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Artificial Intelligence
Home›Artificial Intelligence›How Machine Learning Is Transforming Assistive Technology

How Machine Learning Is Transforming Assistive Technology

By Matthew Lynch
May 18, 2020
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You may hesitate to embrace machine learning until you see how it’s transforming assistive technology.

In the past, machine learning has caused suspicion about its ability to transform the learning experience for many learners. Some teachers have been slow to trust that a machine can diagnose a learning disability, prescribe an instructional intervention, execute the strategy, and monitor its effectiveness.

For students with disabilities, machine learning is equalizing opportunities in the classroom. It’s also relieving some of the time-consuming burden placed on teachers when planning specialized instruction.

Identifying the need for assistance

Diagnosing a learning disability can be tricky, especially in younger students or those who are learning English as a second (or third) language. Teachers often are told to wait, gather data, and then make a request for testing. The process can take months. As each week slips by, the affected students fall further behind.

Machine learning and artificial intelligence can assist with making accurate diagnoses. The computer can even prescribe a plan of action for both academics and behavior.

Helping learners with intellectual and developmental disabilities

Machine learning is taking on the task of pairing edtech to learners with I/DD. This particular facet of artificial intelligence uses pre-processing steps to analyze the current status of learning and what intervention a student needs. The result is a customized approach to instruction.

As machine learning grows, it becomes more capable of developing unsupervised algorithms. These complex formulas allow the machines to act independently when making instructional decisions regarding students who need intervention and assistance.

For example, if machine learning is taught that students with I/DD often have reduced numbers of answer choices, the program will automatically reduce the answer choices from four to two. No one has to make the request. Machine learning does it automatically.

Learning to live independently

People with disabilities may find a new reliance on machine learning for some of the basic daily living tasks most people take for granted. Machine learning serves as a live-in companion. Computer assistants automatically set thermostats, check for open doors, and turn off cooktops.

Using machine learning in the home isn’t new. Many people already rely on machine learning to clean their floors with a programmable robot.

There are many other assistive devices that have improved the quality of life for people with disabilities. People who have epileptic seizures receive warnings from a special belt in advance of the event. Blind learners have had text-to-speech apps, but now their smartphones can recognize Braille. Students with difficulty learning benefit from FM technology.

Machine learning and artificial intelligence have made these advances available. Students who would otherwise be disadvantaged in the classroom and their home environments find themselves able to take advantage of technology.

And for teachers and caregivers who may have doubted the benefits of machine learning, rest assured that it’s already here. Students with disabilities are already benefiting from assistive technology that wasn’t present a mere ten years ago.

Machine learning isn’t going away. It’s making learning and living more accessible.

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Since technology is not going anywhere and does more good than harm, adapting is the best course of action. That is where The Tech Edvocate comes in. We plan to cover the PreK-12 and Higher Education EdTech sectors and provide our readers with the latest news and opinion on the subject. From time to time, I will invite other voices to weigh in on important issues in EdTech. We hope to provide a well-rounded, multi-faceted look at the past, present, the future of EdTech in the US and internationally.

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