Category Archives: Curriculum

Should Ed-Tech Platforms Empower or Restrict?

I’ve previously written on being bullish about the potential of ed-tech platforms.

Currently, both Summit Public Schools and Alt Schools are leading the way on developing platforms that may eventually be used by thousands of schools across the country.

Many people are drawn to ed-tech platforms because they can: (1) support teachers to curate innovative lessons and execute more personal coaching; and (2) allow children to learn at their own pace and explore their intellectual interests.

In short, ed-tech platforms are about empowerment.

But it is unclear to me that empowerment will be the only way that ed-tech platforms improve education.

I think they might also improve education by restricting educators and students.

I’m still trying to work through this, but see below for a graphic representation:

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The goal of many (thought not all) personalized and ed-tech enthusiasts is to move from wherever they are to the top right corner.

This vision has much to be said for it, and under the right conditions it very well may work.

But there is also another option – one based more on restriction than empowerment. A couple of great educators have been pushing me to think about this path as well.

The argument for restriction goes something like this:

  1. The No Excuses charter movement has learned a lot about what it takes to increase the learning of students who are multiple grade levels behind.
  2. It will be very difficult to scale No Excuses charter schools due to human capital, operational, and political constraints.
  3. Professional development has proved generally ineffective in spreading the practices of No Excuses charters to mediocre charter and traditional schools.
  4. A tech platform that utilized software that mimics the instructional practices of No Excuses charter schools – and then frees up teachers to do scripted small group and individual tutoring – could be a way to scale the core components of the No Excuses model while bypassing traditional human capital, operational, and political constraints.

Under this scenario, the goal is to move from the bottom-middle row (I do think No Excuses charters are empowering students more than before) to the top-middle row (with more scripted curriculum and teaching structure preventing this model from being ed-tech progressive).

In this model, the tech platform is really a backend way to scale a high-performing whole school model, in that the platform would dictate curriculum, assessments, pacing, and staffing.

Ideally, this packaged model would only take up 3-4 hours a day, and there could still be plenty of time for true project based instruction, extracurriculars, etc.

In summary: perhaps there is a (mostly) best way to teach basic reading and math, and, perhaps, a tech platform can scale this (mostly) best way.

And maybe the “big data” from such a platform could further evolve the (mostly) best way.

I’m not really sure. All feedback welcome.

Quantitative Curriculum Adoption

*Note: I don’t have high confidence in my opinions on curriculum. The below is speculative.*

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I recently visited a high-performing charter high school that serves very low-income students.

During the visit, I sat in on a chemistry class. A student came over to explain to what they were working on and walked me through a problem that had something to do with converting moles to atoms.

To be honest, my initial internal reaction was: “who gives a f**k?”

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I did not expect to have this reaction. So I first tried to check myself on bias: did I think chemistry was not important in this setting because I have low expectations of poor students?

No.

While I do think that the cost of having to learn useless material is higher for students who are further behind, all told, my negative reaction to chemistry is broad: I wish I hadn’t been taught chemistry during my sophomore year of high school.

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I’m surely not the first person to wonder if advanced classes should be taught in high school. A recent New York Time piece made the same argument (but focusing on math instead of chemistry).

The opportunity cost of learning content that will never be used has been recognized by experts for decades, as there is a significant research base on the idea that most knowledge is not transferable across domains (i.e., learning chemistry does not help you learn literature).

But what I haven’t seen is a fleshed out formula about how we might go about making curricular decisions.

So here goes (it’s not rocket science).

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Creating the Curriculum Index:

  1. Analyze some mix of current and medium-term job forecast projections to get a back of the envelope idea of perhaps the top few thousand jobs high school students will be working in over the next decade.
  2. Then tag each job with the prerequisite classes a high school student would need to take to be on track to being prepared for that job upon exiting 12th grade.
  3. Job Skill Index: Create an index that ranks classes (existing or yet to be created) by the % chance that a high school student will utilize this information in the first 2-5 years of  her career.
  4. Core Thriving Index: Couple this an analysis with an analysis of the non-job knowledge, values, and skills that will be important in adulthood (moral living, mental health, appreciation of arts, personal finance, civic knowledge, etc.) – and tag these non-job learning objectives to high school classes.
  5. Rerun every few years.

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Potential implications:

My guess is that conducting the above exercises would lead to numerous additions to the high school curriculum (data-analysis, sales, marketing, project management, policy analysis, etc.) and the demotion of numerous classes (calculus, AP literature, advanced biology, etc.).

Additionally, it might lead to new classes, such as “sprints” – whereby students could take courses that covered the foundational concepts of a few classes (i.e., a science sprint could cover biology, chemistry, and physics in one year), which would raise the class score on the Job Skill Index and allow for student exposure to numerous fields without overcommitting to any specific field.

Duel enrollment in colleges and on-line courses could also allow for personalized specialization in the later years of high school, thereby avoiding the broad mandating of classes that score low on the index.

As a set of classes, Common Core would fair poorly as measured by the index.

Creating the index would also lead to many questions about tracking, as the probability of utilizing information will vary based on a student’s current achievement.

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The benefits of beginning with a more quantitative approach to curriculum would be numerous:

  1. It would bring clarity to why and when we teach vocational knowledge. While some might cringe at teaching sales in high school, the truth is that sales and Algebra II are both predominantly vocational skills (if anything, sales probably provides more insight into our condition than does Algebra II). If we are going to teach a vocational skill in high school, we should have a good idea why we’re doing so.
  2. It would bring clarity to the non-vocational purpose of school: By defining what adults need to thrive, and determining what of this can be taught by schools, it would help harness the high school experience to increase the probability of adult thriving.
  3. It would help us understand trade-offsEven if we decide to offer a class that will only benefit a minority students of the long-haul (and there might be good reasons for doing so), there is a difference between a class benefiting 1% of students and .001% of students. Understanding these differences would allow us to make better decisions.
  4. It would serve as an automatic trigger: Conducting this exercise every few years would force to have conversations about what should be taught. It would help prevent us from relying on hundred year old assumptions that have been mostly developed by content experts (who always overvalue their content).

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Creating and adopting these indices  via public debate and democratic adoption would slow them down immensely and subject them to political considerations.

Some will consider this a feature while others will consider it a bug that needs to be fixed.

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In case you’re curious, see here for broad labor category projections from BLS:

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