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The diverse team of eLearning advisors provide elearning workshops, send out periodic newsletter, provide customised consultation, support the eScholar program and more. Use the 'Filter' pull-down menu above to search for topics by keywords.
Via Kim Flintoff
During the spring 2012 semester, the Open Academic Analytics Initiative (OAAI), led by Marist College, successfully deployed an open-source Learning Analytics solution, developed by the project during the fall, at two community colleges (Cerritos College and College of the Redwoods) and one Historically Black College and University (HBCU) (Savannah State University) as a means to further research in this emerging field. Our spring pilots involved a total of 1379 students, 67% of whom were considered low-income students, who were enrolled in introductory-level courses with, generally, three sections each being taught by the same instructor (e.g. BIOL 101 Section 1, 2 and 3). Each course section was then assigned to either a control or one of two treatment groups, thereby standardizing the instructional delivery to the extent possible across all three. Students in the two treatment groups who had been identified by our predictive model, which uses student demographic, aptitude and course management system usage data, as being likely to not complete the course received interventions designed to help them succeed.
Graph databases and graph-processing applications have been popping up all over the place lately, and now they’re starting to go commercial. On Tuesday, popular open source project GraphLab joined the ranks of graph startups.
Desire2Learn has introduced new functionality to its learning management suite, including new predictive analytics tools, improvements on the mobile and e-portfolio fronts, and an important addition in the area of accessibility.
Kate Crawford of the MIT Centre for Civic Media goes behind the numbers to debunk five myths about big data.
With GeoFlow, you can: Map Data: Plot more than one million rows of data from an Excel workbook, including the Excel Data Model or PowerPivot, in 3D on Bing maps. Choose from columns, heat maps, and bubble visualizations.Discover Insights: Discover new insights by seeing your data in geographic space and seeing time-stamped data change over time. Annotate or compare data in a few clicks.Share Stories: Capture "scenes" and build cinematic, guided "tours" that can be shared broadly, engaging audiences like never before.
Via siobhan-o-flynn
The use of big data and analytics to predict student success presents unique ethical questions for higher education administrators relating to the nature of knowledge; in education, "to know" entails an obligation to act on behalf of the student. The Potter Box framework can help administrators address these questions and provide a framework for action.
Big data, big money, big skill set now required. Universities are on it.
Students' online academic activities are used to predict which students are most likely to fail.
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 Susan Bainbridge
Nine universities are testing technology that allows them to track their students’ progress with digital textbooks.
Bentley University's Senior Lecturer in Computer Information Systems explores how big data is increasingly flourishing all around us, and what that means for instruction, for the academic disciplines, and for IT in higher education.
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Presentation for LAK13 open online course
Higher education is a big business, and colleges and universities need reliable data to inform decisions that impact thousands of students and faculty each day.
Nine universities are testing technology that allows them to track their students’ progress with digital textbooks.
QUT is looking to tap the power of analytics with a plan to mine data from multiple systems including massively open online courses.
In our digital world, social relations have become mediated by data. Without even realizing it, we’re barricading ourselves against strangeness -- people and ideas that don't fit the patterns of who we already know, what we already like and where we’ve already been. A call for technology to deliver us to what and who we need, even if it’s unfamiliar. (Filmed at TED@Intel.) A principal engineer at Intel, Maria Bezaitis focuses on how constellations of personal data can form new business models.
Abstract The Open Academic Analytics Initiative (OAAI) seeks to increase college student retention by performing early detection of academic risk using predictive analytics. OAAI examined the degree to which a model built using data from Marist College would compare to the original model built at Purdue University, and we found the models to be statistically similar. For the research project reported in this paper, the OAAI sought to improve understanding of how learning analytics can best be scaled across institutions of higher education. During the spring 2012 semester, the OAAI successfully deployed an open-source learning analytics solution at two community colleges (Cerritos College and College of the Redwoods) and one historically black university (Savannah State University) as a means to further research in this emerging field. The Seeking Evidence of Impact (SEI) program is intended to bring the teaching and learning community into a discussion about ways of gathering evidence of the impact of our innovations and current practices. The goal of the SEI case studies is to provide examples of successful projects evaluating the impact of innovation, technology, and best practices in teaching and learning. In addition to the SEI case studies, you may find other ELI resources useful in addressing teaching, learning, and technology issues at your institution. To learn more, please visit the ELI Resources page.
The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses. Numbers can't speak for themselves, and data sets -- no matter their scale -- are still objects of human design. The tools of big-data science, such as the Apache Hadoop software framework, do not immunize us from skews, gaps, and faulty assumptions. Those factors are particularly significant when big data tries to reflect the social world we live in, yet we can often be fooled into thinking that the results are somehow more objective than human opinions. Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
Desire2Learn has introduced new functionality to its learning management suite, including new predictive analytics tools, improvements on the mobile and e-portfolio fronts, and an important addition in the area of accessibility.
The New York-based institution has teamed up with IBM to offer a new graduate degree program that aims to prepare students for information technology jobs supporting big data. The degree program will be a one year, 30 credit program. The curriculum will focus on three core components: A business core to show big data's role in business strategy, operations, growth and competitive standing; An analytics core, with training in predictive modeling, recognizing data patterns, managing data, statistical analysis, and exploiting big data; An experiential core with project-based courses in which students apply what they've learned to real-world business issues.
Schools put CourseSmart‘s big data analytics to work monitoring student engagement of assigned course materials. Earlier, we mentioned Desire2Learn, which analyzes student performance on the course level to improve graduation rates. Here’s a look at CourseSmart that crunches ebook usage by students so teachers can parse engagement through reports like the one excerpted above (full report at The Times).
Collecting data and statistics is nothing new in education. Educators have been using Blackboard’s analytics software for years. But what is new is the sheer amount of predictive analytics that is available. President Obama recently announced that he wants America’s college graduate ranking to go from 12th place in the world last year to first by 2020. To accomplish this, our nation’s schools and educators will need to harness the power of big data – at least that’s what Toronto-based education startup Desire2Learn says.
We may be upon predictive analytics’ moment in higher education, with student retention as its “killer app”. Institutions of every type – from 4-year publics to 4-year privates and community colleges – are acquiring commercial systems or building their own to mine a lengthening online audit trail of student data for everything from student services portal logins to LMS activity to digital textbook interactions.
But our efforts at personalization in math education have led all of our students to the same buffet line. Every station features the same horrible gruel but at its final station you can select your preferred seasoning for that gruel.
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