December 1, 2014
School Districts Pressure Publishers to Adopt Interoperability Standards
Several large US school districts are applying pressure to publishers to adopt interoperability standards, like those developed by the IMS Global Learning Consortium. The adoption of such standards would increase competition in the k-12 educational publishing space by preventing ‘lock-in,’ and increase freedom on the part of teachers to customize course content. Such standards would also lend themselves powerfully to the development of more versatile learning analytics tools.
December 4, 2014
White House Urges Colleges, Ed Tech Companies To Help Graduate More Students
The White House, during its second “College Opportunity Day of Action,” announces 600 new actions related to college preparation and completion. Important among its commitments is a push toward increasing investment and capability in the areas of predictive analytics and adaptive learning.
Student Privacy and Ethics
November 30, 2014
Whistle Blown on Womb to Workforce Data-Mining Scheme
Two groups, Pennsylvania Against Common Core and Pennsylvanians Restoring Education, are asking Gov. Tom Corbett to place a moratorium on data collection in the Pennsylvania Information Management System or PIMS. The system gathers information on students in all 500 school districts across the state and some schools have started collecting behavioral data that goes beyond testing for academic knowledge, according to the two organizations.
December 1, 2014
New South Wales Schools to Share Information on Expelled Students
Under new rules, struck by NSW Education Minister Adrian Piccoli, mean public, private and Catholic schools will share information about the background and past behavior of transfer students. The decision was justified by a sense of moral responsibility to students and stewardship in the use of tax-payer money. The new rules do not apply to independent schools
December 1, 2014
3 Lessons From Data on Children’s Reading Habits: Data from Accelerated Reader, a program used in schools, highlights trends in children’s reading habits.
Report on the results of mining data collected by Renaissance Learning on the reading activity of students outside of the classroom. Three major findings include: (1) girls read more than boys, (2) 15 minutes of reading a day is a ‘sweet spot’ in terms of promoting optimum learning gains, and (3) students benefit from taking on the challenge of books above their reading level.
Learning Analytics and Educational Research — What’s New? by Simon Buckingham Shum
A wonderful exercise in clarifying the distinctions between (1) educational and learning sciences research, (2) learning analytics research, and (3) learning analytics systems. One of the claims here is that learning analytics only begins to take place with the automation of coding and other research processes. When learning analytics is viewed in the tradition inaugurated by the Decision Support System (as, indeed, I am inclined to do), then I am inclined to agree that automation serves as a distinguishing feature.
ascilite 2014: ‘Rhetoric and Reality’ – critical perspectives on educational technology by Richard Walker
This summary of the ascilite 2014 conference opens with a summary of remarks made by Shane Dawson, Cathy Gunn, and Linda Corrin on the topic of learning analytics. Dawson delivered an event keynote, during which he warned of the danger associated with use of vendor-provided solutions without “some form of application to pedagogic interventions that change academic practice and enhance the student learning experience.” Gunn cautioned against the temptation to view data as providing a complete picture of students and their learning. Corrin mentioned that the use of student-facing dashboards raised ethical concerns, as well as concerns about mitigating ‘gaming’ behaviors, and observed that pilot data provided little evidence in support of the effectiveness of such tools in changing student behavior.
Online Education Run Amok?” Private Companies Want to Scoop Up your Child’s Data by Caitlin Emma
A compelling piece, reviewing the ways in which government and ed tech working in k-12, higher ed, and MOOCs are working to harvest student data amidst murky federal privacy laws. Citing David Hoffman (Global Privacy Officer, Intel), the piece concludes with the suggestion that next phase of educational data may not be marked by progress in predictive or analytics capabilities, but rather by advances in ethics.
Your Data Lack Value, and What You Can Do About It by Nick Sheltrown
The piece opens with the claim that “When it comes to data use in schools, our rhetoric outpaces reality. Even though many school districts lay claim to data-driven instruction, too often the expression serves only as a convenient slogan for school improvement plans, conference presentations, and accreditation documents.” Conceptually, ‘data-driven ________’ points to a basic misunderstanding about data science, by suggesting that data come first. Rather than start with the data, Sheltrown offers four basic steps that should define work with data: (1) articulate the information need, (2) identify the best measures, (3) develop processes, and (4) monitor data use for the sake of making adjustments as necessary.
What’s Wrong with Using Data to Grade Teachers? by Mercer Hall & Gina Sipley
The authors detail pushback against New York State’s new controversial teacher evaluation system. Value-added models (VAMs) aim to move beyond evaluation strictly based on student test scores, and instead to identify effective and ineffective teaching. whether this is a good idea or not, the implementation of the VAM rankings in New York has not only been reductionist, but also laughably poor in its execution.
Getting Privacy Policies Right…the First Time by Brenda Leong & Jules Polonetsky
Lessons that the education sector can learn from recent blunders from the private business sector: (1) Do not claim that you can simply change your policy at any time, (2) Do not simply say that if your company is sold, student data is an asset that will also be sold to the acquirer, and (3) Don’t disclaim responsibility for any third party code on your site.
Using Evidence of Student Learning to Improve Higher Education
George D. Kuh, Stanley O. Ikenberry, Natasha Jankowski, Timothy Reese Cain, Peter T. Ewell, Pat Hutchings, Jillian Kinzie
American higher education needs a major reframing of student learning outcomes assessment
Dynamic changes are underway in American higher education. New providers, emerging technologies, cost concerns, student debt, and nagging doubts about quality all call out the need for institutions to show evidence of student learning. From scholars at the National Institute for Learning Outcomes Assessment (NILOA), Using Evidence of Student Learning to Improve Higher Education presents a reframed conception and approach to student learning outcomes assessment. The authors explain why it is counterproductive to view collecting and using evidence of student accomplishment as primarily a compliance activity.
This paper discusses how educational policies have shaped the development of large-scale educational data and reviews current practices on the educational data use in selected states. Our purposes are to: (1) analyze the common practice and use of educational data in postsecondary education institutions and identify challenges as the educational crossroads; (2) propose the concept of Data Literacy (DL) for teaching (Mandinach & Gummer, 2013a) and its relevance to researchers and stakeholders in postsecondary education; and (3) provide future implications for practices and research to increase educational DL among administrators, practitioners, and faculty in postsecondary education.
Student Privacy in Learning Analytics: An Information Ethics Perspective
Alan Rubel & Kyle M. L. Jones
In recent years, educational institutions have started using the tools of commercial data analytics in higher education. By gathering information about students as they navigate campus information systems, learning analytics “uses analytic techniques to help target instructional, curricular, and support resources” to examine student learning behaviors and change students’ learning environments. As a result, the information educators and educational institutions have at their disposal is no longer demarcated by course content and assessments, and old boundaries between information used for assessment and information about how students live and work are blurring. Our goal in this paper is to provide a systematic discussion of the ways in which privacy and learning analytics conflict and to provide a framework for understanding those conflicts.
Consultation by Jisc with representatives from the UK higher and further education sectors has identified a requirement for a code of practice for learning analytics. The complex ethical and legal issues around the collection and processing of student data to enhance educational processes are seen by universities and colleges as barriers to the development and adoption of learning analytics (Sclater 2014a). Consequently a literature review was commissioned by Jisc to document the main challenges likely to be faced by institutions and to provide the background for a sector-wide code of practice. This review incorporates many relevant issues raised in the literature and the legislation though it is not intended to provide definitive legal advice for institutions. It draws from 86 publications, more than a third of them published within the last year, from a wide range of sources
Videos, Presentations, and Webinars
Advancing University Teaching with Analytics: Linking Pedagogical Intent and Student Activity through Data-Based Reflection
Calls for Papers / Participation
Workshop: It’s About Time: 4th International Workshop on Temporal Analyses of Learning Data @LAK15 Poughkeepsie, NY | 16 – 20 March, 2015 (SUBMISSION DEADLINE: 11 January 2015)
EDM 2015: 8th International Conference on Education Data Mining Madrid, Spain | 26 – 29 June, 2015 (SUBMISSION DEADLINE: 12 January 2015)
Workshop: Ethics and Privacy in Learning Analytics (#EP4LA) @LAK15 Poughkeepsie, NY | 16 – 20 March, 2015 (SUBMISSION DEADLINE: 15 January 2015)
Workshop: LAK Data Challenge 2015 Poughkeepsie, NY | 16 – 20 March, 2015 (SUBMISSION DEADLINE: 31 January 2015)
EDEN Annual Conference Barcelona, Spain | 9 – 12 June, 2015 (SUBMISSION DEADLINE: 31 January 2015)
The Fourth International Conference on Data Analytics Poughkeepsie, NY | 19 – 24 July, 2015 (SUBMISSION DEADLINE: 27 February 2015)
Journals / Book Chapters
Universities and Knowledge Society Journal (RUSC): Special Section on Learning Analytics (SUBMISSION DEADLINE: 20 January 2015)
Journal of Learning Analytics: Special Section on Multimodal Learning Analytics (SUBMISSION DEADLINE: 1 March 2015)
NYU Steinhardt School of Culture, Education,and Human Developments Center for Research on Higher Education Outcomes (USA)
12-month postdoctoral position – available for a qualified and creative individual with interests in postsecondary assessment, learning analytics, data management, and institutional research.The Postdoctoral Fellow will be responsible for promoting the use of institutional data sources and data systems for the purpose of developing institutional assessment tools that can inform decision making and contribute to institutional improvement across New York University (NYU). DEADLINE FOR APPLICATION: Open Until Filled
University of Boulder Colorado (Boulder, Colorado, USA)
Multiple Tenure Track Positions in Computer Science – The openings are targeted at the level of Assistant Professor, although exceptional candidates at higher ranks may be considered. Research areas of particular interest include secure and reliable software systems, numerical optimization and high-performance scientific computing, and network science and machine learning. DEADLINE FOR APPLICATION: Posted Until Filled
University of Michigan (Ann Arbor, MI)
Senior Digital Media Specialist – The University of Michigan is seeking a qualified Senior Digital Media Specialist to create digital content in support of online and residential educational experiences for the Office of Digital Education & Innovation (DEI). DEADLINE FOR APPLICATION: Posted Until Filled