Posts tagged ‘educational technology’
Checking our hubris with checklists: Learning a lesson from the XO Laptop
My Blog@CACM blog post for February was on Morgan Ames’ book The Charisma Machine (see post here). The book is well-written, and I do recommend it. In the post, I say that the OLPC opposition to HCI design practices is one of the themes in her book that I found most interesting:
It takes humility to design software that humans will use successfully. The human-computer interaction (HCI) community has developed a rich set of methods for figuring out what users need and might use, and for evaluating the potential of a new interface. To use these methods requires us to recognize our limitations — that we are unlikely to get the design right the first time and that our users know things that we don’t.
How do we get developers to have that humility? There are a lot of rewards for hubris. Making big promises that you probably can’t keep is one way to get grant and VC funding.
I just finished Atul Gawande’s The Checklist Manifesto (which I already blogged about here, before I even read it). It’s a short book which I highly recommend. I hadn’t realized before how much Gawande’s story overlaps with the OLPC story — or rather, how much it doesn’t but should have. Gawande is a surgeon. His entry into the idea of checklists is because of the success of checklists in reducing costs and improving patient success rates in medicine. There, too, they had to deal with physician hubris. They saw the checklists as busywork. As one physician said in opposition to checklists, “Forget the paperwork. Take care of the patient.”
The OLPC project couldn’t be bothered with user studies or pilot studies. They wanted to airdrop tablets into Ethiopia. They were so confident that they were going to (in Negroponte’s words) “eliminate poverty, create peace, and work on the environment.” They couldn’t be bothered with the details. They were taking care of the patient!
Gawande points out that checklists aren’t needed because physicians are dumb, but because they know SO much. We’re humans and not Econs. Our attention gets drawn this way or that. We forget about or skip a detail. Our knowledge and systems are so complex. Checklists help us to manage all the details.
We need checklists to check our hubris. We have confidence that we can build technology that changes users lives. The reality is that the odds are slim that we can have impact without going through an HCI design process, e.g., know the user, test often, and iterate. The OLPC Project could have used an HCI checklist.
The second to last chapter in Gawande’s Checklist Manifesto captures the idea well that we need checklists:
We are all plagued by failures—by missed subtleties, overlooked knowledge, and outright errors. For the most part, we have imagined that little can be done beyond working harder and harder to catch the problems and clean up after them. We are not in the habit of thinking the way the army pilots did as they looked upon their shiny new Model 299 bomber—a machine so complex no one was sure human beings could fly it. They too could have decided just to “try harder” or to dismiss a crash as the failings of a “weak” pilot. Instead they chose to accept their fallibilities. They recognized the simplicity and power of using a checklist. And so can we. Indeed, against the complexity of the world, we must. There is no other choice. When we look closely, we recognize the same balls being dropped over and over, even by those of great ability and determination. We know the patterns. We see the costs. It’s time to try something else. Try a checklist.
Do we really want computerized personalized tutoring systems? Answer: Yes
An excerpt from Mitchel Resnick’s new book Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play is published below in the Hechinger Report. Mitchel argues against computerized personal tutoring systems, because they are only good for “highly structured and well-defined knowledge.” Because we don’t know how to build these tutoring systems to teach important topics like creativity and ethics.
Agreed, but we are not currently reaching all students with the “highly structured and well-defined knowledge” that we want them to have. We prefer students to have well-educated teachers, and we want students to learn creativity and ethics, too. But if we can teach topics like mathematics well with personalized tutoring systems, why shouldn’t we use them? Here in Atlanta, students are not learning mathematics well (see blog post referencing an article by Kamau Bobb). We have good results on teaching students algebra with cognitive tutors.
Here’s my concern: Wealthy schools can reject computerized personal tutoring systems because they can afford well-trained teachers, which means that there is less of a demand for computerized personal tutoring systems. Lower demand means higher costs, which means that less-wealthy schools can’t afford them. If we encourage more computerized personal tutoring systems where they are appropriate, more of them get created, they get better, and they get cheaper.
But I’m skeptical about personalized tutoring systems. One problem is that these systems tend to work only in subject areas with highly structured and well-defined knowledge. In these fields, computers can assess student understanding through multiple-choice questions and other straightforward assessments. But computers can’t assess the creativity of a design, the beauty of a poem, or the ethics of an argument. If schools rely more on personalized tutoring systems, will they end up focusing more on domains of knowledge that are easiest to assess in an automated way?
Disrupt This!: MOOCs and the Promises of Technology by Karen Head
Over the summer, I read the latest book from my Georgia Tech colleague, Karen Head. Karen taught a MOOC in 2013 to teach freshman composition, as part of a project funded by the Gates Foundation. They wanted to see if MOOCs could be used to meet general education requirements. Karen wrote a terrific series or articles in The Chronicle of Higher Education about the experience (you can see my blog post on her last article in the series here). Her experience is the basis for her new book Disrupt This! (link to Amazon page here). There is an interview with her at Inside Higher Education that I also recommend (see link here).
In Disrupt This!, Karen critiques the movement to “disrupt education” with a unique lens. I’m an education researcher, so I tend to argue with MOOC advocates with data (e.g., my blog post in May about how MOOCs don’t serve to decrease income inequality). Karen is an expert in rhetoric. She analyzes two of the books at the heart of the education disruption literature: Clayton Christensen and Henry Eyring’s The Innovative University: Changing the DNA of Higher Education from the Inside Out and Richard DeMillo’s Abelard to Apple: The Fate of American Colleges and Universities. She critiques these two books from the perspective of how they argue — what they say, what they don’t say, and how the choice of each of those is designed to influence the audience. For example, she considers why we like the notion of “disruption.”
Disruption appeals to the audience’s desire to be in the vanguard. It is the antidote to complacency, and no one whose career revolves around the objectives of critical thinking and originality—the pillars of scholarship—wants to be accused of that…Discussions of disruptive innovation frequently conflate “is” (or “will be”) and “ought.” In spite of these distinctions, however, writers often shift from making dire warnings to an apparently gleeful endorsement of disruption. This is not unrelated to the frequent use of millenarian or religiously toned language, which often warns against a coming apocalypse and embraces disruption as a cleansing force.
Karen is not a luddite. She volunteered to create the Composition MOOC because she wanted to understand the technology. She has high standards and is critical of the technology when it doesn’t meet those standards. She does not suffer gladly the fools who declare the technology or the disruption as “inevitable.”
The need for radical change in today’s universities—even if it is accepted that such change is desirable—does not imply that change will inevitably occur. To imply that because the church should have embraced the widespread publication of scripture, modern universities should also embrace the use of MOOCs is simply a weak analogy.
Her strongest critique focuses on who these authors are. She argues that the people who are promoting change in education should (at least) have expertise in education. Her book mostly equates expertise with experience. My colleagues and I work to teach faculty about education, to develop their expertise before they enter the classroom (as in this post). I suspect Karen would agree with me about different paths to develop expertise, but she particularly values getting to know students face-to-face. She’s angry that the authors promoting education disruption do not know students.
It is a travesty that the conversation about the reform or disruption of higher education is being driven by a small group of individuals who are buffered from exposure to a wide range of students, but who still claim to speak on their behalf and in their interests.
Disrupt This! gave me a new way to think about MOOCs and the hype around disruptive technologies in education. I often think in terms of data. Karen shows how to critique the rhetoric — the data are less important if the argument they are supporting is already broken.
The Father Of Mobile Computing Is Not Impressed: The Weight of Redefining the Normal
I have been fortunate to have heard Alan Kay talk on the themes in this interview many times, but either he’s getting better at it or I’m learning enough to understand him better, because this was one of my favorites. (Thanks to Ben Shapiro for sending it to me.) He ties together Steve Jobs, Neal Postman, and Maria Montessori to explain what we should be doing with education and technology, and critiques the existing technology as so much less than what we ought to be doing. In the quote below, he critiques Tim Berners-Lee for giving us a World Wide Web which was less than what we already knew how to do. The last paragraph quoted below is poignant: It’s so hard to fix the technology once it’s established because of “the weight of this redefining of the normal.”
What I understood this time, which I hadn’t heard before, was the trade-off between making technology easier and making people better. I’ve heard Alan talk about using technology to improve people, to help them learn, to challenge their thinking. But Alan led the team that invented the desktop user interface — he made computing easier. Can we have both? What’s the balance that we need? That’s where Neal Postman and Bertrand Russel come in, as gifted writers who drew us in and then changed our minds. That’s why we need adults who know things to create a culture where children learn 21st century thinking and not oral culture (that’s the Maria Montessori part), and why the goal should be about doing what’s hard — not doing what’s universal, not doing what pre-literate societies were doing. Alan critiques the iPhone as not much better than the television for learning, when the technology in the iPhone could have made it so much more.
He tosses out another great line near the end of the interview, “How stupid is it, versus how accepted is it?” How do we get unstuck? The iPhone was amazing, but how do we roll back the last ten years to say, “Why didn’t we demand better? How do we shuck off the ‘the weight of this redefining of the normal’ in order to move to technology that helps us learn and grow?”
And so, his conception of the World Wide Web was infinitely tinier and weaker and terrible. His thing was simple enough with other unsophisticated people to wind up becoming a de facto standard, which we’re still suffering from. You know, [HTML is] terrible and most people can’t see it.
FC: It was standardized so long ago.
AK: Well, it’s not really standardized because they’re up to HTML 5, and if you’ve done a good thing, you don’t keep on revving it and adding more epicycles onto a bad idea. We call this reinventing the flat tire. In the old days, you would chastise people for reinventing the wheel. Now we beg, “Oh, please, please reinvent the wheel.”At least give us what Engelbart did, for Christ’s sake.
But that’s the world we’re in. We’re in that world, and the more stuff like that world that is in that world, the more the world wants to be that way, because that is the weight of this redefining of the normal.
How to Write a Guzdial Chart: Defining a Proposal in One Table
In my School, we use a technique for representing an entire research proposal in a single table. I started asking students to build these logic models when I got to Georgia Tech in the 1990’s. In Georgia Tech’s Human-Centered Computing PhD program, they have become pretty common. People talk about building “Guzdial Charts.” I thought that was cute — a local cultural practice that got my name on it.
Then someone pointed out to me that our HCC graduates have been carrying the practice with them. Amy Voida (now at U. Colorado-Boulder) has been requiring them in her research classes (see syllabus here and here). Sarita Yardi (U. Michigan) has written up a guide for her students on how to summarize a proposal in a single table. Guzdial Charts are a kind of “thing” now, at least in some human-centered computing schools.
Here, I explain what a Guzdial Chart is, where it came from, and why it should really be a Blumenfeld Chart [*].
Phyllis Teaches Elliot Logic Models
In 1990, I was in Elliot Soloway’s office at the University of Michigan as he was trying to explain an NSF proposal he was planning with School of Education professor, Phyllis Blumenfeld. (When I mention Phyllis’s name to CS folks, they usually ask “who?” When I mention her name to Education folks, they almost always know her — maybe for her work in defining project-based learning or maybe her work in instructional planning or maybe her work in engagement. She’s retired now, but is still a Big Name in Education.) Phyllis kept asking questions. “How many students in that study?” and “How are you going to measure that?” She finally got exasperated.
She went to the whiteboard and said, “Draw me a table like this.” Each row of the table is one study in the overall project.
- Leftmost column: What are you trying to achieve? What’s the research question?
- Next column: What data are you going to collect? What measures are you going to use (e.g., survey, log file, GPS location)?
- Next column: How much data are you going to collect? How many participants? How often are you going to use these measures with these participants (e.g., pre/post? Midterm? After a week delay?)?
- Next column: How are you going to analyze these data?
- Rightmost column: What do you expect to find? What’s your hypothesis for what’s going to happen?
This is a kind of a logic model, and you can find guides on how to build logic models. Logic models are used by program evaluators to describe how resources and activities will lead to desired impacts. This is a variation that Phyllis made us use in all of our proposals at UMich. (Maybe she invented it?) This version focused on the research being proposed. Each study reads on a row from left-to-right,
- from why you were doing it,
- to what you were doing,
- to what you expected to find.
When I got to Georgia Tech, I made one for every proposal I wrote. I made my students do them for their proposals, too. Somewhere along the way, lots of people started doing them. I think Beth Mynatt first called them “Guzdial Charts,” and despite my story about Phyllis Blumenfeld’s invention, the name stuck. People at Georgia Tech don’t know Phyllis, but they did know Guzdial.
Variations on a Guzdial Chart Theme
The critical part of a Guzdial Chart is that each study is one row, and includes purpose, methods, and expected outcome. There are lots of variations. Here’s an example of one that Jason Freeman (in our School of Music) wrote up for a proposal he was doing on EarSketch. He doesn’t list hypotheses, but it still describes purpose and methods, one row per study.
In Sarita’s variation, she has the students put the Expected Publication in the rightmost column. I like that — very concrete. If you’re in a discipline with some clearly defined publication targets, with a clear distinction between them (e.g. , the HCI community where Designing Interactive Systems (DIS) is often about process, and User Interface Software and Technology (UIST) is about UI technologies), then the publication targets are concrete and definable.
My former student, Mike Hewner, did one of the most qualitative dissertations of any of my students. He used a Guzdial Chart, but modified it for his study. Still one row per study, still including research question, hypothesis, analysis, and sampling.
I still use Guzdial Charts, and so do my students. For example, we used one to work through the story for a paper. Here’s one that we started on a whiteboard outside of my office, and we left it there for several weeks, filling in the cells as they made sense to us.
A Guzdial Chart is a handy way of summarizing a research project and making sure that it makes sense (or to use when making sense), row-by-row, left-to-right.
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[*] Because Ulysses now makes it super-easy to post to blogs, and I do most of my writing in Ulysses, I accidentally posted this post to Medium — my first ever Medium post. I wanted this to appear in my WordPress blog, also, so I decided to two blog posts: The Medium one on Blumenfeld Charts, and this one on Guzdial Charts.
NSF director unveils big ideas, with an eye on the next President and Congress
Interesting and relevant for this list. There’s a lot in the NSF big ideas document (see link here) about using technology for learning, but there’s also some on what we want students to know (including about computing technology), e.g., “the development and evaluation of innovative learning opportunities and educational pathways, grounded in an education-research-based understanding of the knowledge and skill demands needed by a 21st century data-capable workforce.”
The six “research” ideas are intended to stimulate cross-disciplinary activity and take on important societal challenges. Exploring the human-technology frontier, for example, reflects NSF’s desire “to weave in technology throughout the fabric of society, and study how technology affects learning,” says Joan Ferrini-Mundy, who runs NSF’s education directorate. She thinks it will also require universities to change how they educate the next generation of scientists and engineers.
Source: NSF director unveils big ideas, with an eye on the next president and Congress | Science | AAAS
The Indian Education Context is Completely Different from the US Education Context
At LaTICE 2016, I attended a session on teacher professional development. I work at preparing high school CS teachers. I felt like I’d be able to relate to the professional development work. I was wrong.
One of the large projects presented at LaTICE 2016 was the T10kT project (see link here) whose goal is to use technology to train 10,000 teachers. What I didn’t realize at first was that the focus is on higher-education teachers, not high school teachers. The only high school outreach activity I learned about at LaTICE 2016 was from the second keynote, on an Informatics Olympiad from Madhavan Mukund (see slides here) which is only for a select group of students.
India has 500 universities, and over 42,000 higher education institutions. They have an enormous problem trying to maintain the quality of their higher-education system (see more on the Wikipedia page). They rely heavily on video, because videos can be placed on a CD or USB drive and mailed. The T10kT instructors can’t always rely on Internet access even to higher-education institutions. They can’t expect travel even to regional hubs because many of the faculty can’t travel (due to expense and family obligations).
As can be seen in the slide above, they have a huge number of participants. I asked at the session, “Why?” Why would all these higher-education faculty be interested in training to become better teachers? The answer was that participants get certificates for participating in T10kT, and those certificates do get considered in promotion decisions. That’s significant, and something I wish we had in the US.
I tried to get a sense for how many primary and secondary schools there are in India, and found estimates ranging from 740K to 1.3M. Compulsory education was only established in 2010 (goes to age 14), and is not well enforced. I heard estimates that about 50% of school-age children go to school because only enrollment is checked, not attendance.
Contrast this with the CS10K effort in the United States. There are about 25-30,000 high schools in the US. Having 10K CS teachers wouldn’t reach every school, but it would make a sizable dent. A goal to get 10K CS teachers in Indian high schools would be laughable. When you increase the number of high schools by two orders of magnitude, 10,000 teachers barely moves the needle. Given the difficulty of access and uncertain Internet, it’s certainly not cheaper to provide professional development in India. They have an enormous shortage of teachers — not just CS. They lack any teachers at all in many schools. The current national focus is on higher-education because the secondary and primary school problems are just so large.
Alan Kay has several times encouraged me to think about how to provide educational technology to support students who do not have access to a teacher. I resisted, because I felt that any educational technology was a poor substitute for a real teacher. Now I realize what a privilege it is to have any teacher at all, and how important it is to think about technology-based guided learning for the majority of students worldwide who do not have access to a teacher.
How do we do it? How do we design technology-based learning supports for Indian students who may not have access to a teacher? I attended a session on IITBx, the edX-hosted MOOCS developed by IIT-Bombay. I tweeted:
#latice2016 Bravo! #iitb MOOCs are made explicitly for India. Advice for US/UK-providers on how to make their MOOCs more useful in India?
— Mark Guzdial (@guzdial) April 3, 2016
One of the IIT-Bombay graduate students responded:
I believe the ans is to have MOOCs made in India and for India keeping the local context in mind #latice2016 https://t.co/Bs9wLFMGmJ
— akothiyal (@akothiyal) April 3, 2016
Here’s the exchange as a screencap, just in case the Twitter feed doesn’t work right above:
I’m sure that Aditi (whose work was described in the previous blog post) is right. Developers in the US can’t expect to build technologies for India and expect them to work, not without involving Indian learners, teachers, and researchers. One of the themes in my book Learner-Centered Design of Computing Education is that motivation is everything in learning, and motivation is tied tightly to notions of identity, community of practice, and context. I learned that I don’t know much about any of those things for India, nor anywhere else in the developing world. The problems are enormous and worth solving, and US researchers and developers have a lot to offer — as collaborators. In the end, it requires understanding on the ground to get the context and motivation right, and nothing works if you don’t get that right.
New OECD Report Slams Computers And Says Why They Can Hurt Learning: It’s all about the pedagogy
My PhD advisor, Elliot Soloway, considers a new report on the value of computers in education, and gets to the bottomline. To swipe a line from Bill Clinton, “It’s the pedagogy, stupid!” Of course, I agree with Elliot, and it’s why Lecia Barker’s findings are so disturbing. We have to be willing to change pedagogy to improve learning.
The findings are the findings, but what is really interesting is a statement that Andreas Schleicher, the director of OECD, made as to why the impact of technology is negative. In the foreword to the OECD report, he writes, “…adding 21st century technologies to 20th century teaching practices will just dilute the effectiveness of teaching.”WOW! In this one sentence, Schleicher names clearly what he sees as the root cause of the lack of technology’s impact on student achievement. While the NYT’s articles danced around the issues, Schleicher doesn’t pull any punches: The reason computers are not having a positive impact lies in the use of outmoded teaching practices that do not truly exploit the opportunities that a 1-to-1 classroom affords.
Source: New OECD Report Slams Computers — and Actually Says Why They Can Hurt Learning — THE Journal
The Invented History of ‘The Factory Model of Education’: Personalized Instruction and Teaching Machines aren’t new
When I was a PhD student taking Education classes, my favorite two-semester sequence was on the history of education. I realized that there wasn’t much new under the sun when it comes to thinking about education. Ideas that are key to progressive education movements date back to Plato’s Republic: “No forced study abides in a soul…Therefore, you best of men, don’t use force in training the children in the studies, but rather play. In that way you can also better discern what each is naturally directed toward.” Here we have learning through games (but not video games in 300BC) and personalized instruction — promoted over 2400 years ago. I named my dissertation software system Emile after Rousseau’s book with the same name whose influence reached Montessori, Piaget, and Papert decades later.
Audrey Watters takes current education reformers to task in the article linked below. Today’s reformers don’t realize the history of the education system, that many of the idea that they are promoting have been tried before. Our current education system was designed in part because those ideas have already failed. In particular, the idea of building “teaching machines” as a response to “handicraft” education was suggested over 80 years ago. Education problems are far harder to solve than today’s education entrepreneurs realize.
Many education reformers today denounce the “factory model of education” with an appeal to new machinery and new practices that will supposedly modernize the system. That argument is now and has been for a century the rationale for education technology. As Sidney Pressey, one of the inventors of the earliest “teaching machines” wrote in 1932 predicting “The Coming Industrial Revolution in Education,”
Education is the one major activity in this country which is still in a crude handicraft stage. But the economic depression may here work beneficially, in that it may force the consideration of efficiency and the need for laborsaving devices in education. Education is a large-scale industry; it should use quantity production methods. This does not mean, in any unfortunate sense, the mechanization of education. It does mean freeing the teacher from the drudgeries of her work so that she may do more real teaching, giving the pupil more adequate guidance in his learning. There may well be an “industrial revolution” in education. The ultimate results should be highly beneficial. Perhaps only by such means can universal education be made effective.
via The Invented History of ‘The Factory Model of Education’.
The reality is that technology never has and never will dramatically change education (as described in this great piece in The Chronicle). It will always be a high-touch endeavor because of how humans learn.
Education is fundamentally a human activity and is defined by human attention, motivation, effort, and relationships. We need teachers because we are motivated to make our greatest efforts for human beings with whom we have relationships and who hold our attention.
In the words of Richard Thaler, there are no Econs (see recommended piece in NYTimes).
What MOOCs are really good for: I’m going to do my first MOOC
A nice piece updating what we know about MOOCs, who’s taking them, and what they’re good for. I have decided to offer my first MOOC, as part of an HCI specialization with Coursera. (See the announcement here.) This fits in exactly with what I think a MOOC is good for — it’s professional development for people with background in the field. If students going to learn about HCI, I’d also like them to learn about making technologies for learning and about how people learn. I agreed to do a short four week MOOC on designing learning technologies, development to occur this summer. This isn’t about my research exactly (though, because it’s me, a lot of the examples will probably come from computing education). It’s not about reaching an under-served population, or teaching CS-novices or teachers. Different purpose, different objectives — and objectives for this course and for the GT HCI specialization match for what a MOOC is good for.
The companies that rode to fame on the MOOC wave had visions and still do of offering unfettered elite education to the masses and driving down college tuition. But the sweet spot for MOOCs is far less inspirational and compelling. The courses have become an important supplement to classroom learning and a tool for professional development.
Why one school district decided giving laptops to students is a terrible idea
A really fascinating piece about all the problems that Hoboken had with their one-laptop-per-child program. The quote listed below describes the problems with breakage and pornography. The article goes on to describe problems with too little memory, bad educational software, wireless network overload, anti-virus expense, and teacher professional learning costs. I firmly believe in the vision of one-laptop-per-student. I also firmly believe that it’s crazy-expensive and hard to make work right, especially in large school districts.
We had “half a dozen kids in a day, on a regular basis, bringing laptops down, going ‘my books fell on top of it, somebody sat on it, I dropped it,’ ” said Crocamo. Screens cracked. Batteries died. Keys popped off. Viruses attacked. Crocamo found that teenagers with laptops are still… teenagers. “We bought laptops that had reinforced hard-shell cases so that we could try to offset some of the damage these kids were going to do,” said Crocamo. “I was pretty impressed with some of the damage they did anyway. Some of the laptops would come back to us completely destroyed.”
Crocamo’s time was also eaten up with theft. Despite the anti-theft tracking software he installed, some laptops were never found. Crocamo had to file police reports and even testify in court.
Hoboken school officials were also worried they couldn’t control which websites students would visit. Crocamo installed software called Net Nanny to block pornography, gaming sites and Facebook. He disabled the built-in web cameras. He even installed software to block students from undoing these controls. But Crocamo says students found forums on the Internet that showed them how to access everything.“There is no more determined hacker, so to speak, than a 12-year-old who has a computer,” said Crocamo.
Crowd-sourcing hints for Code.org tutorials via CSTA teachers
Really interesting idea — Code.org’s Pat Yongpradit sent a note to all of CSTA, asking CS teachers to help provide hints for Code.org tutorials. By reaching out to CSTA, they’re doing better than crowd-sourcing. They’re CS-teacher-sourcing.
We’ve had millions of students try the Code.org tutorials. They’ve submitted over 11 million unique computer programs as solutions to roughly 100 puzzles.
We’ve mapped out which submissions are errors (ie they don’t solve the puzzle), and which are sub-optimal solutions (they solve the puzzle, but not efficiently).
Today, erroneous user submissions receive really unhelpful error feedback, such as “You’re using the right blocks, but not in the right way”. We want your help improving this, by providing highly personal feedback to very specific student errors. Watch the video below to see what we mean.
Workshop Report: Multidisciplinary Research for Online Education » CCC Blog
The report on the CCC’s workshop on MOOCs and other online education technologies is now out.
In February 2013 the Computing Community Consortium (CCC) sponsored the Workshop on Multidisciplinary Research for Online Education (MROE). This visioning activity explored the research opportunities at the intersection of the learning sciences, and the many areas of computing, to include human-computer interactions, social computing, artificial intelligence, machine learning, and modeling and simulation.
The workshop was motivated and informed by high profile activities in massive, open, online education (MOOE). Point values of “massive” and “open” are extreme values that make explicit, in ways not fully appreciated previously, variability along multiple dimensions of scale and openness.
The report for MROE has been recently completed and is online. It summarizes the workshop activities and format, and synthesizes across these activities, elaborating on 4 recurring themes:
- Next Generation MOOCs and Beyond MOOCs
- Evolving Roles and Support for Instructors
- Characteristics of Online and Physical Modalities
- Physical and Virtual Community
via Workshop Report: Multidisciplinary Research for Online Education » CCC Blog.
Gesture interfaces can convey scale better than fixed diagrams
The title on the post linked below is wrong, “Can iPads help students learn science? Yes, study shows.” It’s never whether a technology can help learning. It’s how it can help, and what it can help with. The study described is a great example of this.
iPads can be used really badly (while also being quite expensive) in schools. Philip Sadler’s new study shows that students can use the gesture-based interface of the iPad to understand issues of scale (just how far is the Moon from the Earth?) better than any diagram can convey.
They found that while the traditional approaches produced no evident gain in understanding, the iPad classrooms showed strong gains. Students similarly struggle with concepts of scale when learning ideas in biology, chemistry, physics, and geology, which suggests that iPad-based simulations also may be beneficial for teaching concepts in many other scientific fields beyond astronomy.
Moreover, student understanding improved with as little as 20 minutes of iPad use. Guided instruction could produce even more dramatic and rapid gains in student comprehension.
“While it may seem obvious that hands-on use of computer simulations that accurately portray scale would lead to better understanding,” says Philip Sadler, a co-author of the study, “we don’t generally teach that way.” All too often, instruction makes use of models and drawings that distort the scale of the universe, “and this leads to misconceptions.”
via Can iPads help students learn science? Yes, study shows.
ScratchJr: Coding for Young Kids — Kickstarter Campaign
I got to see a build of ScratchJr at the NSF CE21 PI’s meeting in January — it’s really fun. Attractive, responsive, and well thought through, as one would expect with this team.
Coding (or computer programming) is a new type of literacy. Just as writing helps you organize your thinking and express your ideas, the same is true for coding. In the past, coding was seen as too difficult for most people. But we think coding should be for everyone, just like writing.
As young children code with ScratchJr, they learn how to create and express themselves with the computer, not just interact with it. In the process, children develop design and problem-solving skills that are foundational for later academic success, and they use math and language in a meaningful and motivating context, supporting the development of early-childhood numeracy and literacy.
With ScratchJr, children aren’t just learning to code, they are coding to learn.
via ScratchJr: Coding for Young Kids by Mitchel Resnick — Kickstarter.
Computing Ed Research - Guzdial's Take 
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