Artificial Intelligence Technology to Help Students With Disabilities: Promises and Implications for Teaching and Learning

Artificial Intelligence Technology to Help Students With Disabilities: Promises and Implications for Teaching and Learning

Rashi Kohli, Sparsh Phutela, Anchal Garg, Mark Viner
DOI: 10.4018/978-1-7998-7630-4.ch013
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This chapter reviews current and future artificial intelligence (AI) to meet the needs of numerous students with special learning requirements. The current AI technology and AIEd Models are explored with the better diagnosis there is need to improvise the process of learning by interventions and making it efficient in a playful manner. The chapter caters to the various existing software's for the purpose and how they can be improvised in future. AI focuses on creating technology to perform functions like speech recognition, learning, and problem-solving. The technology has been widely spreading, and many AI tools have been developed to cater to the needs of exceptional learners within the classroom. The technology has developed interactive programs that help classroom teachers in differentiating instruction in the classroom. This chapter highlights the current analysis of the AI and AIEd models that have helped students with special learning needs. Furthermore, it also highlights the functioning of the AIEd model as well as how AI can help instructors and learners learn differently.
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The field of Artificial Intelligence (AI) and Machine Learning (ML) over the past three decades has been growing at an increasing rate. Many tools have been developed to cater to the needs of students starting from elementary education to the college level. The concept of AI technology is constantly being applied to the education sector, which helps to develop skills and testing systems. As AI instructive arrangements keep on developing, the expectation is that AI can help fill holes in learning and educating. Man-made intelligence can drive proficiency, personalization, and smooth out administrator assignments to permit educators the time and opportunity to give comprehension and flexibility—extraordinarily human capacities where machines would battle. By utilizing the best traits of machines and educators, the vision for AI in instruction is one where AI is cooperated into teaching and learning to benefit students. Based on research across several disciplines, AI will be prevalent in the future and our educational institutions must be open to utilizing AI technologies for innovation. For example, teachers need to utilize virtual AI-based technology by developing lesson plans that will promote students' growth in academically challenging environments.

While the definition of Artificial Intelligence can vary, generally Artificial Intelligence refers to human intelligence simulated into machines that are programmed to think like humans and replicate their actions. The term can be expanded to any computer that shows human brain-related characteristics such as learning and problem solving. The first part of this chapter explores “What should students learn in the age of AI”. It is widely expected that AI has and, in the future, will have an enormous impact on how teachers utilize technology tools to differentiate and design institutional practices. AI machines can formulate decisions and take actions like humans. The overall objective placed behind these machines is to fabricate a method with state-of-art strategic thinking. These machines possess abilities to reason, catering to solutions to a problem that cascades the learning process using experiences. The specific skills these machines are imbibed with are a blend of Natural Language Processing (NLP), expert systems, aptitude for fuzzy logic, neural networks, and robotics (Wu et al., 2006). This amalgamation of the natural language processing ability and artificial intelligence is the underpinning of an advanced machine system such as a flight tracking system or healthcare-oriented machines.

Natural Language Processing (NLP) aids in the processing of language that includes the assembly of translation and the generation of language from various virtual compartments. The most paramount domain of implication of AI is Robotics. Robotics is the use of robots that are experts for a particular task in a real-time environment. The algorithms and computer programs are the elementary units for robots that allow them the ability to run in a computer-simulated environment. AI provides the proclivity for the sole formulation of codes that can be altered as per the requirement needed. For example, robots are now capable of self-reflection, self-direction, and working in teams. The aggregating vitality of the AI can be recognized by the fact that various complex systems can work by human commands. AI robots can now effectively understand human speech at a high level of accuracy and may interact with humans (Malik et al., 2019).

Key Terms in this Chapter

ADHD: A mental illness.

Special Education: The process of individualized education for the students of special mental needs.

Speech Recognition: The ability of artificially intelligent machines to recognize the speech commands and execute them.

Assistive Technology: Technological aid in making the process easier for the individuals with disabilities.

Machine Learning: The process of understanding and fabricating the algorithms for enabling machines to be artificially intelligent.

Natural Language Processing: The blend of linguistics and artificial intelligence enabling the interface between machines and user.

Autism Spectrum Disorder: A neurological differential ability.

AIED: The dissemblance of Artificial intelligence for plethora of educational platforms.

Artificial Intelligence: The capability of the machines to evolve and execute tasks on the process of adaptation.

Learning Disabilities: Hindrances in acquiring memory.

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