Unifying the Complex Field of Learning Analytics

• In Event: 77.028 - Can Learning Analytics Improve Learning?

Abstract

Demonstrating the impact of learning analytics on learning and instruction across a wide range of contexts and categories of learners is a big challenge. To meet it successfully, the field of Learning Analytics will need to draw upon and find ways to synthesize the knowledge and skills of all its disparate participants, from teachers and administrators to cognitive scientists, educational measurement experts, educational policy researchers, and many others. If this unification across disciplinary lines were not to happen—if instead, LA remained an unfocused conglomeration of disconnected research and analytics groups, each making progress in its own silo but oblivious to the progress others have made—the field would not achieve what it could and in fact would hardly merit designation as an autonomous field.
Many new fields—for example, educational psychology, sociolinguistics, and bioinformatics—have formed in response to work happening at the intersection of two or more established fields, creating what Galison (1997, p. 783) calls ‘trading zones’, a metaphor he used to account for how physicists from different paradigms collaborated with each other and with engineers to develop particle detectors and radar, hammering out local co-ordinations even with quite different meanings assigned to the central objects or concepts being exchanged.
Historically, these combined fields have tended to follow development sequences described by Kuhn (1970) and others, growing and over time taking on the customary trappings of academic disciplines, including professional societies, conferences, journals, and degree programs. Learning analytics already shows many of these trappings, but its ambitions should go beyond just becoming an academic discipline: many in the field now want to see that LA makes a significant difference in education, with valid and compelling evidence for its impact, not simply hype.
This conceptually-oriented presentation will describe efforts to build capacity in the field for creating an innovative and sustainable ecosystem dedicated to advancing the state of learning data and analytics on behalf of all children’s college and career readiness. In particular, the presentation will briefly describe the foundational work done by the Learning Analytics Workgroup over several years, which will lead to discussion about how this work can be taken up and extended by anyone attending the session who may be interested.

Author

• Roy D. Pea, Stanford University