009). Computational diagnosis of learning disability. International Journal of Recent Trends in Engineering, 2(3), 64-66.
  • Kambalimath, S., & Deka, P. C. (2020). A basic review of fuzzy logic applications in hydrology and water resources. Applied Water Science, 10(8), 1-14.
  • Katoch, S., Chauhan, S. S., & Kumar, V. (2021). A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80(5), 8091-8126.
  • Kaur, J., Khan, M. A., Iftikhar, M., Imran, M., & Haq, Q. E. U. (2021). Machine learning techniques for 5G and beyond. IEEE Access, 9, 23472-23488.
  • Kubat, M. (2017). An introduction to machine learning (2nd Edition). Springer International Publishing.
  • Kumar, V., Chhabra, J. K., & Kumar, D. (2014) Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems. J Comput Sci 5(2),144–155
  • Lambora, A., Gupta, K., & Chopra, K. (2019, February). Genetic algorithm-A literature review. In 2019 international conference on machine learning, big data, cloud and parallel computing (COMITCon) (pp. 380-384). IEEE.
  • Liddy, E. D. 2001. Natural Language Processing. In Encyclopedia of Library and Information Science, 2nd Ed. NY. Marcel Decker, Inc.
  • Mao, W. B., Lyu, J. Y., Vaishnani, D. K., Lyu, Y. M., Gong, W., Xue, X. L., ... & Ma, J. (2020). Application of artificial neural networks in detection and diagnosis of gastrointestinal and liver tumors. World Journal of Clinical Cases, 8(18), 3971.
  • Mao, Y., Yan, W., Song, Y., Zeng, Y., Chen, M., Cheng, L., & Liu, Q. (2020). Differentiate quality of experience scheduling for deep learning applications with docker containers in the cloud. arXiv preprint arXiv:2010.12728.
  • Mathew, T. V. (2012). Genetic algorithm. (30 March 2022) retrieved from http://datajobstest.com/data-science-repo/Genetic-Algorithm-Guide-[Tom-Mathew].pdf
  • Mbaabu, O. (2020). Intelligent agents in artificial intelligence. (25 March 2022) retrieved from https://www.section.io/engineering-education/intelligent-agents-in-ai/
  • McCormack, A., & Fortnum, H. (2013). Why do people fitted with hearing aids not wear them? International Journal of Audiology, 52(5), 360-368.
  • Mirjalili, S., Song Dong, J., Sadiq, A. S., & Faris, H. (2020). Genetic algorithm: Theory, literature review, and application in image reconstruction. In Nature-Inspired Optimizers (69-85) Springer:
  • Mulfari, D., Minnolo, A. L., & Puliafito, A. (2017, May). Building tensorflow applications in smart city scenarios. In 2017 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 1-5). IEEE.
  • Murero, M., Vita, S., Mennitto, A., & D'Ancona, G. (2020). Artificial intelligence for severe speech impairment: innovative approaches to AAC and communication. CEUR Workshop Proceedings 2730, pp. 1-6
  • Najafzade, A. (2020). AI for better integration of people with disabilities (Visual impairment) (Unpublished master’s thesis). Tallinn University of Technology.
  • Nielsen, J. B. B., Nielsen, J., & Larsen, J. (2014). Perception-based personalization of hearing aids using Gaussian processes and active learning. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 23(1), 162-173.
  • OrCam (2021). About OrCam. Retrieved from https://www.orcam.com/en/about/.
  • Özdemir, O., & Kalınkara, Y. (2020). Bulanık Mantık: 2000-2020 Yılları Arası Tez ve Makale Çalışmalarına Yönelik Bir İçerik Analizi. Acta Infologica, 4(2), 155-174.
  • Pavlopoulos, J., Vrettaros, J., Vouros, G., & Drigas, A. S. (2008, September). The Development of a Self-assessment System for the Learners Answers with the Use of GPNN. In World Summit on Knowledge Society (pp. 332-340). Springer, Berlin, Heidelberg.
  • Pirim, H. (2006). Yapay zeka. Journal of Yaşar University, 1(1), 81-93. Rego, N., (2017). Aipoly Vision Wins the Best of Innovation Award at CES2017. Cool Blind Tech. Retrieved from https://coolblindtech.com/aipoly-vision-wins-the-best-of-innovation-award-at-ces2017/.
  • Rende, F. Ş., Bütün, G., & Karahan, Ş. (2016). Derin Öğrenme Algoritmalarında Model Testleri: Derin Testler. 10. Ulusal yazılım Mühendisliği Sempozyumu,24-26 Ekim, pp:54-59, Çanakkale. Russell, S. J., & Norvig, P. (2020). Artificial intelligence: a modern approach (Fourth edition), Pearson Education.
  • Sadauskaite, J. (2017). Artificial intelligence tools to overcome autism disorders. Smart Week. Retrieved from https://www.smartweek.it/artificial-intelligence-tools-to-overcome-autism-disorders/.
  • Sağıroğlu, Ş., Erler, M., & Beşdok, E. (2003). Mühendislikte yapay zeka uygulamaları-I: yapay sinir ağları. Kayseri: Ufuk Kitap Kırtasiye-Yayıncılık.
  • Santoki, S., & Patvardhan, N. (2019). To research the advantages and limitations of AI based app in the Indian context for the visually challenged. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(6S4), 271-278.
  • Schipor, O. A., Pentiuc, S. G., & Schipor, M. D. (2010). Improving computer-based speech therapy using a fuzzy expert system. Computing and Informatics, 29(2), 303-318.
  • Sherbin, B. (2018). Israeli ai startup restores speech abilities to stroke victims, others with impaired language. Retrieved from: https://blogs.nvidia.com/blog/2018/11/28/voiceitt-ai-startup/.
  • Shrestha, A., & Mahmood, A. (2019). Review of deep learning algorithms and architectures. IEEE Access, 7, 53040-53065.
  • Singh, S., Kumar, P., Chaudharya, H., Khurana, R., & Shokeen, A. (2022) Augmented Reality and Virtual Reality Creating Ripple in Medical and Pharmaceutical World. In: Verma J.K., Paul S. (eds) Advances in Augmented Reality and Virtual Reality Studies in Computational Intelligence, vol 998. Springer, Singapore. https://doi.org/10.1007/978-981-16-7220-0_8
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Artificial Intelligence and Innovative Applications in Special Education

Year 2023, , 176 - 199, 31.12.2023
https://doi.org/10.52911/itall.1297978

Abstract

Artificial intelligence can be defined as systems that imitate human intelligence to fulfil tasks and can iteratively improve themselves according to the data they collect. Artificial intelligence applications, which are among innovative technologies, are widely used in the field of education as well as in many different fields such as entertainment, medicine, cyber security, transport, tourism, e-commerce, banking, and finance. Developments in artificial intelligence applications have brought different innovations in the field of special education as in other fields of education. This research aims to evaluate the role of various artificial intelligence applications in meeting the needs and wishes of individuals with special needs. In the current research, narrative inquiry research method was preferred to develop an in-depth understanding of artificial intelligence applications in special education. According to the results of the research, it can be concluded that artificial intelligence applications successfully meet the needs and wishes of individuals with special needs. Artificial intelligence adapted to the needs of individuals offers personalized assistance to identify their deficiencies and support their development. In addition, AI applications help individuals with special needs to interact emotionally with their parents, teachers, psychologists, and other people around them in a more comfortable way.

References

  • Aggarwal, C. C. (2018). Neural networks and deep learning. Springer.
  • Amazon (2021). What is artificial intelligence? Machine learning and deep learning. Retrieved from https://aws.amazon.com/machine-learning/what-is-ai/.
  • Ambroz, N. (2019). Natural Language Processing: A Short Introduction to Get You Started. Retrieved from https://aliz.ai/natural-language-processing-a-short-introduction-to-get-you-started/.
  • Bai Y, Zhuang H, Wang D (2006) Fundamentals of fuzzy logic control— fuzzy sets, fuzzy rules, and defuzzification. In: Advanced fuzzy logic technologies in industrial applications (pp. 17-36). Springer.
  • Balling, L.W., Townend O., Switalski W. (2019). Real-life hearing aid benefit with Widex EVOKE. Hearing Review, 26(3), 30-36.
  • Balling, L. W., Townend, O., Mølgaard, L. L., Jespersen, C. B., & Switalski, W. (2021). AI-driven insights from AI-driven data. Hearing Review, 28(01), 27-29.
  • Barua, P. D., Vicnesh, J., Gururajan, R., Oh, S. L., Palmer, E., Azizan, M. M., ... & Acharya, U. R. (2022). Artificial intelligence enabled personalised assistive tools to enhance education of children with neurodevelopmental disorders—a review. International Journal of Environmental Research and Public Health, 19(3), 1192.
  • Bhattacharjee, D., Kim, W., Chattopadhyay, A., Waser, R., Rana, V. (2018). Multi-valued and fuzzy logic realization using TaOx memristive devices. Scientific Reports, 8(1), 1-10.
  • Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24.
  • Costa, A. P., Charpiot, L., Lera, F. R., Ziafati, P., Nazarikhorram, A., van der Torre, L., & Steffgen, G. (2018). A comparison between a person and a robot in the attention, imitation, and repetitive and stereotypical behaviors of children with autism spectrum disorder. In Proceedings workshop on Social human-robot interaction of human-care service robots at HRI2018 (pp. 1-4).
  • Demiris, G., Oliver, D. P., & Washington, K. T. (2019). Defining and analyzing the problem. Behavioral intervention research in hospice and palliative care: Building an evidence base, 27-39.
  • Dickerson, J. A., & Kosko, B. (1997). Virtual worlds in fuzzy cognitive maps. In Kosko B (Editor). Fuzzy engineering, 173-189. Upper Saddle River, NJ: Prentice-Hall.
  • Drigas, A. S., & Ioannidou, R. E. (2012). Artificial intelligence in special education: A decade review. International Journal of Engineering Education, 28(6), 1366-1372.
  • Drigas, A. S., & Ioannidou, R. E. (2013). A review on artificial intelligence in special education. Information Systems, E-learning, and Knowledge Management Research: 4th World Summit on the Knowledge Society,
  • WSKS 2011, Mykonos, Greece, September 21-23, 2011. Revised Selected Papers 4, 385-391.
  • Eğrisöğüt Tiryaki, A., & Kazan, R. (2007). Bulaşık makinesinin bulanık mantık ile modellenmesi. Mühendis ve Makine, 48(565), 3-8.
  • Elmas, Ç. (2003). Yapay sinir ağları. Seçkin Yayıncılık.
  • Ertel, W. (2018). Introduction to artificial intelligence. Springer.
  • Ferrari, R. (2015). Writing narrative style literature reviews. Medical Writing, 24(4), 230-235.
  • Geeks for Geeks (2021). Agents in artificial intelligence. (14 November 2021) retrieved from https://www.geeksforgeeks.org/agents-artificial-intelligence/
  • Georgopoulos, V. C., Malandraki, G. A., & Stylios, C. D. (2003). A fuzzy cognitive map approach to differential diagnosis of specific language impairment. Artificial intelligence in Medicine, 29(3), 261-278.
  • Goggin, G. (2019). Cars and contemporary communication disability, connected cars, and communication. International Journal of Communication, 13, 27-39
  • Granquist, C., Sun, S. Y., Montezuma, S. R., Tran, T. M., Gage, R., & Legge, G. E. (2021). Evaluation and comparison of artificial ıntelligence vision aids: Orcam MyEye 1 and seeing AI. Journal of Visual Impairment & Blindness, 115(4), 277-285.
  • Green BN, Johnson CD, Adams A. (2006) Writing narrative literature reviews for peer-reviewed journals: secrets of the trade. J Chiropratic Medicine 5, 101–117.
  • Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., & Lew, M. S. (2016). Deep learning for visual understanding: A review. Neurocomputing, 187, 27-48.
  • Gupta, I., & Nagpal, G. (2020). Artificial intelligence and expert systems. Stylus Publishing, LLC.
  • Haber, N., Voss, C., Daniels, J., Washington, P., Fazel, A., Kline, A., ... & Wall, D. P. (2020). A wearable social interaction aid for children with autism. arXiv preprint arXiv:2004.14281.
  • Islam, S. N. (2013, November). ShellAg: Expert system shell for agricultural crops. In 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (pp. 83-86). IEEE.
  • Jain, K., Manghirmalani, P., Dongardive, J., & Abraham, S. (2009). Computational diagnosis of learning disability. International Journal of Recent Trends in Engineering, 2(3), 64-66.
  • Kambalimath, S., & Deka, P. C. (2020). A basic review of fuzzy logic applications in hydrology and water resources. Applied Water Science, 10(8), 1-14.
  • Katoch, S., Chauhan, S. S., & Kumar, V. (2021). A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80(5), 8091-8126.
  • Kaur, J., Khan, M. A., Iftikhar, M., Imran, M., & Haq, Q. E. U. (2021). Machine learning techniques for 5G and beyond. IEEE Access, 9, 23472-23488.
  • Kubat, M. (2017). An introduction to machine learning (2nd Edition). Springer International Publishing.
  • Kumar, V., Chhabra, J. K., & Kumar, D. (2014) Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems. J Comput Sci 5(2),144–155
  • Lambora, A., Gupta, K., & Chopra, K. (2019, February). Genetic algorithm-A literature review. In 2019 international conference on machine learning, big data, cloud and parallel computing (COMITCon) (pp. 380-384). IEEE.
  • Liddy, E. D. 2001. Natural Language Processing. In Encyclopedia of Library and Information Science, 2nd Ed. NY. Marcel Decker, Inc.
  • Mao, W. B., Lyu, J. Y., Vaishnani, D. K., Lyu, Y. M., Gong, W., Xue, X. L., ... & Ma, J. (2020). Application of artificial neural networks in detection and diagnosis of gastrointestinal and liver tumors. World Journal of Clinical Cases, 8(18), 3971.
  • Mao, Y., Yan, W., Song, Y., Zeng, Y., Chen, M., Cheng, L., & Liu, Q. (2020). Differentiate quality of experience scheduling for deep learning applications with docker containers in the cloud. arXiv preprint arXiv:2010.12728.
  • Mathew, T. V. (2012). Genetic algorithm. (30 March 2022) retrieved from http://datajobstest.com/data-science-repo/Genetic-Algorithm-Guide-[Tom-Mathew].pdf
  • Mbaabu, O. (2020). Intelligent agents in artificial intelligence. (25 March 2022) retrieved from https://www.section.io/engineering-education/intelligent-agents-in-ai/
  • McCormack, A., & Fortnum, H. (2013). Why do people fitted with hearing aids not wear them? International Journal of Audiology, 52(5), 360-368.
  • Mirjalili, S., Song Dong, J., Sadiq, A. S., & Faris, H. (2020). Genetic algorithm: Theory, literature review, and application in image reconstruction. In Nature-Inspired Optimizers (69-85) Springer:
  • Mulfari, D., Minnolo, A. L., & Puliafito, A. (2017, May). Building tensorflow applications in smart city scenarios. In 2017 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 1-5). IEEE.
  • Murero, M., Vita, S., Mennitto, A., & D'Ancona, G. (2020). Artificial intelligence for severe speech impairment: innovative approaches to AAC and communication. CEUR Workshop Proceedings 2730, pp. 1-6
  • Najafzade, A. (2020). AI for better integration of people with disabilities (Visual impairment) (Unpublished master’s thesis). Tallinn University of Technology.
  • Nielsen, J. B. B., Nielsen, J., & Larsen, J. (2014). Perception-based personalization of hearing aids using Gaussian processes and active learning. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 23(1), 162-173.
  • OrCam (2021). About OrCam. Retrieved from https://www.orcam.com/en/about/.
  • Özdemir, O., & Kalınkara, Y. (2020). Bulanık Mantık: 2000-2020 Yılları Arası Tez ve Makale Çalışmalarına Yönelik Bir İçerik Analizi. Acta Infologica, 4(2), 155-174.
  • Pavlopoulos, J., Vrettaros, J., Vouros, G., & Drigas, A. S. (2008, September). The Development of a Self-assessment System for the Learners Answers with the Use of GPNN. In World Summit on Knowledge Society (pp. 332-340). Springer, Berlin, Heidelberg.
  • Pirim, H. (2006). Yapay zeka. Journal of Yaşar University, 1(1), 81-93. Rego, N., (2017). Aipoly Vision Wins the Best of Innovation Award at CES2017. Cool Blind Tech. Retrieved from https://coolblindtech.com/aipoly-vision-wins-the-best-of-innovation-award-at-ces2017/.
  • Rende, F. Ş., Bütün, G., & Karahan, Ş. (2016). Derin Öğrenme Algoritmalarında Model Testleri: Derin Testler. 10. Ulusal yazılım Mühendisliği Sempozyumu,24-26 Ekim, pp:54-59, Çanakkale. Russell, S. J., & Norvig, P. (2020). Artificial intelligence: a modern approach (Fourth edition), Pearson Education.
  • Sadauskaite, J. (2017). Artificial intelligence tools to overcome autism disorders. Smart Week. Retrieved from https://www.smartweek.it/artificial-intelligence-tools-to-overcome-autism-disorders/.
  • Sağıroğlu, Ş., Erler, M., & Beşdok, E. (2003). Mühendislikte yapay zeka uygulamaları-I: yapay sinir ağları. Kayseri: Ufuk Kitap Kırtasiye-Yayıncılık.
  • Santoki, S., & Patvardhan, N. (2019). To research the advantages and limitations of AI based app in the Indian context for the visually challenged. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(6S4), 271-278.
  • Schipor, O. A., Pentiuc, S. G., & Schipor, M. D. (2010). Improving computer-based speech therapy using a fuzzy expert system. Computing and Informatics, 29(2), 303-318.
  • Sherbin, B. (2018). Israeli ai startup restores speech abilities to stroke victims, others with impaired language. Retrieved from: https://blogs.nvidia.com/blog/2018/11/28/voiceitt-ai-startup/.
  • Shrestha, A., & Mahmood, A. (2019). Review of deep learning algorithms and architectures. IEEE Access, 7, 53040-53065.
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There are 67 citations in total.

Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Articles
Authors

Nihal Şen 0000-0002-9511-8401

Tuncer Akbay 0000-0003-3938-1026

Early Pub Date December 30, 2023
Publication Date December 31, 2023
Submission Date May 16, 2023
Acceptance Date September 7, 2023
Published in Issue Year 2023

Cite

APA Şen, N., & Akbay, T. (2023). Artificial Intelligence and Innovative Applications in Special Education. Instructional Technology and Lifelong Learning, 4(2), 176-199. https://doi.org/10.52911/itall.1297978

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