The first International Conference on Learning Analytics & Knowledge (LAK) was held in 2011. The annual conferences were established to be:
“a premier research forum, providing common ground for academics, administrators, software developers and companies to shape and debate the state of the art in knowledge about learning analytics (LA).”
The LAK conferences are one of the major initiatives of SoLAR (the Society for Learning Analytics Research). According to SoLAR, the conferences (and the other SoLAR initiatives) we are exposed to an unprecedented explosion in the quantity and quality of information available not only to us, but about us. What adaptations are necessary individually, institutionally and culturally? What impacts do these transitions in technologies and social norms have? What are the implications of such data availability for learning and knowledge building in all possible contexts?
The topics at this year’s LAK2017 conference include:
LA Infrastructure, Modelling Student Behaviour, Students at-Risk – Studies, Improving Learning, Understanding Discourse I, LA Ethics, Understanding Student Behaviour – Multimodal Analytics, Self-Regulated Learning, Reflective Writing, Understanding Student Behaviour – Engagement, Learning Design, Understanding Discourse II, LA Policies, Teacher Support Tools I, Skill Assessment, Student Support Tools, Teacher Support Tools II, Feedback Systems, Understanding Discourse III, LA Adoption – Recommendations, Understanding Student Behaviour – General, Adaptive Learning, Understanding Student Behaviour – Help-Seeking / Search, Affective Learning, Students at-Risk – Systems, Retention, LA Adoption – Experiences
LAK2017 is hosted by the Faculty of Education at Simon Fraser University, in Vancouver, Canada. The Faculty is celebrating its 50th anniversary. It describes itself as being “a global education leader engaged in research and scholarly inquiry, committed to advancing knowledge and dedicated to improving the practice of teaching and the learning experience.”
SLATE is sending a team of researchers and students to the conference. They will present a full paper in a session on LA Policies and a research poster at the poster session. In addition, SLATE associated researchers are part of pre-conference activities. Grete Netteland is presenting iComPAss work in the pre-conference workshop on Writing Analytics Literacy – Bridging from Research to Practice and Weiqin Chen is organising a pre-conference workshop on Learning Analytics and Policy (LAP) – international aspirations, achievements and constraints. Learn more.
Paper (In the LA Policy Session):
“The Influence of Data Protection and Privacy Frameworks on the Design of Learning Analytics Systems” by Tore Hoel, David Griffiths, Weiqin Chen
Learning analytics open up a complex landscape of privacy and policy issues, which will influence how learning analytics systems and practices are designed. Research and development is governed by regulations for data storage and management, and by research ethics. Consequently, when moving solutions out the research labs implementers meet constraints defined in national laws and justified in privacy frameworks. This paper explores how the OECD, APEC and EU privacy frameworks seek to regulate data privacy, with significant implications for the discourse of learning, and ultimately, an impact on the design of tools, architectures and practices that now are on the drawing board. A detailed list of requirements for learning analytics systems is developed, based on the new legal requirements defined in the European General Data Protection Regulation, which from 2018 will be enforced as European law. The paper also gives an initial account of how the privacy discourse in Europe, Japan, South-Korea and China is developing and reflects upon the possible impact of the different privacy frameworks on the design of LA privacy solutions in these countries. This research contributes to knowledge of how concerns about privacy and data protection related to educational data can drive a discourse on new approaches to privacy engineering based on the principles of Privacy by Design. For the LAK community, this study represents the first attempt to conceptualise the issues of privacy and learning analytics in a cross-cultural context. The paper concludes with a plan to follow up this research on privacy policies and learning analytics systems development with a new international study.
“When Learning is High Stake”
Cecilie Johanne Slokvik Hansen, Barbara Wasson, Hans Skretting, Grete Netteland and Marina Hirnstein