Educational Algorithms in Special Education’s Future

Exciting Changes in Education

Education News seems to show a major trend toward personalized learning. Is there anyone who has seen Sugata Mitra’s talks about Child Driven Education and not been deeply impacted by the amount of amazing potential in children waiting to be unleashed? His idea isn’t necessarily a brand new one, but how he implements child-focused learning is groundbreaking.

 

Teachers who implemented child-focused flipped classrooms years ago have also certainly seen the benefits of differentiated learning. No one can deny the research provided by Columbia College about Teach to One math program, which began as School of One in New York City. The research shows personalized learning making a significant impact in the lives of students. Right now, the algorithm by the School of One isn’t truly accessible for everyone due to equipment costs. This math algorithm also doesn’t address every topic in education, but there should be algorithms created to do this.

 

I think the questions remaining are not if or how education will move toward personalized, differentiated and inclusive learning, but when and where. Right now, countries and school districts on the forefront of educational technology are embracing this new school of thought, but other countries are not connecting with the trend due to equipment difficulties, lack of training, lack of research data or lack of data consumption and comprehension. These issues will stand in the way of a global movement toward child-focused education. But, when the whole of the educating, global population shifts its lesson plans and technology usage, special education issues will thankfully be included in that mix.

 

Special Education of the Future is for Everyone

Even though the most recent research shows that 20% of all children need learning support at some point in their career (Giszczak, 2014), my estimation is that an algorithm for personalized learning will show that more children need learning support than what is currently predicted through research and diagnoses data.

 

An algorithm set to figure out how a child learns best will uncover if a child needs specialized support. If equipped with the right resources, this educational algorithm should be able to assess hiccups between the cerebellum and cerebrum (leading to learning disabilities) and assign students physical exercises for therapy, similar to the DORE program. An algorithm fueled with the right information could help assess emotional difficulties and assign the right in-school therapy for students to cope with difficult emotions, like anger. An algorithm this powerful would be more precise than doctors in recognizing developmental delays, especially important in recognizing autism.

 

Honestly, the most ideal situation would be if the algorithm assigns specialized support without consulting parents, teachers or administrators and doesn’t label the support as “specialized.” This type of learning moves toward Finland’s early intervention model where children are special if they haven’t received special education at some point during their education. This just becomes truly personalized education where every child is supported in their weaknesses and allowed to flourish in their strengths. While implementing the principles found in personalized education, ignoring children with disabilities or special education will prove futile and impossible.

 

Perhaps that’s quite a statement? But personalized learning must address the needs of the disabled or the learning isn’t personalized. Personalizing education also means addressing the whole child, not just subjects of academia. An ideal education system through educational algorithms would allow children to learn whenever they are awake, exploring any topic that can be taught. Children need to explore issues not just of math, but social constructs, societal relationships, culture and language nuisances since these things can be hard to grasp, especially when someone has a disability.

 

Educational algorithms could be used to prepare students for college and for political engagement as empowered citizens. Youth voters are notorious for not engaging in the American political system. By the way, when someone makes and algorithm for American, Chinese and global politics, the programmer can thank me for these ideas by entering me into their program as one of the first students. These topics make my blood pressure rise and my head swirl with contradictory facts and perspectives.

 

Digressing, I can only theorize that the role of the educator will also shift from strictly lecturer or facilitator into a dynamic role of researcher, writer and creator of activities and practices to feed the algorithm with projects it could assign to all of our individually, special students. If educational algorithms were shared globally, they would be a powerful tools, bringing the expertise of a whole nation of teachers, united by their passion for education, to a classroom of eager, ageless students, united by their passion for learning.

 

Reference

Giszczak, J. (2014, November 3). Inclusive Education [Telephone interview].

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