Elearning August-September

AUG-SEP 2016

Elearning! Magazine: Building Smarter Companies via Learning & Workplace Technologies.

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Elearning! August / September 2016 43 to to her, and her AI framework allowed her her, and her AI framework allowed her to to interact with the person in a conversa- interact with the person in a conversa- tional tional mode. She represented the precursor mode. She represented the precursor of of the personal tutor — especially when the personal tutor — especially when Bina48's Bina48's caretaker mentioned that she caretaker mentioned that she would would one day sell for less than an iPhone one day sell for less than an iPhone at at a store like Sharper Image. at price a store like Sharper Image. at price point point could potentially mean a personal could potentially mean a personal tutor tutor in every home. in every home. Social robotics is not the only avenue for for AI. It's being used successfully in de- AI. It's being used successfully in de- vices vices as ubiquitous as our mobile phones, as ubiquitous as our mobile phones, as as well as in products like Alexa that Ama- well as in products like Alexa that Ama- as well as in products like Alexa that Ama- zon zon successfully brought to market. Using successfully brought to market. Using either either of these devices, we can verbally ask of these devices, we can verbally ask either of these devices, we can verbally ask questions questions that we don't know the answers that we don't know the answers to. to. All of this tutoring-like technology is All of this tutoring-like technology is thanks thanks to AI algorithms. And considering to AI algorithms. And considering its its rapid proliferation by major soware rapid proliferation by major soware and and hardware producers, it appears that hardware producers, it appears that in in the next decade we're going to be able the next decade we're going to be able to to solve the elusive 2 Sigma Problem us- solve the elusive 2 Sigma Problem us- ing ing AI. But if a Bina48-lookalike is not AI. But if a Bina48-lookalike is not by by our side tutoring us or answering our our side tutoring us or answering our every every informational need, maybe it'll be a informational need, maybe it'll be a wearable wearable device that will provide us with device that will provide us with coaching, coaching, tutoring and mentoring that tutoring and mentoring that can can help us with our form and tell the help us with our form and tell the wearer wearer when he or she is at the gym and when he or she is at the gym and isn't isn't in the correct position to li as much in the correct position to li as much weight weight as they would like. ese latter as they would like. ese latter devices devices are now in early stages of funding are now in early stages of funding and and development in the form of wearable development in the form of wearable vests, vests, and the investment backing is com- and the investment backing is com- ing ing from the insurance industry, which from the insurance industry, which certainly certainly has a vested interest in helping has a vested interest in helping people people avoid injuries. Another possibility avoid injuries. Another possibility is is that tutoring might just be integrated that tutoring might just be integrated into into our work environment or in our work our work environment or in our work into our work environment or in our work equipment, equipment, much like navigation is now much like navigation is now integrated integrated into our cars. into our cars. To ultimately solve the entire 2 Sigma Problem, Problem, we're going to need to consider we're going to need to consider another another teaching conundrum. Part of any teaching conundrum. Part of any teacher's teacher's role is to present new information role is to present new information to to students, even when a student didn't ask students, even when a student didn't ask for it. e notion divides knowledge into three categories: 1. ings we know (known knowns); 2. ings we don't know (known un- knowns); and 3. ings we don't know, we don't know (unknown unknowns). The concept of "known unknowns" and "unknown unknowns" has largely been attributed to NASA in its work. The known unknowns are generally cat- egorized into risks that can be measured for compliance, such as the operation of various various sensors in a space craft. It's the sensors in a space craft. It's the unknown unknowns that are a result of unexpected or unforeseeable conditions, such as a properly installed heat panel failing during re-entry. We encounter similar problems when we learn more about a topic. ere are things we know, and things we know that we don't know. But how can we be tutored by a technology, unless that technology can introduce the things that we don't know we don't know? at will be the final obstacle to over- come when we use AI technology to create an EdTech tutoring device. Just as a hu- man tutor would be able to suggest that a student should consider an additional topic he or she might not be aware of, we need to build that "suggestive capability" into our AI tutors. Additional Reading: Benjamin S. Bloom, "The 2 Sigma Problem: The Search for Methods of Group Instruc- tion as Effective as One-to-One Tutor- ing," Educational Researcher, American Educational Research Association, Vol. 13, No. 6. (Jun. - Jul., 1984), pp. 4-16. URL: http://web.mit.edu/5.95/read- ings/bloom-two-sigma.pdf. REFERENCES Most importantly, reinforcement provides a 1.2 sigma impact on student achievement.

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