Is it ethical for marketers to ‘nudge’?

They almost got me.

As I reached for the gasoline nozzle, I realized at the very last minute that what I thought was regular gasoline was actually ‘plus,’ a grade that I did not want and that I would have paid a premium for. The reason for my near mistake? The way my options were ordered. I expected the grades to be ordered by octane as they almost always are. But in this case, regular 87 was sandwiched between two more premium grades.

The strategy that was employed at the pump at this Shell station in Virginia is an example of ‘nudging.’ It is an example of leveraging preexisting expectations and habits to increase the chances of a particular behavior. There is nothing dishonest about the practice. Information is complete and transparent, and personal freedom to choose is not affected. It is simply that the environment is structured in such a way as to promote one decision instead of others. 

Ethically, I like the position of Thaler and Sunstein when they talk about ‘libertarian paternalism.’ In their view, nudging can be a way to reconcile a strong belief in personal freedom with an equally strong belief that certain decisions are better than others. But not all nudges are created equal. Just as it is possible to promote decisions that are better for individuals, so too is it possible to increase the likelihood of choices that serve other interests, and that even serve to subvert the fullest expression of personal liberty, as in the gasoline example above.

One way to think of marketing is as the use of the principles of behavioral economics to change consumer behavior. Marketers are in the business of nudging. Because nudging has a direct impact in human behavior, it is also a fundamentally ethical enterprise. Marketing carries with it a huge burden of responsibility.

What ethical positions do you take in your marketing efforts? What would marketing look like if we were all libertarian paternalists?

This Week in Learning Analytics (November 1 – 7, 2014)

The Report to the European Commission on New Modes of Learning and Teaching in Higher Education recommends the fill and informed consent of all students who lend their data for the sake of educational purposes. (Image Source: Report to the European Commission on New Modes of Learning in Higher Education)

The Report to the European Commission on New Modes of Learning and Teaching in Higher Education recommends the fill and informed consent of all students who lend their data for the sake of educational purposes. (Image Source: Report to the European Commission on New Modes of Learning in Higher Education)


Latest News

7 November 2014
Microsoft and Other Firms Pledge to Protect Student Data
Fourteen companies, including Microsoft and Mifflin Harcourt, Amplify, and Edmodo, have pledged to adopt nationwide policies that will restrict and protect data collected from K-12 students. The group in pledging not to (1) sell student information, (2) target students with advertisements, or (3) compile personal student profiles unless authorized by parents or schools. The pledge, which is not legally binding, was developed by the Future of Privacy Forum.

6 November 2014
Lecturer Calls for Clarity in Use of Learning Analytics
Sharon Slade (Open University) talks about her university’s effort to develop and ethical policy on the use of student data, that attempts to carefully address conflicting student concerns: (1) concerns about institutional ‘snooping’ on the one hand, and (2) an interest in personalized modes of communication. The Ethical Use of Student Data for Learning Analytics Policy produced at the Open University is the first of its kind, and the result of an exemplary effort that should be repeated widely.

6 November 2014
Echo360 Appoints Dr. Bradley S. Fordham as Global Chief Technology Officer
Echo360, an active learning and lecture capture platform, has appointed Dr. Fordham as Global Technology Officer. With a wealth of industry and scholarly experience, Dr. Fordham will add significant expertise, legitimacy, and exposure to the platform. The this is the latest in a series of recent investments in developing the platform’s real-time analytics capabilities, which until recently, have been rather limited and unsophisticated.

6 November 2014
Harvard Researchers Used Secret Cameras to Study Attendance. Was That Unethical?
In the spring of 2013, cameras in 10 Harvard classrooms recorded one image per minute, and the photographs were scanned to determine which seats were filled. The study rankled computer-science professor, Harry R. Lewis, who viewed the exercise as an obvious intrusion into student privacy. George Siemens notes that attendance data is the ‘lowest of the low,’ and notes that the level of surveillance taking place in online courses far exceeds what was collected as part of the attendance-tracking exercise. Since Lewis raised his concerns, Harvard has committed itself to reaching out to every faculty member and student whose image may have been captured to inform them of the research, a not-so-easy effort, as images were captured anonymously and have subsequently been destroyed as part of the research methodology.

5 November 2014
Disadvantages Students in Georgia District Get Home Internet Service
Fayette County Schools in Georgia have partnered with Kajeet to give Title 1 students a Kajeet SmartSpot so that they can access online textbooks, apps, email, documents, sites, and their teachers while outside of school. The mobile hotspot works with the Kajeet cloud service and allows districts and schools to restrict access according to site- and time- base rules. The service also monitors student activity and provides teachers and administrators with learning analytics reports.

1 November 2014
Track Your Child’s Development Easily
In May 2011, Jayashankar Balaraman — a serial entrepreneur with a background in advertising and marketing — moved into the education space with the launch of KNEWCLEUS, which in just three years has grown to become India’s largest parent-school engagement platform. The platform’s success is a result of the ease with which it makes parent-teacher communication, and the analytics engine that monitors student performance, identifies areas in need of remediation, and recommends relevant content.

Latest Blogs

Does Exercise (and Learning) Count If Not Counted? by Joshua Kim
Kim asks the age-old question, “If I exercise and my fitness app does not record my steps, did my exercise ever happen?” He wonders about how the ability to track certain forms of activity, including learning activity, ends up altering behavior and shifting values on the basis of ‘trackability.’ The danger here, cautions Kim, is that we may come to conflate good teaching with digital practices that are more amenable to datafication.

Report on Modernisation of Higher Education: Focus on Open Access and Learning Analytics by Brian Kelly
A brief summary and review of the Report to the European Commission on New Modes of LEarning and Teaching in Higher Education, delivered in October 2014 by the High Level Group on the Modernisation of Higher Education. The report makes explicit mention of learning analytics, recommending collaboration over competition, and an increase in personalized learning informed by better data. The report’s advocacy of ‘better data’ includes strong ethical considerations, including the full and informed consent of students and the ability to ‘opt-out.’

10 Hottest Technologies in Higher Education by Vala Afshar
Afshar summarizes the hottest technologies discussed by CIOs at the 2014 Annual EDUCUASE conference last month. Included in the list are wifi, social media, badges, analytics, wearables, drones, 3D printing, digital courseware, Small Private Online Courses (SPOCs), and virtual reality. Although analytics is included as one of many trends, it of course is also a major driver for each of these technologies as well.

Schools keep track of students’ online behavior, but do parents even know? by Taylor Armerding
A truly exceptional review of literature and debates surrounding the collection and use of data from K-12 students. What kinds of data are a school’s ‘business’ to collect? How does an institution ensure informed consent, when privacy policies are often so complex as to be inaccessible by many parents? What is a school’s responsibility if it discovers something with implications for student success? Are schools ‘grooming kids for a lifetime of surveillance?’

Should Google Be a Signatory to Student Privacy Pledge? by Tracy Mitrano
Mitrano asks why the K-12 School Service Provider Pledge to Safeguard Student Privacy is not being more strongly considered in higher education, and asks why Google and Amazon have not publicly committed themselves to the pledge alongside Microsoft, Houghton Mifflin Harcourt, Knewton, and others.

Why I’m Voting ‘Yes’ on the Smart Schools Bond Act, Proposition 3 by Leonie Haimson
New York Proposition 3 (also known as the Smart Schools Bond Act) would allow the sale of bonds top generate $2 billion statewide for capital funding. In spite of her resistance to using bond revenue to purchase electronic devices in schools (one of the key ways in which the bond revenues are meant to be spent), Haimson notes the urgent need that many schools have for an injection of funding, and notes that the finds may be spent in a wide variety of ways. She raises a concern about the proliferation of technolgies driven by companies interested in educational data mining, but notes that, thanks to the Children’s Online Privacy Protection Act, all parents have the right to opt out of any online data-mining instructional or testing program that collects personal data, whether their children participate in this program at school or home.

Featured Videos, Presentations & Webinars

Carolyn Rosé: Learning analytics and educational data mining in learning discourses
Talk delivered to the International Society of the learning Sciences Network of Academic Programs in the LEarning Sciences (NAPLES). Click HERE for full Webinar Recording.

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Recent Publications

Embracing Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge
Leah MacFadyen, Shane Dawson, Abelardo Pardo, Dragan Gašević

In the new era of big educational data, learning analytics (LA) offer the possibility of implementing real–time assessment and feedback systems and processes at scale that are focused on improvement of learning, development of self–regulated learning skills, and student success. However, to realize this promise, the necessary shifts in the culture, technological infrastructure, and teaching practices of higher education, from assessment–for–accountability to assessment–for–learning, cannot be achieved through piecemeal implementation of new tools. We propose here that the challenge of successful institutional change for learning analytics implementation is a wicked problem that calls for new adaptive forms of leadership, collaboration, policy development and strategic planning. Higher education institutions are best viewed as complex systems underpinned by policy, and we introduce two policy and planning frameworks developed for complex systems that may offer institutional teams practical guidance in their project of optimizing their educational systems with learning analytics.

Learning Analytics: Challenges and Future Research Directions
Mohamed Amine Chatti, Vlatko Lukarov, Hendrik Thüs, Arham Muslim, Ahmed Mohamed Fahmy Yousef, Usman Wahid, Christoph Greven, Arnab Chakrabarti, Ulrik Schroeder

In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.

Calls for Papers / Participation

Conferences

2015 Southeast Educational Data Symposium (SEEDS) Emory University (Atlanta, GA) | 20 Feb 2015 (APPLICATION DEADLINE: 14 November 2014)

11th International Conference on Computer Supported Collaborative
Learning: “Exploring the material conditions of learning: Opportunities and
challenges for CSCL”
 
University of Gothenburg, Sweden | 7 – 11 June 2015 (SUBMISSION DEADLINE: 17 November 2014)

28th annual Florida AI Research Symposium (FLAIRS-28) on Intelligent Learning Technologies Hollywood, Florida, USA (SUBMISSION DEADLINE: 17 November 2014)

EDM 2015: 8th International Conference on Education Data Mining Madrid, Spain | 26 – 29 June, 2015 (SUBMISSION DEADLINE: 12 January 2014)

Journals / Book Chapters

Universities and Knowledge Society Journal (RUSC): Special Section on Learning Analytics (SUBMISSION DEADLINE: 20 January 2015)

Employment Opportunities

Simon Fraser University (Victoria, BC, Canada)
Tenure Track Position In Educational Technology And Learning Design – The Faculty of Education, Simon Fraser University (http://www.sfu.ca/education.html) seeks applications for a tenure-track position in Educational Technology and Learning Design at the Assistant Professor rank beginning September 1, 2015, or earlier. The successful candidate will join an existing complement of faculty engaged in Educational Technology and Learning Design, and will contribute to teaching and graduate student supervision in our vibrant Masters program at our Surrey campus and PhD program at our Burnaby campus. DEADLINE FOR APPLICATION: December 1, 2014

NEW! University at Buffalo (Buffalo, NY, USA)
Associate for Institutional Research/Research Scientist: Online Learning Analytics – The University at Buffalo (UB), State University of New York seeks a scholar in online learning analytics to join its newly formed Center for Educational Innovation. Reporting to the Senior Vice-Provost for Academic Affairs, the Center for Educational Innovation has a mission to support and guide the campus on issues related to teaching, learning and assessment, and at the same time serves as a nexus for campus-wide efforts to further elevate the scholarship of and research support for pedagogical advancement and improved learning. The Research Scientist in online learning analytics will work in the area of Online Learning within the department and join a campus-wide network of faculty and researchers working on “big data”. DEADLINE FOR APPLICATION: December 6, 2014

NEW! 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 Technology, Sydney (Sydney, AUS)
Postdoctoral Research Fellow: Academic Writing Analytics – Postdoctoral research position specialising in the use of language technologies to provide learning analytics on the quality of student writing, across diverse levels, genres and domains 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

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

This Week in Learning Analytics: Privacy and Ethics

DogDisguiseGregor Kennedy argues that the value of data lies, not only in opportunities for increased personalization within MOOCs themselves, but in their potential to inform decisions about more traditional learning environments as well. For the Chronicle of Higher Education, Jeffrey R. Young sat down for a conversation with L. Todd Rose to discuss the opportunities that data afford for personalizing content delivery, but also the challenges of data sharing, particularly in the case of MOOCs, where sharing of educational data is largely precluded as a consequence of existing business models. Lastly, in an article written for ACM Queue, Daries, et al add that the sharing of MOOC data is not only limited by business considerations, but also out of respect for student privacy. They observe that anonymization processes often function to radically undermine the possibilities for future analysis. The authors argue that, even if researchers can identify individuals and their actions, privacy can still be upheld by if those researchers are bound to an ethical and legal framework.

Another set of ethical issues that were raised this week involve the intersection of analytics and the humanities. Joshua Kim sparked a conversation about the place of analytics in the liberal arts. In the discussion following Kim’s post, greatest attention was paid to issues of definition: What is ‘assessment’? What are the ‘Liberal Arts’? (Mike Sharkey, for example, suggests that the liberal arts simply imply “small classes and a high-touch environment,” and argues that analytics offers very little value in such contexts. Timothy Harfield argues that the liberal arts provide a critical perspective on analytics, and are crucial to ensuring that educational institutions are learning-driven rather than data-driven). Lastly, in an article for Educause Review Online, James E. Willis discusses the failure of ethical discussions in learning analytics, and offers an ethical framework that highlights some of the complexities involved in the debate. He categorizes ethical questions in terms of three distinct philosophical perspectives, what he calls “Moral Utopianism,” “Moral Ambiguity,” and “Moral Nihilism.” The framework itself is at once overly pedantic and lacking in the clarity and sophistication that one would expect from a piece with tacit claims to a foundation in the history of philosophy, but nevertheless represents an interesting attempt to push the debate outside of the more comfortable legal questions that most often frame conversations about data and privacy.

Recent Blog Posts

Featured Articles

Privacy, Anonymity, and Big Data in the Social Sciences
Jon P. Daries, Justin Reich, Jim Waldo, Elise M. Young, Jonathan Whittinghill, Daniel Thomas Seaton, Andrew Dean Ho, Isaac Chuang

Open data has tremendous potential for science, but, in human subjects research, there is a tension between privacy and releasing high-quality open data. Federal law governing student privacy and the release of student records suggests that anonymizing student data protects student privacy. Guided by this standard, we de-identified and released a data set from 16 MOOCs (massive open online courses) from MITx and HarvardX on the edX platform. In this article, we show that these and other de-identification procedures necessitate changes to data sets that threaten replication and extension of baseline analyses. To balance student privacy and the benefits of open data, we suggest focusing on protecting privacy without anonymizing data by instead expanding policies that compel researchers to uphold the privacy of the subjects in open data sets. If we want to have high-quality social science research and also protect the privacy of human subjects, we must eventually have trust in researchers. Otherwise, we’ll always have the strict tradeoff between anonymity and science illustrated here.

Using Learning Analytics to Analyze Writing Skills of Students: A Case Study in a Technological Common Core Curriculum Course
Chi-Un Lei, Ka Lok Man, and T. O. Ting

Pedagogy with learning analytics is shown to facil- itate the teaching-learning process through analyzing student’s behaviours. In this paper, we explored the possibility of using learning analytics tools Coh-Metrix and Lightside for analyzing and improving writing skills of students in a technological common core curriculum course. In this study, we i) investigated linguistic characteristics of student’s essays, and ii) applied a machine learning algorithm for giving instant sketch feedback to students. Results illustrated the necessity of improving student’s writing skills in their university learning through e- learning technologies, so that students can effectively circulate their ideas to the public in the future.

Calls for Papers

CALL FOR CHAPTERS: Developing Effective Educational Experiences through Learning Analytics
Edge Hill University Press (ABSTRACT SUBMISSION DEADLINE: 15 September 2014)

CALL FOR PAPERS: 5th International Learning Analytics and Knowledge (LAK) Conference
Marist College (Poughkeepsie, NY) | 16-20 March 2015 (SUBMISSION DEADLINE: 14 October 2014)

Recommended Resources

swirl: Learn R, in R
swirl teaches you R programming and data science interactively, at your own pace, and right in the R console!

Upcoming Events

6-9 October 2014
Learning Analytics Week
École polytechnique fédérale de Lausanne

15 October 2014
ALE Speaker Series: Charles Dziuban on Engaging Students in an Engaging Educational Environment

Emory University (Streaming Available)

20 October 2014
Data, Analytics and Learning: An introduction to the logic and methods of analysis of data to improve teaching and learning

University of Texas Arlington | EdX

The Costs of Privacy

In November 2012, in response to threats of expulsion from John Jay Science & Engineering Academy on account of her refusal to wear a mandatory RFID badge, Andrea Hernandez filed a law suit against San Antonio’s Northside Independent School District. If she continues to refuse even to wear an RFID-disabled badge–an accommodation sanctioned by a federal district judge who ruled against her–Hernandez will be placed in Taft High School beginning in September 2013, the public school to which she would normally be assigned.

In refusing to wear even an RFID-disabled badge, Hernandez’s case seems to have lost its ‘bite’ (it’s difficult to justify her appeal to religious freedom once tracking mechanisms are disabled). In spite of the fact that her concerns were ultimately voiced in terms of an interest in preserving religious freedom, however, the case nonetheless draws attention to the potential costs of privacy.

As elite institutions increasingly adopt comprehensive analytics programs that require students to give up their privacy in exchange for student success, are they also strongly contributing to a culture in which privacy is no longer valued? A robust analytics program requires every student to opt-in (i.e. students are not given the option of opting out). If analytics programs are seen as effective mechanisms to increase the chances of student success, and such programs are effective only to the extent that they gather data that is representative of their entire student body, and, as such, consenting to being tracked is made a condition of enrollment at the most elite universities (universities with the resources necessary to build and sustain such programs), then students must ask what it is that they value more: an education at a world-class institution (and all of the job prospects and other opportunity that such an education affords), or the ability to proverbially click ‘do not track.’ My suspicion is that, if explicitly given the choice, the vast majority of students are willing to give up the latter for the former, a symptom of our growing acceptance of, and complacence toward, issues of electronic privacy, but perhaps also an indication that a willingness to sacrifice privacy for success increasingly forms a key part of the ‘hidden curriculum.’

Erasing Privacy

[Image Creative Commons licensed / Flickr user Alan Cleaver]

(Interestingly, in addition to gathering data from Learning Management and operational systems, universities also regularly collect data from student id card swipes. This data can easily be mobilized as part of a kind of ‘card-swipe surveillance’ program, as in fact has been done by Matthew S. Pittinksy (co-founder of Blackboard) at Arizona State University. According to Pittinsky, tracking card-swipe behavior can allow an institution to effectively map a student’s friend group, determine their level of social integration, and predict their chances of attrition.)