Personalized learning vs. simulated classrooms during school closure?

Many of us who write blogs key off each other’s posts. One of my favorites is

Computing Education Research Blog by Mark Guzdial

The following notes are my response to his latest commentary , So much to learn about emergency remote teaching, but so little to claim about online learning  , about a suggestion that we take advantage of enforced school closures to compare classroom with online instruction. Thank you, Mark, for your insightful comments. 

Teaching and Learning

I want to reinforce the idea that ‘teaching’ and ‘learning’ are very different behaviors and shouldn’t be conflated. Human ‘learning’ is always local. It manifests as change within an individual mind/body or change in the collective processes of an organization. Sometimes learning is a result of intentional teaching. Most of the time humans learn from observing other people and from spontaneously interacting with their environments. 

IMG_0500Teaching’ is a behavior performed by individuals or groups of individuals with the goal of stimulating learning in someone else. If a student fails to demonstrate, in some measurable way, that s/he has changed as the teacher intended this is not evidence that learning has not taken place. It only tells us that the teaching failed. Much may have been learned although ignored by the teacher.

Both teaching and learning always take place in an environment. As living humans we are always somewhere and that somewhere has physical and social characteristics. A classroom is a highly structured social environment designed to enhance one-to-many teaching. Sometimes classrooms also enhance learning. Sometimes, for some learners, classrooms inhibit success.

New Skills Needed

With these distinctions in mind let’s turn back to closed schools and “remote emergency teaching”. Whether the communication channel is the internet or snail mail, remote teaching happens in environments drastically different from traditional school or college classrooms. Teachers need a whole new repertory of behaviors to help their students absorb academic material. Students also need new study and social skills to adapt to this task while in their home environments. Perhaps, during this time of social and medical crisis, we educators would be wise to ease up in our efforts to teach academic subjects except when interacting with students who are intrinsically motivated to learn them. Instead, we have an opportunity to help our students explore/learn about/master/reflect on these three topics:

1. online communication. This includes how to operate the myriad features of the electronic device (computer, tablet, smart phone) you have available, how to use the software that runs on your device, how to craft the messages you choose to distribute via your device, and how to evaluate the messages you receive.

IMG_E12242. intrinsic personal interests. In physical school, teachers get to choose what students must attend to and, for the most part, have tools to enforce student compliance. This is very difficult to do in remote teaching. Therefore, now is the time for young and old learners to discover what captures and holds their attention spontaneously. 

 

 

 

 

 

IMG_00853. learning styles and environmental preferences. While modern teachers may pay lip service to the idea that one student may memorize information more effectively by watching a video, another by reading a book and a third by acting in an improvised play, most classroom lessons are more mono- , than multi- media. The explosion of online information in many formats creates an opportunity for learners to experiment with and reflect on the ‘envelop’ that contains the information that interests them. Similarly, we are always in an enveloping environment of people, noise, smells, furniture, etc. while learning. My brother may find sitting on a park bench with people all around him the perfect place to read on his smart phone. I may prefer to sit at my desk computer in a warm, empty room with only the ticking of the clock for sound. My sister may thrive in a group of three friends in the living room discussing their ideas and interests with the radio blaring music and occasional dips into social media on their tablets. (It is possible to do all this while still maintaining 6 foot social distancing.)

Now Is a Good Time To Personalize

Learners who understand their own interests and preferences, know how to use their digital tools and are willing to take charge of putting themselves in a personally optimal learning environment are poised to thrive both in the current crisis and during more normal times. Isn’t this a moment when we can let academics slide a little and go for serious investigation of the skills, advantages and perils of online teaching and learning?

Individualizing Education with AI

As I surf the web I find an increasing number of posts about “deep learning”… I’m always disappointed to discover the learner is a neural network computing machine, not a human – not even an animal. See, for example

Deep Learning in a Nutshell: Reinforcement Learning

I’d like to apply this kind of deep machine learning to a problem in human education: the matching of learners’ characteristics (background knowledge, learning styles and goals) with learning objects (more properly labeled “teaching objects” including Open Educational Resources, free-lance teachers and communities of practice). The machine (AI) would scan the profile of the learner and search online for the most appropriate collection of teaching objects to meet the learner’s goals given his/her abilities and background knowledge.

This is actually not a very challenging logical problem for a computer but it does involve gathering a lot of data and learning (by the machine) about which matches are useful to the learner. Two metadata considerations make this difficult to implement:

First: We don’t have very elaborated ways of describing learner characteristics. At the moment we usually note academic subject, language (natural, not machine) and educational level of the learner. There’s a lot more to know about learning styles, for example, whether the student is

  •  self-directed or other-directed
  • predominantly visual, auditory or kinesthetic
  • intellectual strengths and weaknesses (see SOI)
  • physical abilities/handicaps (accessibility)
  • solo or social (independent or classroom)

to name just a few.

Second: When we catalog teaching objects (Open Educational Resources (OER) in, say, OpenStax CNS, OERCommons, MIT’s Open CourseWare, we don’t provide the learner enough information about the resource to figure out whether s/he can benefit from the material offered.

By combining crowdsourcing of feedback on materials as learners try to use them and developing better descriptions of learners we would have the prerequisites to use deep learning AI’s to teach many more students much more effectively.

In future blogs I’ll explore learner characteristics, OER and other ideas we might use to implement a new “open educative system” that could support learning in this century better than our current classroom-teacher-school-based “educational systems” do today.

If this topic interests you, I’d love to hear from you. Please leave a comment here or email 

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