Blog Archives

Predicting course outcomes with digital textbook analytics

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By Reynol Junco, associate professor, Iowa State University; and faculty associate, Berkman Center for Internet and Society1.

Over the last years, I’ve been researching how real-time behavioral data, collected unobtrusively through technology, can predict learning outcomes. As part of this line of research, I’ve recently published the paper Predicting course outcomes with digital textbook usage data in The Internet and Higher Education.

The study used data collected from student engagement with digital textbooks in order to predict course grades. Two measures of student engagement with the texts were analyzed: an engagement index that was calculated through a linear combination of the number of pages read, number of times a student opened their textbook, number of days the student used their textbook, time spent reading, number of highlights, number of bookmarks, and number of notes. The second analysis included the individual components of the engagement index.

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Analytics by and for students

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By Maarten de Laat, professor, Open University of the Netherlands.

Professor of professional development in social networks, De Laat interests in big data and analytics rely on the idea that they can make more visible and transparent what people are talking about in educational environments, making easier for other students to engage in a group with shared interests. He is also a strong defender of releasing the information obtained through analytics to students, instead of keeping it within a teaching/administrative level, so that they can use it to facilitate their own learning processes. Get De Laat’s complete reflections in the short video below. We would like to thank the EDEN Conference organisation for this contribution.

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Big Data, Learning Analytics and Distance Education

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By Terry Anderson, professor in Distance Education, Athabasca University.

As an educational technologist, I seem always infatuated with the latest tools, even as I grow increasingly alert to what is lost as well as what is gained from their use.

Learning analytics joins the family of mostly commercial applications based on “big data”. These tools promises — perhaps too optimistically — to replace metaphors of information overload, info glut and obesity with the more optimistic sense that, although “big” we can effectively gather and interpret the torrent of digital information traces left by distance teachers and learners.

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The importance of context

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By Julià Minguillón, Associate Professor, UOC-eLC.

We are living in the information age. Or maybe in the knowledge one, according to the DIKW pyramid, which stands for data, information, knowledge and wisdom. But there is neither information nor knowledge without data, which is nowadays massively and continuously generated.

As inhabitants of a digital world, all our actions are under a constant surveillance, and we leave a myriad of traces of even the most mundane everyday experiences. We voluntarily use our smartphones, credit cards or ID badges, leaving such digital traces, but we are also involuntarily recorded in traffic cameras or when browsing the Internet, for instance.

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Shedding light on personal data, analytics and education

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By Angel A. Juan, Associate Professor, UOC – IN3.

Welcome to this new blog on Analytics and its social impact on Business, Smart Cities, and, specially, Education. In particular, through the opening question of the blog we are interested in analyzing how Analytics and Big Data are transforming our society, from the way people move around modern cities to the way governments and enterprises use customers’ data — sometimes crossing ethical boundaries — to infer and influence their behavior.

In effect, organizations have now access to an enormous amount of personal data describing our habits, tastes, and social or professional links. The proper combination of these data with current computing power and analytic methods allow these organizations to extract and infer individual and collective behavior patterns.

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About the Question
Are Big Data & Analytics shaping a smarter society?

Every day we generate a huge amount of big data, but we need to resort to analytics to make abstract information meaningful and get valuable knowledge from it. In education, learning platforms let us easily gather an immense quantity of data regarding students’ behaviour, interactions, preferences and opinions. When properly analysed — through learning analytics — all these data might provide useful insight on how to make learning processes more adaptive, attractive and efficient.

Are these techniques allowing us to provide better support to our students? Are we taking advantage of big data and analytics to help shape the citizens of the future?

Big Data and Simheuristics
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