The Brave New (Wired) World of Online Education

For all our modern advances, the jury is still out regarding the most effective ways to teach online.

It is a brave new world, indeed, in which milk, cars, and spouses can all be acquired via the Internet. But for all our advances, the jury is still out regarding the most effective ways to teach online.

Many online learning platforms consist of passive video lectures and podcasts, or universities repackaging classes for the web. To illustrate, imagine you have students who have never seen a pizza before and want to learn how to make one. Working with current online teaching methods, they’d likely not throw the dough, choose the toppings, or get feedback on their work. They would probably have to sit quietly through written descriptions and video lectures online.

The prevalence of this passive approach demonstrates a key challenge in the pursuit of engaging, effective web-based education: the issue of interactivity. While more studies are showing that interactivity breeds engagement and information retention, instructors and platforms are still struggling to employ effective levels and modes of interactivity.

Researchers at Columbia University’s Community College Research Center examined 23 entry-level online courses at two separate community colleges and made some interesting discoveries on this phenomenon. Their assessment was that most of the course material was “text-heavy” and that it “generally consisted of readings and lecture notes. Few courses incorporated auditory or visual stimuli and well-designed instructional software.” While technology that supported feelings of interpersonal interaction was found to be helpful, mere incorporation of technology was insufficient—and recognized as such by the students. The research noted that, “Simply incorporating technology into a course does not necessarily improve interpersonal connections or student learning outcomes.”

The research specifically called out message boards (where instructor presence and guidance was minimal) to be insufficiently interactive to engage students in a way that they found clear and useful. The consensus of their research was that “effective integration of interactive technologies is difficult to achieve, and as a result, few online courses use technology to its fullest potential.”

Another interesting look at web-based learning and interactivity is a 2013 study conducted by Dr. Kenneth J. Longmuir of UC Irvine. Motivated by the fact that most “computerized resources for medical education are passive learning activities,” Professor Longmuir created his own online modules designed for iPad (and other mobile devices). These three online modules replaced three of his classroom lectures on acid-base physiology for first-year medical students. Using a Department of Defense handbook as his guide for incorporating different levels of activity, Longmuir utilized text and images side-by-side and had an embedded question and answer format. From student comments, “The most frequent statement was that students appreciated the interactive nature of the online instruction.” In fact, 97% of surveyed students said it improved the learning experience. They reported that not only did the online material take a shorter time to master than in-person lectures, but the interactivity of the modules was the “most important aspect of the presentation.”

While Dr. Longmuir was reluctant to draw hard conclusions about this particular online course’s efficacy (due to variables in student procrastination, students skipping important material, etc.), there are a few clear points to be taken from both studies. For one, engaging, interactive content is the exception, not the rule, in today’s online learning environment. Both studies suggest the importance of interactivity in online learning—if not definitively in test results (though that’s a possibility), certainly in how students feel about their engagement with the material. This isn’t surprising since research is showing that lack of interactivity in traditional classrooms is detrimental, as well.

While the science behind producing effective online learning courses is still in development, the need for meaningful interactivity in new educational technology seems like a no-brainer. If we hope to teach our students to make that pizza, the most effective way is not to drown them in video clips and PDF files; we should create online learning experiences that mimic—or even improve upon—the interactivity and satisfaction that pounding the dough themselves would provide.

 

Learning Game Trees and Forgetting Wrong Paths

This is the second of two blog posts delineating the pedagogical approach of Herb Simon, the man credited with inventing the field of artificial intelligence, for which he won a Turing award in 1975. (Read the first post here.) Simon was a polyglot social scientist, computer scientist and economics professor at Carnegie Mellon University, He later won the Nobel Prize in 1978 in economics for his work in organizational decision-making.

Game Tree
Tic Tac Toe Game Tree, Gdr from Wikimedia Commons

Dr Simon would often tell his students that he liked to think about human learning as a game tree: when you start out learning about a new topic, you begin at the root of the tree with what you already know, and follow connections to related topics, discovering new “nodes” in the tree. You employ a variety of search strategies to follow connections both broadly and deeply through related topics, loading as much of the explorable tree into memory as possible. As you discover and master each “node” on the tree, you learn which branches of the tree are fruitful and which are fruitless.

During and after exploration though, the entire game tree remains in your working memory, slowing you down. When you take breaks, not only are you relaxing, but you are also forgetting wrong paths – pruning those fruitless branches from your working memory. When you next return to the task at hand, you resume exploring connections and mastering concepts not at the very top of the tree, but in the most fruitful subtrees where you left off, making better use of your working memory.

At Pedago, we believe in learning by doing, and we want to break complex topics and concepts down into what Seymour Papert in the book Mindstorms calls “mind-sized bites.” One of the benefits of breaking complicated topics into “bites” is that it is easier to build learning content that learners can work through when they only have a few minutes free, on whatever device they have on hand.

As we build our database of short concepts and lessons, we find ourselves also building a rich tree structure of topic relation metadata that in structure is not unlike Simon’s game tree of learning. A nice side-effect of a learning solution with rich, encapsulated, short lessons is that you don’t have to commit to a thirty minute video – you can learn in bits and pieces throughout your day. And by doing this, you are unintentionally building and then pruning your learning game tree in an efficient way, forgetting wrong paths and making the best use of your working memory each time you return to your lessons.

 

Herb Simon on Learning and Satisficing

This is the first of two posts delineating the pedagogical approach of Herb Simon, credited with inventing the field of AI, for which he won a Turing award in 1975.

This is the first of two blog posts delineating the pedagogical approach of Herb Simon, the man credited with inventing the field of artificial intelligence, for which he won a Turing award in 1975. Simon was a polyglot social scientist, computer scientist and economics professor at Carnegie Mellon University. He later won the Nobel Prize in 1978 in economics for his work in organizational decision-making.

Herbert Simon in front of blackboard
Herbert Simon, Pittsburg Post Gazette Archives

“Learning results from what the student does and thinks and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn.” –Herb Simon

Among his many accomplishments, Herb Simon was a pioneer in the field of adaptive production systems. He also identified the decision-making strategy “satisficing,” which describes the goal of finding a solution that is “good enough” and which meets an acceptability threshold, as opposed to “optimizing,” which aims to find an ideal solution.

Simon believed that human beings lack the cognitive resources to optimize, and are usually operating under imperfect information or inaccurate probabilities of outcomes. In both computer algorithm optimization and human decision-making, satisficing can save significant resources, as the cost of collecting the additional information needed to make the optimal decision can often exceed the total benefit of the current decision.

We live in a world where overwhelming amounts of information are at our very fingertips. Every month new educational software offerings are on the market. You can find tutorials to fix anything in your house, learn a new language for free, find lessons that teach you to dance, and watch video lectures from top universities in the topics of your choice.

I like to think of myself as a polyglot learner: I would love nothing better than to just take a year, or two, or ten, and learn as much as I can about everything. But unfortunately, I have limited time. How do I know which tutorials, lessons, and classes are worth the commitment of my time? How can I find a satisficing solution to the problem of becoming a more well-rounded learner and human being?

In Simon’s words, “information is not the scarce resource; what is scarce is the time for us humans to attend to it.” At Pedago we’ve been inspired by thinkers such as Simon to build a learning solution that makes the most of the scarce resource of your time, by employing curated streams of bite-sized lessons; rich, explorable connections between topics; interactive learn-by-doing experiences; and just the right amount of gamification. We want to enable you to craft your own learning experience, so that you can, as Simon would say, positively influence what you do and what you think.

Stay tuned for the second post in this series as we examine Simon’s modeling of human learning.

 

Tinkering Toward Learning

Given how useful the tinkering approach is for keeping learners motivated, how do we apply a similar approach to a subject like Finance?

man holding bicycle
By Artaxerxes (Own work) [CC-BY-SA-3.0], via Wikimedia Commons
My friend Alfredo builds bikes as a hobby. He started by replacing a broken chain on his own bike. Then he upgraded his brakes. After a few more repairs, he understood the whole bike system well enough that he could gather all the parts and build one from scratch.

Experienced programmers generally learn new languages in a similar way. We get assigned to a new project for which there is an existing codebase that needs to be maintained or extended. Everything is mostly working, but something needs to be tweaked or added. So we tweak it. After working on five or ten features, we know the new language well enough that we could start a new project ourselves.

In more traditional educational environments, however, we tend to learn things the other way around. We start with simple, contrived building blocks and slowly work our way up to the point where we can comfortably manipulate a more complex and realistic system.

For example, a course that teaches the principle of the “Time Value of Money” is likely to start with a question like “if someone offered you $90 today or $100 a year from now, which one would you take?” This is, to say the least, an unrealistic scenario. But it is an introduction into the concept. After working through a number of similar examples in order to allow the student to master the math, the course will hopefully move on to a more reasonable explanation of how this concept is used in practice.

By Anna reg (Own work) [GFDL or CC-BY-SA-3.0-at], via Wikimedia Commons
By Anna reg (Own work) [GFDL or CC-BY-SA-3.0-at], via Wikimedia Commons
Not that it was a bad course. I actually quite liked it. But this would be like if Alfredo had first worked on pedals, then wheels, then built himself a unicycle before moving on to gears and brakes. It would have been years before he had anything he could ride on. Knowing Alfredo, he would have had no hope of staying motivated for such a long time with no bike to show for it.

Given how useful the tinkering approach is for keeping learners motivated, how do we apply a similar approach to Finance? It turns out this is difficult to do because it often involves risking real money and waiting years to see any results. What a learner really needs is a safe environment to develop intuition around the long-term consequences of her decisions and to discover for herself the places where she needs to dig deeper.

At Pedago, developing alternative approaches to teaching tough topics is what we’re passionate about. Stay tuned over the coming months to see us tackle similar problems.

 

This post has been updated to include a clearer example. Thanks to Earthling for the feedback!

Teaching with Time-Lapse

How do you convince a skeptic that climate change is real? The documentary Chasing Ice takes on this challenge to awe-inspiring effect.

How do you convince a skeptic that climate change is real? The documentary Chasing Ice takes on this challenge to awe-inspiring effect.

There’s no obvious connection between the melting of glaciers and online learning, so you might be wondering why this would be relevant to Pedago, an educational technology company. But bear with me.

The hero of the film, James Balog, turned to photography after finishing his master’s degree in Geology because he felt science was becoming too focused on numbers and statistics for him to enjoy. He believed he could make a greater impact through documenting Nature rather than dissecting it.

Thus, when faced with his own dawning realization that climate change was real, and human-influenced, he understood that facts, statistics, and lectures were ill-suited to sway the minds of a disbelieving public. He explored how best to use the tools of his trade–camera and ice axe–to make a difference.

His solution embodies the writer’s maxim to show and not tell. For three years, he and his team captured time-lapse images from Iceland, Alaska, Greenland, and Montana, then stitched them together. The resulting videos provide indisputable evidence that glaciers are receding ever more quickly. They are at once alarming, awesome, and visceral–attributes the standard “facts-and-graphs” discussions of climate change typically lack.

After watching this documentary, it really struck me that Balog was able to transform the conversation around a topic that is so frequently debated in the public space. Global warming is disputed more in American popular media than by scientists, its facts often treated as fictions promoted by activists. It’s difficult to convince people who are determined not to be convinced, even with the dramatic (but indirect) evidence of recent natural disasters. What can we learn from Balog’s feat?

I believe the key lesson is artful choice of data representation. The time-lapse images Balog’s team produced form physical evidence that is easily consumed. The viewer can wrap her mind around them, consider them as evidence, believe them or not with her own eyes. If the best way to understand the effects of global warming is to travel to a glacier and watch it calve icebergs or shrink into itself season after season, then bringing the key moments of this experience to a wider audience is certain to make a greater impact than presenting yet another statistic. A time lapse is worth a thousand graphs.

Balog’s accomplishment serves as a reminder to educators of the power in choosing novel representations for the material being presented. At the intersection of art, science, and technology, there is the potential for greater educational impact.

See the Chasing Ice trailer here: