The 2016 convening assembled a small group of academic leaders to consider how data describing adult students might be managed in ways that enable the improvement of educational experiences, the progress of science, and the integrity of information describing human beings.  Co-hosted by Stanford University and Ithaka S+R, this event builds on the 2014 assembly that produced the Asilomar Convention for Learning Research in Higher Education of 2014.

Objectives of Asilomar II
— Enable a national peer review of how data describing adult students are produced and deployed at a wide range of academic institutions.
— Synthesize current best practices to specify norms for the ethical use of student data.
— Draft succinct statements to inform institutional, national and global policies regarding the research, application, and representation of adult student data.

Format and Outcomes of Asilomar II
Asilomar II is a working assembly.  At its core are three task groups, charged with developing general principles to inform policies and practices among organizations providing educational services.  Short draft documents, commissioned and distributed in advance of the physical convening, will provide starting points for in-person discussions.

Task group I: Research 
Convener: Tim McKay, University of Michigan
Educators are now obliged to continuously improve learning environments informed by systematic evidence. Digital technologies have brought many new mechanisms for producing, evaluating, and deploying such evidence.  Yet in order for relevant research to accumulate and develop into tractable insight, researchers must develop shared units of analysis and empirical and theoretical frontiers while safeguarding student privacy and discretion.

Task group II: Application
Convener: Sharon Slade, Open University UK
Advances in computational capacity and new data streams describing student behavior create extraordinary opportunities — even ethical obligations — to personalize and improve learning environments. While personalization has long been elemental to face-to-face teaching and advising, the use of algorithmic systems and predictive models through digital media brings capacity for personalization at mass scale. It also raises important dilemmas. What principles should educators apply when deciding who may know what about students?  What responsibilities does possession of this knowledge entail — for schools, businesses, instructors, and researchers? What sort of infrastructure is needed to realize the benefits of these technologies and ensure their appropriate use?

Task group III:  Representation

Convener: Tom Black and Helen Chen, Stanford University

Traditional college records represent student accomplishments as quasi-public records called “transcripts.” Students select courses while schools (and, increasingly, other kinds of organizations) control how evaluation is carried out and whether and how that evaluation is recorded into official documents. In light of exceptionally rich empirical information about educational environments, student behavior, and student learning now available through digital media, how is student accomplishment best and most ethically represented to others? What roles do students, schools, and other service providers play in deciding how myriad information describing students is related to official records? In an increasingly diverse ecology of educational provision, what makes a student record “official”?

For more information visit the 2016 Convening webpage.