Disrupting Class: Chapter 4: Disruptively Deploying Computers

disrupting-class

Summary:

One of the case study students wants to study Arabic, but it isn’t offered at her school. Luckily, the principal offers her a chance to participate in an online Arabic course.

This chapter discusses how computer-based learning is likely to disrupt U.S. schooling. Like all disruptive innovations, it will begin by competing against nonconsumption. These settings might include AP courses, credit recovery, special tutoring, prekindergarten–anything that is not generally available to all students. In small, rural schools, urban secondary schools, and homeschooling situations, there are often learning experiences that would be nice to have, but, due to lack of resources, are not always available. Computer-based learning would be a welcome solution in these situations where the alternative is to forgo offering that subject altogether. By providing options in these moments of nonconsumption, computer-based learning will gain a foothold in the market. “Disruptive innovation requires…focus[ing] on courses that the pubic schools would be relieved not to have to teach, but do feel the need to offer” (p. 103). Teachers unions and funding models that penalize per-pupil funding for schools when students take online courses may impede this disruption, but the authors suggest that this kind of impediment will likely not be sufficient to prevent the shift to computer-based learning. They also mention that the lack of a free market will not prevent the disruption either. 

The authors then suggest that disruptive innovations tend to follow similar patterns as they gain market share. These patterns are graphed and discussed. The takeaway: The data (as of 2008) suggest that approximately 50% of high school courses will be delivered online by 2019. This disruption will unfold slowly at first, but accelerate due to four factors: product improvement (as computer-based learning is honed as it competes against nonconsumption); the ability of students, teachers, and parents to select appropriate learning pathways; the looming teacher shortage, as baby-boomers retire; and lower costs as computer-based learning scales up.

What will post-disruption classrooms look like? The authors first turn to Virtual ChemLab, a course designed by a BYU professor, in which students can virtually conduct experiments. Although perhaps not as good as actually working in a lab, this ChemLab is “infinitely better than many students’ alternative–nothing at all” (p. 105). Other courses of other subjects might look similar, with teachers acting as mentors and motivating students to remain focused, rather than lecturing in front of the class. As the role of the teacher changes, so would the role of assessment. Instead of testing students at the end of the unit, essentially measuring which percentage of students mastered the material, computer-based learning would allow for ongoing assessment that was tied to the delivery of material.

This kind of ongoing, interrelated assessment and instruction is compared with Toyota’s assembly plant. Instead of teaching workers everything that will be required of them on the assembly line, sending them to the line, and then inspecting their product for errors afterward (as happens in some assembly lines), Toyota only teaches one step at a time. Once workers have demonstrated mastery of each step, they move on to the next step. Not only was testing and assessment an integral part of the training, but there were mechanisms built into the assembly process that verified immediately that each step had been done properly. Because of this, Toyota did not need to spend time and money inspecting and fixing products at the end of the line. The analogy is clear: schools are like the assembly lines that teach, release, and then test at the end; computer-based learning is like Toyota, where “assessment and individualized assistance can be interactively and interdependently woven into the content-delivery stage” (p. 111).

Commentary:

I wonder if the data still suggest that the education system is on track for disruption. It certainly doesn’t seem that by 2019, 50% of high school courses will be offered online. I’d be interested to know if the authors have updated that prediction at all.

A few issues: I felt that the portrayal of teachers’ assessments was a bit of a strawman. Although the batch-processing, test-at-the-end-and-move-on system is real, teachers are encouraged not to do that. “Formative assessments” is the term that describes the Toyota-style of teaching, and it is not something that is unique to computer-based learning. If the batch-processing model of teaching is not inherent in the school system, and if teachers do shift to a formative assessment approach with differentiated instruction (these are concepts that practically all teachers will know), how would that affect the disruption model?

Also, the emphasis on individual learning paths and isolated students working on computers underlined the fundamentally individualistic perspective of learning this book is based on. Sociocultural theorists would likely take issue with this. Vygotsky’s famous concept of “zone of proximal development,” for example, suggests that students’ potential is best measured by that which they can accomplish in collaboration with other people, not that which they can do on their own. Computer-based learning, at least as it seems to be conceptualized here, seems to view individuals and not interactive systems as the unit of analysis.

Here’s a big idea that may be only tangentially related to this chapter: What if we used computers to provide context rather than content for learning? Instead of giving learners the next module they are ready for, what if computers provided an immersive context in which students and teachers could interact? I’ll keep thinking about that.

 

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