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.
Massive Open Online Courses (MOOCs) collect valuable data on student learning behavior; essentially complete records of al student interactions in a self-contained learning environment, with the benefit of large sample sizes. […]
• […] 76% of all participants were browsers who collectively accounted for only 8% of time spent in the course, whereas, the 7% certificate-earning participants averaged 100 hours each and collectively accounted for 60% of total time.
• Students spent the most time per week interacting with lecture videos and homework, followed by discussion forums and online laboratories;
While written and oral language dominate instruction, the explosion of visual information has created new opportunities to represent complexity, reveal themes, explore data, and communicate information in powerful ways. Here is an overview of some of my favorite examples of visual data representation for education.
We invite you to read our latest SVC2UK White Paper, “The Future of E-ducation“, written in collaboration with Gold Mercury International, the Corporate Vision® Strategy Think Tank. The Paper draws on many of the case studies from SVC2UK 2013 and explores what the future is likely to look like for teachers and students.
"Register now for Tackling the Challenges of Big Data, an online MIT course for engineering and business professionals offered by MIT Professional Education and CSAIL.
This Online X course will survey state-of-the-art topics in Big Data, looking at data collection (smartphones, sensors, the Web), data storage and processing (scalable relational databases, Hadoop, Spark, etc.), extracting structured data from unstructured data, systems issues (exploiting multicore, security), analytics (machine learning, data compression, efficient algorithms), visualization, and a range of applications.
Each module will introduce broad concepts as well as provide the most recent developments in research."
At a conference devoted to exploring Big Data in higher education, the event’s keynote speaker had a surprisingly contrarian take on the subject.
“Big Data is bull—,” Harper Reed, the chief technology officer of President Obama’s 2012 campaign, said to an audience that included many campus IT officials hoping to learn more about Big Data’s benefits.
Reed, who used the power of data to help Obama secure reelection, said the term is just a marketing tool meant to drive college and university IT officials toward expensive technologies for storing and analyzing data.
Kim Flintoff's insight:
Is Big Data just too big to distil into meaningful decisions?
No two students are the same; each brings their own interests, learning modalities, strengths, and prior knowledge of the topic at hand. Addressing students’ individual learning needs in the classroom has always been a key challenge for educators—but new instructional technologies can help.
With student polling software, for instance, teachers can get an accurate, immediate view of each learner’s progress—a concept known as “feedback for learning”—and can tailor their instruction to meet students’ individual needs in real time. And putting mobile technology in the hands of every child allows students to explore their own interests and opens a whole world of self-guided instruction.
With the generous support of Promethean, we’ve assembled this collection of stories to help you use technology to personalize learning for students in your own schools.
Kim Flintoff's insight:
Personalisation is one of the big hopes for the "big data:" movement ion Higher Education.
The collection of data in higher education will never produce a single formula for success, no matter how much students clamor for such a miracle algorithm.
That, along with other harsh realities of data collection and analysis on college campuses, was discussed during the “Allure of Big Data” session at the EDUCAUSE 2013 conference in Anaheim, Calif., where campus technologists from across the world gathered to discuss trends in educational technology.
Did you know that 86% of organizations are focused on reporting, but only 15% of HR functions have strong analytics capabilities? This leads to a disconnect between Learning and Development (L&D) and Corporate within organizations.
Course redesign can be a major undertaking, but utilizing the data derived from your existing course can inform your decisions on what areas need to be targeted. When you combine the four factors I mentioned and use them to form a holistic, summative picture of your course redesign project; you can be certain that what is currently working in your course remains, and what is not working is revised.
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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