Perhaps Harkness could be modified to be less expensive to implement.
I had one truly good math class during my secondary education, and the way the teacher conducted things sounds a lot like this. Small groups, sitting around a table, talking about the subject. The overall class size was much larger, of course. So what we had was a class subdivided into smaller groups, with the teacher circulating among the tables, spending maybe 10 minutes at a time at each one.
I suspect the real problem with this approach, at least from an American perspective, is that it's not easy enough to instrument for data collection. You can't measure "mastery", so instead you measure performance on multiple-choice questions. And then you tie funding to goals related to those tests. . . at which point, no matter what you _want_ the teacher's job to be, what they're really being paid to do is train kids to regurgitate information on multiple-choice tests.
I'm a professional data scientist, and, ironically, being one has resulted in me becoming a deep skeptic of the movement toward data-driven everything. "Data" is understood to be quantitative data, and not everything can be studied quantitatively, so it leads to people habitually deciding, intentionally or not, for better or for worse, to re-frame all their activities in ways that make them easier to quantify and micro-quantify.
To take another example, there's a whole lot of well-established research out there indicating what the best way to pick up a second language is. And you'll never see any of this knowledge being applied to language learning classes in American public schools, because its implications about how we should teach second languages are almost universally incompatible with the teachers' mandate to always be quantifying.
> Perhaps Harkness could be modified to be less expensive to implement.
I think it could to some extent. For some students doing self-paced, online learning for lectures and then following that up with individualized/small-group problem-solving and discussion with peers/tutors/teachers certainly does work.
But kids in early high-school and younger? Someone really needs to be there for them all the time.
BTW, I also had a math instructor that got miraculous outcomes by finely grouping students within each classroom according to skill. She would individualize attention to each group, and then move individual students up or down to different groups depending on their ongoing performance/mastery. She literally had what I would recognize today as a kan-ban chart on a blackboard in the classroom and we, the students, were the projects/products. Thinking back about it now, it must have been a herculean effort. It was also the 70's in a Catholic school and she had total autonomy. I seriously doubt a talented teacher could get away with something like that today.
> I seriously doubt a talented teacher could get away with something like that today.
That's so much of the problem right now. My wife teaches and to be blunt, she is not treated as a professional. She is subject to the exact same kind of intrusive rules that minimum wage phone reps are subject to.
I had one truly good math class during my secondary education, and the way the teacher conducted things sounds a lot like this. Small groups, sitting around a table, talking about the subject. The overall class size was much larger, of course. So what we had was a class subdivided into smaller groups, with the teacher circulating among the tables, spending maybe 10 minutes at a time at each one.
I suspect the real problem with this approach, at least from an American perspective, is that it's not easy enough to instrument for data collection. You can't measure "mastery", so instead you measure performance on multiple-choice questions. And then you tie funding to goals related to those tests. . . at which point, no matter what you _want_ the teacher's job to be, what they're really being paid to do is train kids to regurgitate information on multiple-choice tests.
I'm a professional data scientist, and, ironically, being one has resulted in me becoming a deep skeptic of the movement toward data-driven everything. "Data" is understood to be quantitative data, and not everything can be studied quantitatively, so it leads to people habitually deciding, intentionally or not, for better or for worse, to re-frame all their activities in ways that make them easier to quantify and micro-quantify.
To take another example, there's a whole lot of well-established research out there indicating what the best way to pick up a second language is. And you'll never see any of this knowledge being applied to language learning classes in American public schools, because its implications about how we should teach second languages are almost universally incompatible with the teachers' mandate to always be quantifying.