Posts tagged ‘learning sciences’

How do we create cyberattack defenders?

 

Roger Schank (famous AI and cognitive science researcher, the guy who coined the term “learning sciences”) is putting his expertise to the task of creating cyberattack defenders.  The description of his process (linked below) is interesting.  It has all the hallmarks of his work — innovative, informed by research, driven by concrete tasks.  Notice the strong claim that I quoted below.  We shouldn’t be aiming for general cyber attack defense skills.  These skills are going to be industry-by-industry specific.  He’s directly informed by the research that suggests that these skills are unlikely to generalize.

One of the big questions is: where are we going to get the students?  How do we recruit students into this kind of program?

How can we help? The cyber attack course Socratic Arts is building for the DOD will be modified to make the projects specific to particular industries. The banks’ problems are obvious: hackers might want to steal money. Pharma’s problems are obvious: hackers might want to steal secrets. We intend to put out versions of our cyber attack course for each industry. These courses will take 6 months for a student to complete. We are not interested in giving an overview in the typical one week course that is no more than an intro. We want to train real cyber attackers who can help. The only way to learn is by practice (with advice). That’s how you learn to ride a bike and that’s how you learn to do anything.

Source: Cyber Attack Academy

May 24, 2017 at 7:00 am 1 comment

Learning Myths And Realities From Brain Science

Interesting results, but also, concerning.  People really believe that intelligence is “fixed at birth” and that teachers don’t need to know content?  The article has more of these:

On the topic of “growth mindset,” more than one-quarter of respondents believed intelligence is “fixed at birth”. Neuroscience says otherwise.

Nearly 60 percent argued that quizzes are not an effective way to gain new skills and knowledge. In fact, quizzing yourself on something you’ve just read is a great example of active learning, the best way to learn.

More than 40 percent of respondents believed that teachers don’t need to know a subject area such as math or science, as long as they have good instructional skills. In fact, research shows that deep subject matter expertise is a key element in helping teachers excel.

Source: Learning Myths And Realities From Brain Science : NPR Ed : NPR

May 15, 2017 at 7:00 am 2 comments

Passing of William G. Bowen: Walk Deliberately, Don’t Run, Toward Online Education

William G. Bowen of Princeton and of the Mellon Foundation recently died at the age of 83. His article about MOOCs in 2013 is still relevant today.

In particular is his note about “few of those studies are relevant to the teaching of undergraduates.”  As I look at the OMS CS results and the empirical evidence about MOOC completers (which matches results of other MOOC experiments of which I’m aware at Georgia Tech), I see that MOOCs are leading to learning and serving a population, but that tends to be the most privileged population.  Higher education is critiqued for furthering inequity and not doing enough to serve underprivileged students.  MOOCs don’t help with that.  It reminds me of Annie Murphy Paul’s article on lecture — they best serve the privileged students that campuses already serve well.  That’s a subtle distinction: MOOCs help, but not the students who most need help.

What needs to be done in order to translate could into will? The principal barriers are the lack of hard evidence about both learning outcomes and potential cost savings; the lack of shared but customizable teaching and learning platforms (or tool kits); and the need for both new mind-sets and fresh thinking about models of decision making.

How effective has online learning been in improving (or at least maintaining) learning outcomes achieved by various populations of students in various settings? Unfortunately, no one really knows the answer to either that question or the important follow-up query about cost savings. Thousands of studies of online learning have been conducted, and my colleague Kelly Lack has continued to catalog them and summarize their findings.

It has proved to be a daunting task—and a discouraging one. Few of those studies are relevant to the teaching of undergraduates, and the few that are relevant almost always suffer from serious methodological deficiencies. The most common problems are small sample size; inability to control for ubiquitous selection effects; and, on the cost side, the lack of good estimates of likely cost savings.

Source: Walk Deliberately, Don’t Run, Toward Online Education – The Chronicle of Higher Education

March 17, 2017 at 7:00 am 5 comments

What engagement looks like in a MOOC-based CS class

My colleague, Ashok Goel, is getting a lot of (deserved) attention for exploring the role of a cognitive assistant as a teaching assistant, known as Jill Watson. The question he’s exploring is: How do we measure the effect of this assistant?

One exploration involves engagement. I thought that these numbers were interesting, because they’re comparable to the ones I explored in my information ecology paper in CSCL many years ago. 38 or 32 notes student in a 15 week class is a couple per week. That’s not a dialogue, but it might be more engagement. What should we expect? Could those couple notes per week be suggesting greater learning elsewhere? Is it an indicator?

“We’re seeing more engagement in the course. For instance, in fall of 2015 before Jill Watson, each student averaged 32 comments during the semester. This fall it was close to 38 comments per student, on average,” Goel said. “I attribute this increased involvement partly to our AI TAs. They’re able to respond to inquiries more quickly than us.”

Source: Jill Watson, Round Three

February 24, 2017 at 7:26 am Leave a comment

How the tech sector could move in One Direction to get more women in computing

Thanks to Greg Wilson for sending this to me.  It takes a while to get to the point about computing education, but it’s worthwhile. The notion is related to my post earlier in the month about engagement and motivation.

I’d been socialised out of using computers at high school, because there weren’t any girls in the computer classes, and it wasn’t cool, and I just wanted to fit in.  I wound up becoming a lawyer, and spending the better part of twenty years masquerading as someone who wasn’t part of the “tech” industry, even though basically all of my time was spent online.

And I can’t begin to tell you how common it is. So what if your first experience of “code” is cutting and pasting something to bring back replies because Tumblr took them away and broke your experience of the site.

Is that any more or less valid than any dev cutting and pasting from Stack Exchange all day long?What if your first online experiences were places like Myspace and Geocities. Or if you started working with WordPress and then eventually moved into more complex themes and then eventually into plugin development? Is that more or less valid than the standard “hacker archetype”? Aurynn gave a great talk recently about the language we use to describe roles in tech. How “wizards” became “rockstars” and “ninjas”.  But also, and crucially, how we make people who haven’t followed a traditional path feel excluded.  Because they haven’t learnt the “right” programming language, or they haven’t been programming since they were four, or because, god forbid, they use the wrong text editor.

Source: How the tech sector could move in One Direction — Sacha Judd

January 27, 2017 at 7:00 am 1 comment

A review of one of my favorite papers: Cognitive Apprenticeship (Collins, Brown, Newman)

I drew on Cognitive Apprenticeship a lot in my dissertation — so much so that Carl Berger asked me at my proposal, “Are you testing Cognitive Apprenticeship as a model?”  I had no idea how to respond, and 25 years later, I still don’t.  How do you test a conceptual framework?

Cognitive apprenticeship, like situated learning, starts from the assumption that apprenticeship is a particularly effective form of education. Then it asks, “How do you offer an apprenticeship around invisible tasks?”

What I like about the essay linked below is that it places cognitive apprenticeship in a broader context.  Apprenticeship isn’t always the best option (as discussed in the post about the Herb Simon paper).

Active listeners or readers, who test their understanding and pursue the issues that are raised in their minds, learn things that apprenticeship can never teach. To the degree that readers or listeners are passive, however, they will not learn as much as they would by apprenticeship, because apprenticeship forces them to use their knowledge. Moreover, few people learn to be active readers and listeners on their own, and that is where cognitive apprenticeship is critical–observing the processes by which an expert listener or reader thinks and practicing these skills under the guidance of the expert can teach students to learn on their own more skillfully.

Source: Cognitive Apprenticeship (Collins, Brown, Newman) | Reading for Pleasure

January 20, 2017 at 7:03 am Leave a comment

Power law of practice in software implementation: Does this explain the “W” going away?

I wonder if this result explains why the second semester students in Briana’s studies (see previous blog post) didn’t have the “W” effect.  If you do enough code, you move down the power law of practice, and now you can attend to things like context and generating subgoal labels.

Different subjects start the experiment with different amounts of ability and past experience. Before starting, subjects took a multiple choice test of their knowledge. If we take the results of this test as a proxy for the ability/knowledge at the start of the experiment, then the power law equation becomes (a similar modification can be made to the exponential equation):

eqn

That is, the test score is treated as equivalent to performing some number of rounds of implementation). A power law is a better fit than exponential to this data (code+data); the fit captures the general shape, but misses lots of what look like important details.

Source: The Shape of Code » Power law of practice in software implementation

January 18, 2017 at 7:26 am 2 comments

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