A modified version of this post appeared on the Techsmith Blog here and in their quarterly newsletter, the Learning lounge. I appreciate their interest in my perspective. I hope to continue this important discussion here with my readers.
The idea of computational thinking has radically changed my approach to teaching over the past few years. This term, first coined by Jeanette Wing, a professor of computer science at Carnegie Mellon University, refers to several key ideas of thinking that are essential to computer science. The paper clearly identifies the reality that there are some tasks that computers do extremely well, and others that are better suited to the human brain. Traditionally, computer scientists have worked to outsource the calculating, organizing, searching, and processing work for task X to a computer so that they can focus on the more complex, challenging, and engaging aspects of the same task. According to Wing, one of the most essential skills we should develop in students is sorting tasks into these two groups.
My classroom, at its best, is a place where maximum time is spent with students wrestling with an engaging task. They should be working together to develop both intuition and understanding for required content. I can read the smiles or frowns and know whether I should step in. I can use my skills to nudge students in the right direction when I think they need it. Knowing precisely when they need it can't easily be determined by an algorithm. For some students, this moment comes early on after encountering a new concept. Others require just one more minute of struggle before the idea clicks and it's in their brains for good. Knowing the difference comes from the very human experience of time in classrooms with learners.
This is the human side of teaching. It is easy to imitate and approximate using technology, but difficult to produce authentically. Ideally, we want to maximize these personal opportunities for learning, and minimize the obstacles. For me, the computer has been essential to doing both, specifically, identifying the characteristics of tasks that a computer does better. If a computer can perform a task better than me or my students alone, I'm willing to explore that potential.
The most consistent application of this principle has been in the reduction of what I call 'dead time'. I used to define this as time spent on tasks required for learning to be possible, but not actually a learning task itself. Displaying information on the board, collecting student answers, figuring out maximum and minimum guesses for an estimation problem - these take time. These sorts of tasks - displaying, collecting, processing - also happen to be the sort at which computers excel. I wrote a small web application that runs from my classroom computer that allows students to snap a picture of their work and upload it to my computer, anonymously if they choose. We can then browse student answers as a class and have discussions about what we see. The end result is equivalent to the idea of students writing their work on the board. The increased efficiency of sharing this work, archiving it, and freeing up class time to build richer activities on top of it makes it that much more valuable to let the computer step in.
I've also dabbled in making videos of direct instruction, but I have students watch and interact with them while they are in the classroom. During whole class instruction, I can't really keep track of what each student is and isn't writing down because I am typically in a static location in the classroom. With videos simultaneously going throughout the classroom, I can see what students write down, or what they might be breezing through too quickly. I get a much better sense of what students are not understanding because I can read their faces. I can ask individualized questions of students to assess comprehension. The computer distributes and displays what I've put together or curated for my students – one of its strengths. My own processing power and observation skills are free to scan the room and figure out what the next step should be.
Letting the computer manage calculation (another of its strengths) enables students to focus on the significance of calculations, not the details of the calculations themselves. This means that students can truly explore and gain intuition on a concept through use of software such as Geogebra or a spreadsheet before they are required to manage the calculations themselves. For students that struggle with arithmetic operations, this enables them to still make observations of mathematical objects, and observe how one quantity affects another. This involvement has the potential to inspire these same students to then make the connections that underlie their skill deficiencies.
Full disclosure though: I don't have a 100% success rate in doing this correctly. I've invested time in programming applications that required much more effort than an analog solution. For instance, I spent a week writing all of my class handouts in HTML because the web browser seemed like a solution that was more platform independent than a PDF. That ended when I realized the technology was getting in the way of my students making notes on paper, a process I respect for its role in helping students make their own learning tools. There are some tasks that work much more smoothly (or are just more fun) using paper and a marker.
I value my student’s time. I value their thoughts. I want to spend as much class time as is possible building a community that values them as well. Where technology gets in the way of this, or adds too much friction to the process, I set it aside. I sit with students and tell stories. I push them to see how unique it is to be in a room for no other reason but to learn from each other. When I can write a program to randomize groups or roll a pair of dice a thousand times to prove a point about probability, I do so.
Knowing which choice is better is the one I wish I could write an algorithm to solve. That would take a lot of the fun out of figuring it out for myself.