Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education
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Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education
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Rescooped by Peter Mellow from Learning and Teaching in an Online Environment
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Understanding Learning and Learning Design in MOOCs: A Measurement-Based Interpretation | Milligan | Journal of Learning Analytics

Understanding Learning and Learning Design in MOOCs: A Measurement-Based Interpretation
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How Students Engage with a Remedial English Writing MOOC: A Case Study in Learning Analytics with Big Data | EDUCAUSE.edu

How Students Engage with a Remedial English Writing MOOC: A Case Study in Learning Analytics with Big Data | EDUCAUSE.edu | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it

Insufficient academic preparation is a major barrier to student success in higher education in the United States, and a large percentage of students who require remedial education become mired in courses that are taught using the same deficit-based pedagogy that contributed to their failure to master the curriculum in high school. In 2011, declining state revenues in California and shrinking budgets for education prompted a review of massive open online courses (MOOCs) as a means to improve access to college. However, MOOCs are often designed for students who already possess the kinds of study skills and habits that many remedial students lack. Could a MOOC be designed to serve remedial students without strong study skills and habits? Crafting an Effective Writer: Tools for the Trade (CEW) was designed to create a noncredit option for remedial students to help build their skills before they enter college and thus reduce the remedial instruction needed.

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Rescooped by Peter Mellow from Learning with MOOCs
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What 6.9 million clicks tell us about how to fix online education

What 6.9 million clicks tell us about how to fix online education | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it

In a paper published this spring, the CSAIL team outlined some key findings on what online learners want from videos. These include:


Brevity (viewers generally tune out after six minutes)


Informality, with professors seated at a desk, not standing behind a podium


Lively visuals rather than static PowerPoint slides


Fast talkers (professors seen as the most engaging spoke at 254 words per minute)


More pauses, so viewers can soak in complex diagrams


Web-friendly lessons (existing videos broken into shorter chunks are less effective than ones crafted for online audiences)

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Stephen Bright's curator insight, July 29, 2014 6:06 PM

Analysis from MIT about the features of online videos used in MOOCs that online learners prefer. Interesting analysis for MOOCs but these features could be applied to videos used in any implementation of blended learning.

 

Also shows that the slick, production theatre videos with a highly professional look may not be the ones that students prefer to watch.

Nigel Robertson 's curator insight, July 31, 2014 8:04 AM
What we already knew and any academic should intrinsically understand this if they are in tune with the people they teach,
Rescooped by Peter Mellow from Learning with MOOCs
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Analytics at Scale -- Campus Technology

Analytics at Scale -- Campus Technology | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it
MOOCs should be the Holy Grail of student data, but they aren't there yet.

 

One of the great promises of massive open online courses, besides making education more accessible for more students, is the treasure trove of student data collected on a grand scale.

 

Large amounts of data are exactly what higher education needs to stay relevant in this era of disruptive change, as Arizona State University's Adrian Sannier pointed out in his keynote at last year's Campus Technology annual conference. The only way to make sure colleges and universities are continually boosting student success, he said, is evidence-based pedagogy. And that requires scale: "You can't take evidence one class at a time, one person at a time — it takes too long, you don't get a broad enough sample…. I'm not sure you can do it at a university, at a single institution. You may not have enough scale, you may not have enough size."

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Learning analytics at Stanford takes huge leap forward with MOOCs

Learning analytics at Stanford takes huge leap forward with MOOCs | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it
Stanford's Lytics Lab gathers data from massive open online courses to learn more about how we learn. The group studies student behavior to measure interaction and performance.

Via Dr. Susan Bainbridge
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Marci Segal, MS's comment, April 13, 2013 10:56 AM
Good to have a peek inside - thanks!
Marci Segal, MS's curator insight, April 13, 2013 10:57 AM

Good to have a peek inside what's going on, eh?  Ready to take the plunge?

Daniel Tan's curator insight, July 4, 2014 9:42 PM

The greatest contribution of  MOOCs to education will not be the  demographic  and geograhic reach it claims to provide, but the disruption it creates on the limitations and previous beliefs of the instructivist pedagogy model. Data and learning analytics will document how the student, and more specifically,  how the brain learns.  The truism that "(s)he who speaks the most learn the most" will be based on data Collected and analyzed.  For now, we content that in teaching a class, that teacher has  learned the most. :)

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(Re)Searching for Online Learning 2.0 Growth … Are MOOCs The Only Hope? | WiredAcademic

(Re)Searching for Online Learning 2.0 Growth … Are MOOCs The Only Hope? | WiredAcademic | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it
So where will online growth come from? A report last week from Moody’s indicated that massive open online courses (MOOCs) represent a “pivotal development” in higher education and could revolutionize the industry.

 

A ton of educational innovations are coming down the pike as a result of big data, which effectively turns “learning” – heretofore somewhat ineffable – into a living, breathing body that can be monitored: closer to medicine than education has ever been.

 

It is for this reason – the “massive” element – that MOOCs may prove to be important. With mass comes big data. And with big data comes better product and engagement of traditional age students. But massive courses aren’t the only path to big data. Smaller courses with much higher completion rates could prove to be a better source of data.

 

Regardless, in the coming years education research will allow us to check the two hard boxes: product and engagement of traditional age students. Real growth for online education – what we call Online Education 2.0 – will come when we’re firing on all four cylinders, not just two.

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Rescooped by Peter Mellow from Learning with MOOCs
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The Challenge of Understanding MOOC Data -- Campus Technology

The Challenge of Understanding MOOC Data -- Campus Technology | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it
Four years after the launch of edX, the data generated by massive open online courses still mystifies many institutions. Could inter-university collaboration unlock the secrets to better course delivery?
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Research & Practice in Assessment journal releases special big data issue

Research & Practice in Assessment journal releases special big data issue | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it
The issue progresses from a simple definition and explanation of what big data is into more complex issues.
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After grappling with data, MOOC Research Initiative participants release results @insidehighered

After grappling with data, MOOC Research Initiative participants release results @insidehighered | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it

Massive open online course providers are collecting troves of data about their students, but what good is it if researchers can't use the information?


The MOOC Research Initiative formally released its results on Monday, six months after researchers met in Arlington, Texas, to brief one another on initial findings. The body of research -- 22 projects examining everything from how social networks form in MOOCs to how the courses can be used for remedial education -- can perhaps best be described as the first chapter of MOOC research, confirming some widely held beliefs about the medium while casting doubt on others.

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Rescooped by Peter Mellow from Learning with MOOCs
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University to use web data to retain students

University to use web data to retain students | Learning Analytics, Educational Data Mining, Adaptive Learning in Higher Education | Scoop.it
QUT is looking to tap the power of analytics with a plan to mine data from multiple systems including massively open online courses.
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Rescooped by Peter Mellow from Learning with MOOCs
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Pushing the MOOC envelope with Learning Analytics

How can Learning Analytics be used to bring about the true revolution traditionally assumed for MOOCs? With audiences in the thousands of users, the key is mass
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Rescooped by Kim Flintoff from MOOCs, SPOCs and next generation Open Access Learning
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Daphne Koller: What we're learning from online education | Video on TED.com

TED Talks Daphne Koller is enticing top universities to put their most intriguing courses online for free -- not just as a service, but as a way to research how people learn.

 

Each keystroke, comprehension quiz, peer-to-peer forum discussion and self-graded assignment builds an unprecedented pool of data on how knowledge is processed and, most importantly, absorbed.

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