How Can Artificial Intelligence Support Students with Special Education Needs?

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 How Can Artificial Intelligence Support Students with Special Education Needs?

Artificial Intelligence
 Dr. Muhammad Uziar Ul Hassan     Sahib Khan Ph.D. 
                                                                                   Dr. Amber Farooq


Introduction:

Artificial intelligence (AI) has the potential to transform the education sector by offering students with special education needs (SEN) personalized learning experiences. AI-based software and solutions can help instructors detect SEN-specific learning needs and give them individualized support. In this blog, we will examine the current literature on how artificial intelligence can help pupils with special education requirements. AI can significantly assist students with special education needs (SEN). Using AI, educators can detect each SEN student's unique learning needs and provide personalized guidance to improve their academic performance.

Students with special education needs (SEN) frequently require additional assistance to overcome learning hurdles and achieve academic achievement. With advances in artificial intelligence (AI), educators will be able to provide personalized help to SEN kids and construct inclusive learning environments that meet their specific needs. AI-powered systems can analyze massive quantities of data to discover unique learning styles and construct adaptable learning environments that adapt to the demands of each student. This allows SEN students to learn at their own pace while receiving immediate feedback on their progress. Furthermore, AI-based programs can help pupils who have difficulty comprehending language, physical infirmities, or visual impairments. AI can help students with SEN overcome learning challenges and make their education more accessible by providing assistive technology such as text-to-speech capabilities, object recognition, and other tools.


Furthermore, predictive analytics enabled by AI can help instructors identify at-risk pupils and provide tailored interventions to help them. This can assist pupils in avoiding falling behind academically and give early interventions to improve their academic achievements. Despite the potential benefits, the application of artificial intelligence in special education poses ethical problems about data privacy, prejudice, and transparency. As a result, educators and policymakers must carefully assess the ethical implications of artificial intelligence in special education and guarantee that these technologies are used responsibly and transparently. AI can transform special education by offering individualized learning experiences for SEN children and establishing inclusive learning environments that adapt to their specific requirements. However, the ethical implications of these technologies must be thoroughly explored for them to be used responsibly and transparently.


            AI-powered technologies may construct adaptive learning environments that adapt to each student's unique demands, resulting in a personalized learning experience. This can assist SEN students in learning at their own pace and in a manner that is appropriate for their learning style. Furthermore, AI-based programs can help pupils who have difficulty comprehending language, physical infirmities, or visual impairments. AI can help SEN students overcome learning challenges and make their education more accessible by providing text-to-speech capabilities, object recognition, and assistive technologies. AI-powered predictive analytics can also help instructors identify at-risk pupils and provide tailored interventions to help them. This can assist pupils in avoiding falling behind academically and give early interventions to improve their academic achievements.

Literature Reflection

AI-powered programs and technologies can help children with special needs in a variety of ways. The following are some of the current methods in which AI is being used to help SEN students:

Personalized Education

AI can help instructors create personalized learning experiences for children with specific needs. AI-powered systems can identify SEN pupils' specific learning needs and provide them with customized learning experiences. For example, the Smart Sparrow platform employs AI to construct adaptive learning environments that adapt to each student's unique needs (Graesser et al., 2018).

Language Processing

AI can help students who have difficulty comprehending language, such as those who have dyslexia. AI-powered tools can detect language processing mistakes and provide pupils with real-time feedback. Read Write, for example, is an AI-based software that helps dyslexic pupils by giving text-to-speech capabilities and underlining spelling and grammar problems (Moussly et al., 2020).

Assistive Technology

AI can also help students who are physically disabled by offering assistive technology. AI-powered gadgets such as eye-tracking systems, for example, can help students with motor impairments control computer systems (Khan & Alam, 2019). Text-to-speech and object recognition skills provided by AI can also help pupils with visual impairments (Savage et al., 2020).

Predictive Analytics

AI can help instructors estimate the learning outcomes of students with unique needs. Predictive analytics can identify kids who are in danger of falling behind and give them tailored treatments. The Student Success Plan, for example, is an artificial intelligence-based platform that aids instructors in identifying at-risk children and providing personalized interventions to improve their learning results (Snyder et al., 2019).

List of AI tools that can help Students with Special Education needs

Many AI-powered tools can help students with special education needs (SEN) in various ways. Here are some examples:

1.  Text-to-speech software: This software reads text aloud, assisting pupils with visual impairments or dyslexia in understanding written content.

2.  Speech recognition software: By turning spoken language into text, this software can assist kids with speech issues in communicating with their teachers and peers.

3.    Predictive text software: This software can assist students who are having trouble writing by recommending words and phrases as they type.

4.  Object recognition software: This software can assist visually impaired students in identifying items and navigating their surroundings more independently.

5. Virtual assistants: Virtual assistants, such as Siri, Alexa, and Google Assistant, can aid students with impairments in accessing information and doing tasks through voice commands.

6. Adaptive learning software: This software can change the pace and difficulty level of learning exercises to match the needs of individual pupils.

7. Machine learning algorithms: These algorithms can analyze data to detect patterns and forecast results, allowing educators to identify at-risk pupils and provide targeted interventions.

8. Brain-computer interfaces: These gadgets allow students with physical limitations to manipulate computers and other devices with their minds.

9. Robotics: Robots can assist students with physical limitations in interacting with their surroundings and participating in educational activities.

These are just a few examples of artificial intelligence-powered applications that can assist students with special education needs. The possibilities are endless, and the application of AI in special education is always growing. Finally, AI can transform the education industry by providing personalized learning experiences to students with unique needs. AI-based software and solutions can help instructors detect SEN-specific learning needs and give them individualized support. However, AI-based tools and applications in special education are still in their early phases, and more research is needed to understand the potential benefits and problems of employing AI in special education.

Bibliography:

Graesser, A. C., D’Mello, S. K., & Cade, W. L. (2018). Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence. Educational Research Review, 24, 1-18.

Khan, N. A., & Alam, S. S. (2019). Eye Gaze Based Assistive Technology for Persons with Disabilities: A Review. International Journal of Computer Applications, 180(40), 1-6.

Moussly, G., Abdelrahman, Y., & Sayed, S. (2020). Assistive Technology for Dyslexia: A Comprehensive Survey. International Journal of Emerging Technologies in Learning (iJET), 15(23), 160-180.

Savage, R., Koester, H. H., & Hager, J. (2020). Smart glasses for the visually impaired: A review of the recent state-of-the-art. Journal of Ambient Intelligence and Humanized Computing, 11(4), 1499-1514.

Snyder, T., de Brey, C., & Dillow, S. (2019). Digest of Education Statistics 2018 (NCES 2020-009). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Retrieved from https://nces.ed.gov/pubs2019/2019009.pdf

 

 

 

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Thank you for being a member of our community; we look forward to reading your contributions.

Sincerely,

                
                Sahib Khan (Ph.D. Education) 

                University of Sargodha, Sargodha
                Senior Special Education Teacher,
                Department of Special Education,
                Government of Punjab,
                Sargodha, Punjab, Pakistan, 40100 
                +923006105139, s.khansajid139@gmail.com


                Dr. Muhammad Uzair-ul-Hassan

                Associate Professor / Chairperson
                Department of Education, University of Sargodha, Sargodha
                uzair.hassan@uos.edu.pk

                

                Dr. Amber Farooq (Ph.D. Education) 

                University of Sargodha, Sargodha
                 Amberchand559@gmail.com



 

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