Posts tagged ‘learning sciences’
We’re years into the MOOC phenomenon, and I’d hoped that we’d get past MOOC hype. But we’re not. The article below shows the same misunderstandings of learning and teaching that we heard at the start — misunderstandings that even MOOC supporters (like here and here) have stopped espousing.
The value of being in the front row of a class is that you talk with the teacher. Getting physically closer to the lecturer doesn’t improve learning. Engagement improves learning. A MOOC puts everyone at the back of the class, listening only and doing the homework.
In many ways, we have a romanticized view of college. Popular portrayals of a typical classroom show a handful of engaged students sitting attentively around a small seminar table while their Harrison Ford-like professor shares their wisdom about the world. We all know the real classroom is very different. Especially in big introductory classes — American history, U.S. government, human psychology, etc. — hundreds of disinterested, and often distracted, students cram into large impersonal lecture halls, passively taking notes, occasionally glancing up at the clock waiting for the class to end. And it’s no more engaging for the professor. Usually we can’t tell whether students are taking notes or updating their Facebook page. For me, everything past the ninth row was distance learning. A good online platform puts every student in the front row.
I agree strongly with the idea of “learning engineers.” Having learning engineers doesn’t relieve faculty who teach from the responsibility to learn more about learning sciences (see my blog post about testing teachers about PCK). Just teaming up subject-matter experts with learning engineers does not inform a teacher’s day-to-day and in-class decision-making. The general theme below is one I strongly agree with — we should rely more on evidence-based and research-based teaching.
We are missing a job category: Where are our talented, creative, user-centric “learning engineers” — professionals who understand the research about learning, test it, and apply it to help more students learn more effectively?
Jobs are becoming more and more cognitively complex, while simpler work is disappearing. (Even that old standby, cab driving, may one day be at risk from driverless cars from Google!) Our learning environments need to do a better job of helping more people of all ages master the complex skills now needed in many occupations.
I am not suggesting that all subject-matter experts (meaning faculty members) need to become learning engineers, although some might. However, students and faculty members alike would benefit from increased collaboration between faculty members and learning experts — specialists who would respect each other’s expertise — rather than relying on a single craftsman in the classroom, which is often the case in higher education today.
I’m giving the keynote talk at the 2015 International Security Education Workshop at Georgia Tech today. I’ve never spoken on cyber security before, so the talk was challenging and fun to put together. I used some of the learning sciences research we’ve done in computing education to draw connections to cyber security education. The lessons I highlight are:
- Context matters. People only learn when they understand why the learning is useful.
- Identity matters. People who reject computer science (and that’s most people) will likely reject cyber security education, even if they need to know it. The cyber security learning that they need to know has to meet their identity and expectations. Don’t expect them to change who they are and what they think is important.
- Structure matters. Teaching something well, like using subgoal labeling, can dramatically improve learning.
(Click on the image below to get to the Slideshare site)
These do sound like the kinds of things that learning scientists were saying at the start of the MOOC hype (like this post), but I’m glad that he now realizes that MOOCs have limited use and that students vary widely.
And as for MOOCs, which many still predict will displace traditional teaching, he said that they “were the answer when we weren’t sure what the question was.”
He said that their massive nature, which attracted so much attention, was ultimately a problem. “When I think about MOOCs, the advantage — the ability to prepare a course and offer it without personal interaction — is what makes them inexpensive and makes them very limited.”
Students “vary widely in terms of their skills and capability,” he said, such that massiveness is simply not an educational advantage. “For some it’s too deep and for some it is too shallow.”
It’s not surprising that men and women participate differently in online class discussions. I’m disappointed that the interpretations of the results are not grounded in the literature on collaborative learning. We know something about why people might not want to participate in an online forum (as I wrote about in a previous blog post).
Company officials argued that the differences in behavior by gender represent a “gap in confidence” between women and men enrolled in the courses. It’s a phenomenon that has long interested the company’s founder, Pooja Sankar, who says she felt isolated as one of only a few women studying computer science at a university in India and was too shy to collaborate with male classmates.
Based on reports from hundreds of students and professors who use Piazza, “we know that students answer questions more when they feel more confident,” Ms. Gilmartin said. “We know that they use the anonymity setting when they feel less confident.”
Georgia Tech founded the very first HCC degree program in 2004, focusing on the intersection of computing and people – where computing includes not just computers but also different kinds of computational artifacts from games to mobile applications, from robots to bionics and mobile applications; and people includes not only individuals but also teams, organizations, societies and cultures.
Join our 29 faculty in working across the HCC spectrum: learning sciences & technologies, computing education, artificial intelligence, cognitive science, collaboration, design, human-computer interaction, health & wellness, informatics, information visualization & visual analytics, international development, learning sciences & technology, social computing, and ubiquitous & wearable computing.
Join our 39 students, all doing research in one of three broad areas: Cognition, Learning & Creativity, Human-Computer Interaction, and Social Computing. We value diversity in all its dimensions; our students have a broad range of backgrounds, coming from across the world and with a variety of different and undergraduate degrees.
Join a vibrant community of faculty and graduate students that encompasses not just the HCC PhD but also the PhDs in Digital Media, Computer Science with specialization in HCI, Psychology with specializations in Engineering Psychology and Cognitive Aging, Music Technology, and Industrial Design, and the interdisciplinary GVU Center with its multitude of research labs.
Join, upon graduation, our alumni who have academic or research careers at Adobe Research, CMU, Drexel, Georgetown, Georgia Tech, Google, Kaiser Permanente, Kaltura, U. Maryland, U. Michigan, Michigan State, U. Minnesota, Oak Ridge National Labs, Northeastern, Penn State, Rose Hulman, Samsung, Sassafras, U. Washington, US Military Academy and Virginia Tech.
Our curriculum is flexible, allowing considerable customizing based on individual interests: three core courses, three specialization courses and three minor courses. You get involved with research during your first semester, and never stop!
Students receive tuition and a competitive stipend during their studies; outstanding US students are eligible for the President’s Fellowship.
Applications are due December 15; see http://www.ic.gatech.edu/future/phdhcc for additional program and application information.
An interesting new piece on identity within the open source community. Noah Slater addresses a concern that I have, that the definition of contribution in open source communities limits the opportunity for legitimate peripheral participation.
Perhaps the most obvious way in which the hacker identity has a hold over the open source identity is this notion that you have to code to contribute to open source. Much like technical talent is centered in the tech industry, code is seen as the one true way to contribute. This can be such a powerful idea that documentation, design, marketing, and so on are often seen as largely irrelevant. And even when this isn’t the case, they are seen as second class skills. For many hackers, open source is an escape from professional environments where collaboration with these “lesser”, more “mainstream” activities is mandatory.