Privacy-driven Design of Learning Analytics Applications - Exploring the Design Space of Solutions for Data Sharing and Interoperability

Studies have shown that issues of privacy, control of data, and trust are essential to implementation of learning analytics systems. If these issues are not addressed appropriately systems will tend to collapse due to legitimacy crisis, or they will not be implemented in the first place due to resistance from learners, their parents, or their teachers. This paper asks what it means to give priority to privacy in terms of data exchange and application design and offers a conceptual tool, a Learning Analytics Design Space model, to ease the requirement solicitation and design for new learning analytics solutions. The paper argues the case for privacy-driven design as an essential part of learning analytics systems development. A simple model defining a solution as the intersection of an approach, a barrier, and a concern is extended with a process focussing on design justifications to allow for an incremental development of solutions. This research is exploratory of nature, and further validation is needed to prove the usefulness of the Learning Analytics Design Space model.

[1]  Maren Scheffel,et al.  Developing an evaluation framework of quality indicators for learning analytics , 2015, LAK.

[2]  Helen Nissenbaum,et al.  Respect for context as a benchmark for privacy online: what it is and isn’t , 2015 .

[3]  Rebecca Ferguson,et al.  DCLA13: 1st International Workshop on Discourse-Centric Learning Analytics , 2013, LAK '13.

[4]  Tore Hoel,et al.  Privacy Requirements for Learning Analytics – from Policies to Technical Solutions , 2016 .

[5]  Daniel T. Hickey,et al.  Educational data sciences: framing emergent practices for analytics of learning, organizations, and systems , 2014, LAK.

[6]  Rebecca Ferguson,et al.  DCLA14: second international workshop on discourse-centric learning analytics , 2014, LAK.

[7]  Rebecca Ferguson,et al.  Setting learning analytics in context: overcoming the barriers to large-scale adoption , 2014, LAK '14.

[8]  Tore Hoel,et al.  Privacy in Learning Analytics – Implications for System Architecture , 2015 .

[9]  Kazunori Yamaguchi,et al.  Curriculum analysis of CS departments based on CS2013 by simplified, supervised LDA , 2015, LAK.

[10]  Paul Prinsloo,et al.  Student privacy self-management: implications for learning analytics , 2015, LAK.

[11]  Jennifer Heath,et al.  Contemporary Privacy Theory Contributions to Learning Analytics , 2014, J. Learn. Anal..

[12]  Mary Beth Rosson,et al.  The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing , 2011, Decis. Support Syst..

[13]  Maren Scheffel,et al.  Quality Indicators for Learning Analytics , 2014, J. Educ. Technol. Soc..

[14]  Martin Ebner,et al.  Seven features of smart learning analytics - lessons learned from four years of research with learning analytics , 2015 .

[15]  Tim Vogelsang,et al.  On the validity of peer grading and a cloud teaching assistant system , 2015, LAK.

[16]  Rebecca Ferguson,et al.  Ethical and privacy issues in the application of learning analytics , 2015, LAK.

[17]  Rebecca Ferguson,et al.  Social Learning Analytics , 2012, J. Educ. Technol. Soc..

[18]  Neil T. Heffernan,et al.  Towards better affect detectors: effect of missing skills, class features and common wrong answers , 2015, LAK.

[19]  Marc Langheinrich,et al.  Privacy By Design , 2013, IEEE Pervasive Comput..

[20]  V Buxton.  Visions for the future. , 1996, Nursing times.

[21]  Nick Eastmond,et al.  Ethics and Privacy. , 2003 .

[22]  Thomas P. Moran,et al.  Questions, Options, and Criteria: Elements of Design Space Analysis , 1991, Hum. Comput. Interact..

[23]  Larry Johnson,et al.  The NMC Horizon Report: 2012 Higher Education Edition. , 2012 .

[24]  Jon Mason,et al.  Questions as data: illuminating the potential of learning analytics through questioning an emergent field , 2016, Res. Pract. Technol. Enhanc. Learn..

[25]  Lorna Wong,et al.  Building institutional capacities and competencies for systemic learning analytics initiatives , 2014, LAK.

[26]  Alan R. Hevner,et al.  The Three Cycle View of Design Science , 2007, Scand. J. Inf. Syst..

[27]  Mandy Lupton,et al.  Learning analytics beyond the LMS: the connected learning analytics toolkit , 2015, LAK.

[28]  Samantha Adams Becker,et al.  NMC Horizon Report: 2014 K-12 Edition , 2010 .

[29]  Weiqin Chen,et al.  Learning Analytics Interoperability - looking for Low-Hanging Fruits , 2014 .

[30]  James E. Willis,et al.  Ethics, Big Data, and Analytics: A Model for Application , 2013 .

[31]  Mathieu d'Aquin,et al.  The 3rd LAK data competition , 2015, LAK.

[32]  Hendrik Drachsler,et al.  Privacy and Analytics – it’s a DELICATE issue. A Checklist to establish trusted Learning Analytics , 2016 .

[33]  Rebecca Ferguson,et al.  Learning analytics: European perspectives , 2015, LAK.

[34]  Phil Hodkinson,et al.  The interrelationships between informal and formal learning , 2003 .

[35]  Jenni Swenson,et al.  Establishing an ethical literacy for learning analytics , 2014, LAK.

[36]  H. Drachsler,et al.  Privacy and Learning Analytics - it's a DELICATE issue , 2016 .

[37]  George Siemens,et al.  Ethical and privacy principles for learning analytics , 2014, Br. J. Educ. Technol..

[38]  Hendrik Drachsler,et al.  The impact of learning analytics on the dutch education system , 2014, LAK '14.

[39]  Judy Kay,et al.  The LATUX workflow: designing and deploying awareness tools in technology-enabled learning settings , 2015, LAK.

[40]  Jon Mason,et al.  Data Sharing for Learning Analytics - Questioning the Risks and Benefits , 2015, ICCE 2015.

[41]  Ben Williamson,et al.  Digital education governance: data visualization, predictive analytics, and ‘real-time’ policy instruments , 2016 .

[42]  George Siemens,et al.  Learning Analytics , 2013 .

[43]  S. A. Becker,et al.  NMC Horizon Report: 2016 Higher Education Edition , 2015 .

[44]  Steven Lonn,et al.  Perceptions and use of an early warning system during a higher education transition program , 2014, LAK.

[45]  Martin Bichler,et al.  Design science in information systems research , 2006, Wirtschaftsinf..

[46]  Idabc.  European Interoperability Framework for Pan-European eGovernment Services , 2004 .

[47]  M. Perkins,et al.  Visions of the Future , 1996 .

[48]  E. Duval.  Attention please!: learning analytics for visualization and recommendation , 2011, LAK.

[49]  Mathieu d'Aquin,et al.  The learning analytics & knowledge (LAK) data challenge 2014 , 2014, LAK '14.

[50]  Peter Schaar,et al.  Privacy by Design , 2010 .

[51]  Nicolas Daclin,et al.  Framework for enterprise interoperability , 2006 .

[52]  Rebecca Ferguson,et al.  Social learning analytics: five approaches , 2012, LAK.

[53]  Pablo Garaizar,et al.  A multimodal learning analytics view of HTML5 APIs: technical benefits and privacy risks , 2014, TEEM '14.

[54]  Niall Sclater,et al.  Developing a Code of Practice for Learning Analytics , 2016, J. Learn. Anal..

[55]  Herbert Thomas,et al.  Learning spaces, learning environments and the dis'placement' of learning , 2010, Br. J. Educ. Technol..