After a pilot program in four universities, big data technology that predicts which students are at risk of dropping out will expand across the UW System.

Some colleges, in an effort to sort through a growing number of applications, are quietly tracking applicants’ online interaction with the schools and considering it when deciding whom to admit.

It’s a lot easier to start college than to finish. Can big data help?

"Nudging" does not lead to improved outcomes in the case of "summer melt."

REALLY NICE overview of Big Data in education and why it's problematic.

Our laws offer students very little protection against the wiles of the technology industry.

Ethics and Information Technology - With the increase in the costs of providing education and concerns about financial responsibility, heightened consideration of accountability and results,...

Educational Technology Research and Development - The growth of learning analytics as a means to improve student learning outcomes means that student data is being collected, analyzed, and applied...

Students at the Secondary School of Journalism staged a walkout to get the “personalized learning” regimen removed from their classrooms.

Debate over the closure of DeVasco High School shows that data-driven accountability was a methodological and administrative processes that produced both transp...

Who Succeeds in Higher Education? Zoe Fisher The Academic Library in Times of Change California Academic & Research Libraries (CARL) Conference April 15, 2018 San Francisco, California Good morning, and thank you for the opportunity to be here to speak with you today. I am very grateful to the co...

This is a rough transcript of the plenary session presented to the California Academic & Research Libraries conference on April 15, 2018. The full paper is available with the conference proceed…

A key product of ubiquitous surveillance is people who are comfortable with it

MPs challenge company chair over trawling applicants’ social media to inform loan decisions

As higher education increasingly moves to online and digital learning spaces, we have access not only to greater volumes of student data, but also to increasingly fine-grained and nuanced data. A significant body of research and existing practice are used to convince key stakeholders within higher education of the potential of the collection, analysis and use of student data to positively impact on student experiences in these environments. Much of the recent focus in learning analytics is around predictive modeling and uses of artificial intelligence to both identify learners at risk, and to personalize interventions to increase the chance of success.  In this paper we explore the moral and legal basis for the obligation to act on our analyses of student data. The obligation to act entails not only the protection of student privacy and the ethical collection, analysis and use of student data, but also, the effective allocation of resources to ensure appropriate and effective interventions to increase effective teaching and learning.  The obligation to act is, however tempered by a number of factors, including inter and intra-departmental operational fragmentation and the constraints imposed by changing funding regimes. Increasingly higher education institutions allocate resources in areas that promise the greatest return. Choosing (not) to respond to the needs of specific student populations then raises questions regarding the scope and nature of the moral and legal obligation to act. There is also evidence that students who are at risk of failing often do not respond to institutional interventions to assist them.  In this paper we build and expand on recent research by, for example, the LACE and EP4LA workshops to conceptually map the obligation to act which flows from both higher education's mandate to ensure effective and appropriate teaching and learning and its fiduciary duty to provide an ethical and enabling environment for students to achieve success. We examine how the collection and analysis of student data links to both the availability of resources and the will to act and also to the obligation to act. Further, we examine how that obligation unfolds in two open distance education providers from the perspective of a key set of stakeholders - those in immediate contact with students and their learning journeys - the tutors or adjunct faculty.

As in many other fields that have been slow to change, the data revolution is coming for education.

Worcester Polytechnic Institute in Massachusetts will develop a neural network platform to deliver rapid feedback on student-teacher interactions.