In which economists know nothing about teaching and probably less about learning

This is a rant so I thought I’d blow off steam here instead of being rude on MR:

In an online lecture it pays to be concise. Online, the student is in control and can choose when and what to repeat. The result is a big time-savings as students proceed as fast as their capabilities can take them, repeating only what they need to further their individual understanding.

If I’m not making much sense the first time I say it, no matter how many times someone plays back the same incomprehensible words it’s still NOT going to make much sense. It’s the same idea as reading the same incomprehensible passage over and over again. Can’t you get it into your thick skull?

I’m swamped in coursework with Coursera right now (but enjoying it). There is huge IF in online education in general which goes something like this: Assuming that teaching at the college level at its current approach (which is mainly “chalk and talk”) then all educators need to do is bring the in-classroom experience online.

The big IF is the assumption that college level teaching is at its optimum or its current best and many (not all) online courses seem to assume that all the professors have to do is make a video of them standing in front of a blackboard (or a projector screen) available and all is well in the world. There is very little difference between this approach and just having power point slides with a voice behind it. If I don’t get something 5 minutes into the lecture, playing it back 100 times isn’t going to do much good.

Here we go again

Gretchen Rubin ponders the arrival of Hurricane Sandy. Meanwhile this constant flow of tweets and updates is just making me more anxious than it probably would if I just ignored it. After all, we can only sit at home and wait for the inevitable power outage that will come.

From the radar, Sandy looks impressive. (Picture from CWG.)

The state of apple

Finally broke down and got an Apple computer. In order to receive updates I had to create an Apple ID. Okay. But … in order to do this I had to give them a credit card number???

Okay … I guess this is what Apple has come to - besides being a pussy and and a wussy it is trying to extract as much money as it can by coming out with incremental improvements in products that are about as imaginative as innovations in shaving blades.

I remember when it used to be single blades, and then double, and then wow! triple! and then … and so forth.

The iPad and iPhone was an innovative interface just as the shaving blade was an innovation at the time. The incremental improvements that have come from Apple is just as predictable - bigger brighter screen, smaller version - what next? A set of wet wipes attached?

When we censor ourselves what does it say about us?

I was looking forward to getting Enid Blyton’s Famous Five series for the kids. I had enjoyed them when I was in the pre-teen/early teen years. Here are some comments I found when I looked them up on Amazon:

By Titan

This book is not Enid Blyton's original text but an edited version. It is an outrage that this is not made more clear. If I want to read Enid Blyton, I want to read the original words, not a doctored 'modern' version. Apparently the original (first folio) version is still available so you might want to look for that instead of buying this one. I would give the original version 5 stars, incidentally. I loved the Famous Five books as a child.

By Tatyana A Privalova

Chapter one, this edition: She wants a good talking to.

Chapter one, older editions: She wants a good spanking.

Enough said.

By emma_e_brown

Like the last reviewer I am thoroughly disgusted that the publishers have "updated" the text. I was looking forward to a big nostalgia trip, but no lashings of ginger beer here by jove! This is hardly replacing a racially offensive toy with naughty teddies and I see no reason whatsoever for butchering these classic stories. What next - The Lion, The With, and the Ipod?!! Surely contemporary children are just as capable of appreciating a period story as we were?

These reviewers gave the book one star because of the edits. I’m not sure I’d go that far. I had noticed this ‘politically correct edits’ when the kids were younger. In Curious George Goes Fishing, the current edition has George seeing a large man go by. In an older edition of Curious George Flies a Kite (which we got as a hand me down) from which Goes Fishing was excerpted, it was a fat man.

What is the message that we are trying to send? That we don’t want to mislabel someone? Or is it that we don’t want the kids to think badly of us -- that we used to call people fat, that we used to spank? When kids grow up as they all inevitably do, they’ll know what fat and spank are - so what did we achieve by withholding these ‘truths’ from them?

Data scientist(?)

One of the apparently ‘hot’ jobs these days is the data scientist. So hot in fact that the Harvard Business Review has named it the sexiest job of the 21st century. I came across Rachel Schutt’s Data Science class at Columbia (HT: Andrew Gelman) and she has a description of what a data scientists does (or should do):

What is a Data Scientist?

Let me start with academia because that’s quicker. Then industry.

In Academia: No one calls themselves a Data Scientist yet in universities. There are 60 students in my class from across disciplines. I thought when I proposed the course it would be statisticians, applied mathematicians and computer scientists who showed up. Actually it’s them plus sociologists, journalists, political scientists, biomedical informatics students, students from NYC government agencies and non-profits related to social welfare, someone from the architecture school, environmental engineering, pure mathematicians, business marketing students, and students who already work as data scientists. Am I missing someone? They’re all interested in figuring out ways to solve important problems, often of social value, with data.

For the term Data Science to catch on in academia at the level of the faculty, the research area needs to be more formally defined. I see a rich set of problems that could be many PhD theses. My current working definition is a Data Scientist in this setting is a Scientist (from social scientists to biologists) who work with large amounts of data, and must grapple with computational problems posed by the structure, size, messiness and nature of the data, while simultaneously solving a real world problem. Across academic disciplines, the computational and deep data problems are the same. So if researchers across departments join forces, they can solve multiple real-world problems from different domains.

In Industry:

It depends on the level of seniority and whether you’re talking about the internet industry in particular. The role of data scientist need not be exclusive to the tech world, but that’s where the term originated so for the purposes of the conversation, let me say what it means there:

A Chief Data Scientist should be setting the data strategy of the company which involves a variety of things: setting everything up from the engineering and infrastructure for collecting data and logging, to privacy concerns; deciding what data will be user-facing, how data is going to be used to make decisions, and how it’s going to be built back into the product. She should manage a team of engineers, scientists and analysts and she should communicate with leadership across the company including the CEO, CTO and product leadership. She’ll also be concerned with patenting innovative solutions, and setting research goals.

More generally, a data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human. She spends a lot of time in the process of collecting, cleaning and munging data, because data is never clean. This process requires persistence, statistics and software engineering skills– skills that are also  necessary for understanding biases in the data, and for debugging logging. Once she gets the data into shape, a crucial part is exploratory data analysis which combines visualization and data sense. She’ll find patterns, build models and algorithms, some with the intention of understanding product usage and the overall health of the product, and others serve as prototypes that ultimately get baked back into the product. She may design experiments, and is a critical part of data-driven decision making. She’ll communicate with team members, engineers, and leadership in clear language and using data visualizations so that even if her colleagues are not immersed in the data themselves, they will understand the implications.

Looking at the syllabus it sure sounds a lot like data mining. I guess being a scientist beats being a miner.

I’d like to share something with you

But you have to pay for it.
Am I the only one who thinks that this is ironic?

P.S. By the time I read MR's post on the book, the price had risen from $3.99 to $4.99.

Grades, quizzes, homework and Coursera

As I sit through some of the quizzes, homeworks and tests at Coursera I am reminded about why these things suck so bad. It sucks even though there is very little at stake (for me - except probably pride!) and undermines all incentive to learn. I'll bet that this wasn't what on-line educators had in mind when they launched.

There are several ways that assignments and quizzes are graded and these are applied in different combinations listed below:

1. Multiple attempts are allowed, with hard deadlines and soft deadlines with penalty after the hard deadline has passed
2. Only one attempt is allowed
3. Feedback on a question-by-question basis explaining what was right and what was wrong
4. No feedback at all - just a total score - not even an accounting of which question is right or wrong.
5. Time limits are imposed (or not)

So (1) could be combined with (4), (2) with (3) and so forth. These are just from the courses that I’ve been in so peer grading is excluded and since there are no writing assignments I can’t comment on those. At this point, I'll just say that #4 really sucks! #3 is great although when it is combined with #1, the student already has the answer since the questions do not change. So in a way this sucks too.

The question that really needs to be asked is whether grades really reveal anything and reasonably minded people will have different opinions on this. What does an A reveal? What if the whole class got As? Does it make a difference? As the discussion in the embedded link points out, grades reveal as much as they can if there is a point of reference. By itself, my sense is that it is meaningless.

Again, Khan Academy is moving ahead of the curve on this front. The two relevant concepts are achievement of proficiency (either full, average or below average would be a starting delineation though Khan isn’t doing this just yet) and adaptive testing. In other words, achievement of proficiency via adaptive testing. Students learn through quizzes, tests, and exams. If they get it wrong an algorithm defaults to an easier question and steps the student back up to the harder question - either presented again or in a different form or even both.

If there is anything to be taken away from this approach is the following: grades do not penalize learning. As it stands now, grades are more of a penalty than a reward or an incentive. If there are two relevant measures that can be used to gauge a student it is these: persistence and length of time to achieve some proficiency level. These two measure reveal more than the grade itself. A student may have worked hard for an A while another one breezes through the class. A potential employer looking at an A cannot tell if the first person is a hard worker or someone just doing well because they are smart but with no work ethic.

Coursera can implement this type of approach to learning. It does encroach into the testing field where companies like ETS and Pearson may start feeling the heat and it isn’t clear if this is something that Coursera will want to get into (depending on the VCs). Unfortunately, Coursera is far away from implementing this approach although I believe the technology and the architecture are already in place. 

The  same problem that plagues teaching at the college level in the bricks and mortar setting carry over into the online setting. Adaptive testing needs a really large test bank and professors really loathe to do this since research is what they are more interested in. Perhaps it can be assigned to real teachers as opposed to professors and by this I mean the teaching assistants and those not under the publish or perish system. It could even be open or crowd sourced. And perhaps more importantly it forces teachers to think about proficiency in certain concepts - not just the course itself. In order for adaptive testing to work well the concept has the well defined so that the software can step back and present another relevant question. It is easier at Khan Academy since they focus on basic skills but much much harder at the college level.

It would make learning a little bit more fun and take away the feeling that getting a question wrong on a quiz is a penalty.