An Adaptive Learning Model for K12

20 May

My wife and I have been planning to launch a technology-centric non-profit organization to serve the underprivileged kids in poor schools in India. Much research and analysis needs to be done, and it’s going to take us a few years to get everything right. Fundraising, needed to purchase hardware, would take a lot of time too. However, the software, which would be an online product utilizing an adaptive learning model, can be launched sooner, so that we can iterate rapidly and keep improving it.

On a very basic level, for third-grade math, here are the requirements.

Database
A database of math questions with these fields:

  • Question ID
  • Difficulty level
  • Question number
  • Options
  • Correct option
  • Feedback

Adaptive algorithm

  • A multiple-choice question with four options is served.
  • When an option is selected and submitted, the option is compared with the correct option.
  • If correct, the corresponding feedback is displayed.
  • if incorrect, the corresponding feedback is displayed.
  • When the Continue button is clicked, the system checks if the question was answered correctly.
  • If true, another question at the same difficulty level is served to make sure the previous answer was not a fluke.
  • A total of three questions at the same difficulty level is served.
  • If all are answered correctly, the next question would be at a higher difficulty level.
  • If any question is answered incorrectly, more questions at the same difficulty level will be served.
  • If two or more questions are answered incorrectly in succession, a brief tutorial will be displayed showing how to solve the question.
  • The tutorial will be followed by a question at the same difficulty level.

Though there are multiple interpretations of “Adaptive Learning“, I interpret it as a learning model that adapts or shows content based on the users’ current performance. It’s not a one-size-fits-all product, which are common these days though the technology has made rapid advancements. Great content and a great algorithm can be integrated with the right hardware to teach the kids effectively. It’ll take time but I think it’s doable.

A Technology-Centric Non-Profit Organization

14 May

Learning is hard. For most people. Because most of us are average learners.

Learning is hard also because the teachers in schools are not well trained, the classroom size is large, the socio-economic status of some students is low, there are not enough resources in the classrooms, and/or the students don’t expend enough time and effort outside the classroom.

In developing countries like India, there are thousands of schools that suffer from these problems. Surviving on minuscule government funds and poor management, these schools fail to teach their students effectively.

Classroom - India

Classroom in India

A technology-centric non-profit organization
There are many non-profit organizations in India and the US that serve the underprivileged kids. They are focused on training teachers and arranging for resources. Is it possible to build and implement a technology-based learning product for such schools when these schools lack even basic computers?

This is a question my wife and I have set out to find answer to. A few years ago, we’d decided to found our own education-focused non-profit organization to help poor schools teach their kids. This model requires two things:

Software/Learning product: The learning product can use an adaptive model to help the kids learn by creating a personalized learning path.

Hardware: I envision two options.

  1. Cheap 10″ tablets embedded in the desks to prevent mobility and potential damage. This model can be used in the classroom under the teacher’s supervision.
  2. Large touchscreens in kiosk-style stations. This model can be used outside the classroom in common areas to foster group learning and collaboration.

In the next post, I’ll elaborate on my adaptive learning model.

Related:
An Adaptive Learning Model for K12

Forecast, Don’t Predict

8 May

Predict: to declare or tell in advance; prophesy; foretell

In short, a prediction is looking in a crystal ball and is based on one’s knowledge and gut feeling. We all think we are very knowledgeable and can predict the future, and we all know how things turn out. Exactly the opposite.

Crystal Ball

Crystal Ball

A few examples

Apple: A prominent VC, Fred Wilson, recently predicted that Apple won’t figure among the top three companies by 2020 while Google and Facebook will. His logic is based on his knowledge of the hardware industry. We have to wait six years to see how true this prediction is.

The Beatles: “The Beatles have no future in show business.” — A Decca Records executive to the band’s manager, Brian Epstein in 1962

Harry Potter: “Children just aren’t interested in witches and wizards anymore.” — A publishing executive writing to J.K Rowling, 1996

iPhone: “There’s no chance that the iPhone is going to get any significant market share. No chance.” — Microsoft CEO Steve Ballmer, 2007

Computers: “I think there is a world market for maybe five computers.” — Thomas Watson, chairman of IBM, 1943

Personal computers: “There is no reason anyone would want a computer in their home.” — Ken Olson, president, chairman and founder of Digital Equipment Corp., 1977

Invention: “Everything that can be invented has been invented.” — Charles H. Duell, Commissioner, U.S. Office of Patents, 1899

Computer memory: “640K ought to be enough for anybody.” — Bill Gates, 1981


Forecast: to
predict (a future condition or occurrence); calculate in advance

On the other hand, a forecast is based on cold, hard data. Removed from gut feeling or one’s own knowledge or emotion, a forecast takes lots of data and extrapolates from it. Could a forecast be wrong? Yes, it’s possible. However, a forecast always comes with a probability, the chance of something happening. While a prediction carries with it a heavy load of 100% probability, a forecast can be 0% or 100% or any figure in between.

Nate Silver, the founder of FiveThirtyEight.com and the guru of statistical forecasting, has risen to be the most prominent figure in this field, especially after the 2012 presidential elections when many people and polls predicted a Mitt Romney victory. Nate Silver took the data from many polls, ran them through his forecasting analysis, and said that there was a 90% chance of Obama’s victory. His forecast of all 50 states came true. Not all of his forecasts for this year’s Academy awards were true, but at least, he didn’t make a fool of himself like so many famous people.

Suggested readings:
25 Famous Predictions That Were Proven To Be Horribly Wrong
15 famous predictions that were spectacularly wrong

Don’t Fool Yourself …, Or Why Evaluation Is Important

7 Apr

In 2006, when I was attending Stanford University School of Education for my master’s degree, we were working on our master’s project. One of our professors, who is an expert on evaluation, came to our class to discuss evaluation of our projects. He started by saying:

“Don’t fool yourself into believing that you are developing a great product.”

It was a shocker for us as we all completely believed that we were indeed on our way to developing great products. My project was intended to make it easy for school children to view 3D animations on 3D monitors on concepts that were difficult to visualize in 2D, for example, the rotations and revolutions of planets and the atomic structure of molecules. It was the greatest idea of all time. Why did I need to conduct an evaluation for such a simple, yet powerful concept?

We learned a lot that day, especially not overestimating the usefulness and effectiveness of our ideas. Unfortunately, we didn’t have much time to evaluate our projects so we completed our program and set out, starry-eyed. to change the world.

However, people in real world who develop products and services don’t always care about the users of those products and services. They come up with innovative ideas (or so they think), and start working on the ideas with the premise that they are developing great products. Case in point: Windows 8, iTunes Ping, Google Plus. They ask the users what they think about those ideas, and, thanks to confirmation bias, come back with user feedback that confirm the greatness of their ideas.

They fool themselves into believing that they are developing a great product. They don’t want to look at the analytics because that would disprove their hypothesis. And I have been as guilty of this crime as anyone else.

The right way: Startup companies

Startup companies too start with the premise that they are working on the world’s greatest idea. And they are right. If they don’t think that way, they wouldn’t risk everything to work on that idea. They spend years developing, launching, evaluating, and iterating on their idea. Their best friend? Usage analytics, which gives them insights into how many people are using their products, where, and when. How many people are visiting what parts of the product more? What macro-level trends are visible? Does making a minor change in a color shade increase or decrease the usage of a page or a field?

More than 90% of startup companies die within two years of launching because of several reasons. But they all know how useful and effective their products are (or not) thanks to analytics data. Analytics do not always save an idea but they help fail early, fail fast, fail often, and help people learn and move on. They can fool themselves but not for long. And that’s why evaluation is critical to developing great products.

There’s Something About Print Books

7 Mar

In the middle of the fifteen century, the fist major book – Gutenberg Bible – was printed. With the advent of the printing presses, an advancement in printing technologies and chemicals, and the dawn of the industrial revolution, the print books proliferated. Later, some predicted that the Internet was going to kill books, but the number of books published is increasing every year. However, the sale of print books is in decline, mainly because more and more people are reading books on their electronic devices, mostly tablets, e-readers, and smartphones.

Books

The current generation
The current generation, the so called Digital Natives, are considered to be extremely tech-savvy. They are supposed to own all kinds of electronic devices and live their life in a digital world. The printed paper should be anathema to them. We don’t expect them to use printed books.

So what’s the reality? It’s totally different!

I’ve spoken with more than 5o undergraduate students taking business courses in the past few months. The first thing they do when classes start is buy a print book, either a new book, a used book, or a rented one. Many of them are aware of the existence of ebooks, but they all prefer print books. Cost is a factor but not for everyone. I wonder what’s going on?

I asked some students why they prefer print books and got some vague answers. I’ve even asked myself why I prefer print books. I like the touch of the book, I like to display them on my bookshelf, it’s romantic, it’s nostalgic, but I haven’t been able to come up with a better answer. Do we prefer print books because we have used a print book most of our lives? Is it just a habit that’s difficult to break? People break old habits if something compelling enters their lives. Does it mean the current ebooks are not compelling enough?

Some theories
Humans have evolved to be responsive to visual and tactile signals as these traits helped them survive in the wild for thousands of years. Books are tangible things, ebooks are not. Flipping the pages in a physical book is easy and visual/spatial. Research shows that it’s easy to retain information when using a print book versus an ebook. Reading a print book is faster than reading on a screen. Taking notes and highlighting is easier with a print book. There is no battery to charge, no worries of damaging it. The ebooks are mostly a replica of print books.

Some people say that the next generation who are growing up using digital devices since childhood will be more inclined to use ebooks. However, the schools still use mostly paper books and homework though the tests are computer-based and kids use some ebooks and digital learning tools. It might take another 15-20 years before college students use only ebooks.

There must be something about print books.

Related readings
Why Printed Books Will Never Die
E-Reading Rises as Device Ownership Jumps

When The Buck Doesn’t Stop

7 Feb

This week, Satya Nadella was picked to be the next CEO of Microsoft to succeed Steve Ballmer. Being a fellow Indian, I’m happy for him. However, an MBA replacing another MBA is not an appealing idea to me.

Steve Ballmer has been criticized for missing the search (Google) and mobile (Apple) revolutions. Microsoft’s stock price has been stagnant for a decade. The tech media has been pronouncing MS dead for years now, while MS keeps posting bigger and bigger revenues and profits, quarter after quarter.

Was Steve Ballmer a bad CEO? I don’t think so. He was brought in by Bill Gates to increase the revenues and profits of a public company, which he did quite spectacularly. But he is not a product or design guy like Steve Jobs. He didn’t have vision, but he had strategy. He was not innovative, but he knew how to make money.

When nobody questions why the design of a product sucks, when there are too many cooks in the kitchen, you get Windows 8. Surprisingly, MS got it incredibly right with Windows phone, but Windows 8 has an equally confusing design.

Will Satya Nadella be a numbers and strategy guy or a design and innovation guy? We’ll see soon. When there is nobody at the top with design sensibilities who can question the design of a product, the product usually sucks. In every industry, category, and market. Because the buck doesn’t stop with anyone.

Related Readings
Why Designers Leave

The Revolution That Wasn’t: Part 2

28 Jan

I recently read some comments about MOOCs.

Doubts About MOOCs Continue to Rise, Survey Finds: Babson Survey Research Group, Pearson and the Sloan Consortium

The findings, released in a report on Wednesday, reveal a growing skepticism among academic leaders about the promise of MOOCs. The report also suggests that conventional, tuition-based online education is still growing, although not as swiftly as in past years.

The article – Top Issues Facing Higher Education In 2014 on Forbes.com, ends with:

You may observe a notable omission from this list: MOOCs. Increasing awareness of their limitations for certain audiences combined with a feeling of “enough already” will make these yesterday’s news in 2014.

The pioneer of MOOCs, Stanford Professor and founder of Udacity, predicted in 2012:

In 50 years, there will be only 10 institutions in the world delivering higher education and Udacity has a shot at being one of them.

Recently, however, he changed his opinion of MOOCs:

“I’d aspired to give people a profound education–to teach them something substantial. But the data was at odds with this idea.”
“We were on the front pages of newspapers and magazines, and at the same time, I was realizing, we don’t educate people as others wished, or as I wished. We have a lousy product. (emphasis mine)”

I have taken a few MOOC courses on Udacity, Coursera, Stanford Venture Labs, and NovoEd. I’m enrolled in one or two courses all the time, which I complete at my own pace. I believe it’s a great but overhyped idea, and MOOCs are not a replacement for traditional students and universities.

Meanwhile, I stand by my take on MOOCs two years ago – Are MOOCs A Disruptive Innovation?

Suggested Readings:

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