Artificial Intelligence is on the rise, and so are we (as educators).
Artificial intelligence (AI) is becoming more prominent in our day-to-day lives – like Siri on your iphone, or on a more basic level, those blasted recordings we refer to as phone-trees when you call the bank. AI is getting “smarter” every year and has the potential to make learning personalized and fun! It may be a little intimidating that AI technology is advancing so quickly, but there are still things that remain difficult to achieve such as the human quality of free will and the sense to know that which they do not understand. Bostrom (2012) stated, “an agent [AI] might not value knowledge and understanding for their own sakes” (p. 79). It is this type of statement that is both reassuring, because AI is not human, but it’s also a little disconcerting that the value of AI as being anything is being considered. The good part is that AI is getting better and better and will have positive effects on education, without replacing teachers.
Everyone has their own logic, but as educators we help students learn by creating and altering the rules that define their existing concepts.
Thagard (1996) states, “rules can be learned by inductive generalization, in which examples are summarized by means of a rule… with experience you can use a higher-level rule” (p.49). Although it may not be possible for students to learn everything, understanding that we, as educators have the capability to make even a small computational changes to existing representations in the students’ minds, will have an effect on learning. True learning may not occur at the moment in time we desire, but given enough exposure to specific examples and scenarios, a student’s logic will change because their rules will have changed. In the video How We Learn – Synapses and Neural Pathways Rogers (2010) explains how learning new information is like crossing a ravine for the first time. A first it is difficult and slow, but with repeated experience (repetition) the “bridge” to new knowledge becomes easier and quicker.
Learning styles are varied, and so shall your teaching approach.
After taking a quick online assessment of my learning style I was able to identify, well actually it was more like a verification of what my learning preferences are and what they are called. Then, using suggestions by Felder and Soloman (n.d), I read about both the benefits and challenges of my learning style. While I found the information helpful from the perspective of a student, as a future educator it stands to say that my learning style is only one of many ways in which individuals prefer to receive information Willmingham (2008) suggests that our memories or representations are stored in one or multiple sensory formats. Which is to say, that although students may have a preference for how they obtain and recall information, the teaching approach can and should be varied. Cummings (2009) suggests that if you want to reach all of your students you need to ask them to write it, say it, do it.
Bostrom, N. (2012). The superintelligent will: Motivation and instrumental rationality in advanced artificial agents. Minds & Machines, 22(2), 71-85. doi:10.1007/s11023-012-9281-3
Cummings, K. (2009). Teaching Strategies – LearningStyles [Video file]. Retrieved January 20, 2015 from https://www.youtube.com/watch?v=oNxCporOofo
Felder, R., & Soloman, B. (n.d.). Learning Styles and Strategies. Retrieved January 20, 2015 from http://www4.ncsu.edu/unity/lockers/users/f/felder/public/ILSdir/styles.htm
Rogers, R. (2010). How We Learn – Synapses and Neural Pathways [Video file]. Retrieved January 20, 2015 from http://www.youtube.com/watch?v=BEwg8TeipfQ
Here is a link to the online assessment questionnaire I used from Felder & Soloman, North Carolina University. Learning Styles Questionnaire.
How Does the Brain Learn Best? Smart Studying Strategies by Mindshift. http://blogs.kqed.org/mindshift/2014/08/how-does-the-brain-learn-best-smart-studying-strategies/