The Current Education System is Dead

I don’t think this article will tread new ground, but its an attempt at organizing my thoughts.

Observe events of the past few months. We have been forced to go from classroom lectures to online classes  – video recordings of lecturers speaking about their topics. If we have a hypothetical college in Pune with ~400 students in a batch, and therefore ~7 divisions, we suddenly realize that we do not need 7 lectures, but can do with just one. And that one lecture can be conducted by the most effective teacher. So not only is a lot of labor saved, but students get the best instruction. 

Question: Why not do this as a practice, if there are benefits all around? Why subjugate students to sub-standard teaching?

Thinking further, extend this to all colleges in Pune. Get the best teacher for each topic, and we only need one lecturer and students get the best of Pune, not just the best of their college. 

Question: What differentiator is a college providing to justify locking in students to only their offering?

And naturally, why limit ourselves to Pune? Why not get the best teacher in the entire world?


There are two additional factors to take into consideration. 

First, evaluations. How do we give feedback to students so that they understand how much they have learned, and what they need to focus on (this is should be the primary goal of evaluations)?

Second, degrees. What purpose do they serve?


This leads me to wonder why we even have colleges and universities in today’s day and age. Companies have their own criteria for evaluating applicants, and if they use college scores at all, it is as a filter (which is pretty stupid!). There are many that conduct tests online, so it doesn’t matter where you studied, but what you know (see Hackerrank for continuous iterations of this). 

So:

  • I can attend courses online, learning from the best teachers in the world. In some cases, I can learn the same subject from multiple teachers, to get different perspectives, and deepen my understanding.
  • I can engage with mentors who have the right research, academic and industry experience to guide the subjects that I focus on.
  • I can build a portfolio of projects to demonstrate my capabilities. I can contribute to world-class open source projects so that I am gain experience working in teams large and small.

Why do I need to attend college at all?

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Scaling Challenges for MOOCs

I’ve been a massive fan of MOOCs ever since they started, and have personally leveraged the opportunity to the fullest (though it did take some time to figure out how to complete a course, versus starting one!). Students get to learn from the best educators in a variety of different subjects (sometimes they (the teachers) are also from the top universities) for free or for a nominal cost. What’s not to like?

These days Universities are moving from offering individual courses, or ‘micro-master’s’ programs to offering full-fledged online Masters Degrees. These are equivalent to what one would obtain by physically attending the college (the certificate does not distinguish between online and in-person), but this also requires a lot more rigor in evaluating students who attend online, a point that I come back to below. 

I’ve seen quite a transition from a video recording of the teacher with slides/monitor on the side to attempts using Microsoft Kinect. And there’s the disconcerting trend where the instructor writes on a board facing us, but we see things the right way (I haven’t quite figured out how that is done). However, at its core, the model is unchanged: the lecturer lectures and we watch them online, rather than being physically present in the classroom. The watching is done at our convenience and pace, and we can rewind and rewatch what we want. MOOCs are making knowledge accessible, but I don’t think we’ve actually used technology to develop a new way of instruction.

I’d like to focus on a few aspects of scale — the ‘Massive’ part of MOOCs. How do these courses deal with the sheer number of students enrolled, and how do they impart the best possible instruction?

The first, obvious, observation is that there are numerous platforms available (edX, Coursera, Udemy, etc.) that take care of the bureaucratic stuff: accounts, logins, billing, tracking, etc.) and the technology (videos, tests, etc.), so these don’t have to be redeveloped for each course. And yes, there are no scaling limits here. 

The second aspect of scale is that of content delivery. Lectures are recorded and available at all times. We don’t need to have all students in the same location (or online) at the same time. Since the model is different from a physical classroom, the limitations of a physical classroom are dealt away with. This is a solved problem.

The third aspect of scale is where things get interesting, and is that of student evaluation. The original MOOCs (and I suspect, most of the current generation) used to limit themselves to quizzes that consisted of multiple-choice questions. Some were embedded in the videos. These are, of course, easy to grade automatically. Others allow text boxes to enter (numerical) values, and sometimes $\LaTeX$ formatted answers, but these take a bit of getting used to. I have also seen some that require essay-type answers, these are peer evaluation, which I thought was a good way to address the problems of scale, but this seems to have gone down – a failed experiment, perhaps?

Back to the degree-granting MOOCs (can I call them that?): they decided the only way of evaluating students was the traditional way of evaluating students, namely, have them write an exam they way they normally would. So…

students turn on their webcams, rotate them around the room to prove that there is nobody around helping them, and keep these on and focused on them for the duration of the test. I believe the microphone is kept on as well. And there is a person on the other end of the connection keeping an eye on the student! Holy 19th-century non-scalable solutions, Batman!!!

This is a great opportunity for an unskilled proctor who otherwise would not have gainful employment. I have no idea how much they make, and what trauma they go through, having to spend their waking hours watching students bent over exam books.

The final aspect of scaling is that when we have essay-type questions (say, ‘develop an algorithm to do x’), a human grader is going through these and assigning scores. Even if we overload a poor TA with 100 exams, the larger the course, the correspondingly larger staff needed to manage just the grading. 

I think we’ve been going about this the wrong way. We’ve been trying to replicate what we do offline to the online world, which leads to issues like the above. How might we look at this from a fresh perspective? Glad you asked!

  • Goal: Provide feedback to the student on which areas they are doing well and areas for improvement. This is (or should be) the only reason to conduct exams, but that is fodder for another article. A secondary goal is to provide a normalized score that accurately captures the student’s capabilities in the subject. Ultimately, we would like to measure how much a student has learnt.
  • The means of measurement have to be scalable. It should work across thousands or tens of thousands of students. 
  • It should not be possible (too restrictive? Maybe it should be very difficult) to game the measurement

We can think about how technology can solve these issues once we have clarity on what we are trying to solve!

Thoughts?

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Little Things

Student activities: Operate a slot machine using your eyes

This is cool and fun and took just a few days to do. BUT this could be done by using other interfaces – mouse, keyboard, sound(?), etc. What would be a good use of eye-tracking or blinking that would not be possible with existing interfaces?

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Learning by Explaining

It’s incredibly useful to have students work with a partner, rather than doing exercises alone. They start discussing approaches and ideas and have to explain their thinking to each other. This forces them to consider whether their approach is valid, and the act of talking about what they are thinking deepens their understanding as well. Bouncing ideas off of each other leads to further ideas, that would not have come about.

The most fun sessions are when the room is noisy with conversations between pairs of students, conversations across the entire class, students taking hints from each other, offering solutions to solving particularly knotty problems and egging each other on. And most times, we end up with solutions very different from what I had come up with — which is brilliant!

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Learning from mistakes

[Inspired by Dennett’s Intuition Pumps]

My current approach and where I’d like to be works 1:1 or in a small group, much more difficult to do in a lecture-style setting.

When I’m trying to teach a new concept – programming, algorithm, mathematics – I try to give students a bit of structure and context and get them to develop the solution. The amount of structure and context varies from student to student, and its not easy getting it right. Done well, students reach that aha! moment on their own. I’ve been doing this unconsciously for quite a while, but its probably time to do this with more structure (hah!).

One more aspect I would like to add is having students reflect on failed approaches. This may also require reducing the context and allowing them to try out a variety of approaches.  A lot of learning can happen in this analysis. The downside is that it needs time and it needs willingness to expend the effort.

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