Informal Learning, Cyberlearning and Innovative Education Diana G. Oblinger, Ph.D.

Emergent Unpredictable Self-organizing

Emerging educational ecology Learners have almost unlimited access to content, tools, resources, faculty, experts Research and scholarship have become more “conversational” Digital environments are places for scholarship Interdisciplinarity is growing Original research is conducted by “non-scholars,” e.g., undergraduates, citizen scientists Distributed access to resources ―Henry, 2009

Learning beyond the classroom Undergraduate students spend only 7.7% of their time in formal learning environments Grad students spend 5.1% in formal learning environments Who are the educators? ―Faculty ―Academic advisors ―Student affairs staff ―Students ―Community members —Dey, 2008

Finding information

Games and scientific thought 86% of comments aimed at analyzing rules of the game >50% used “systems-based reasoning” analyzing the game as a complex, dynamic system —Steinkuehler, 2008; image courtesy of Smith, % constructed specific models to explain behavior, often using the model to make predictions 25% of commentators built on someone else’s previous argument 25% issued rebuttals

Experiencing learning Problem-solving Virtual worlds Simulations Haptics Remote instruments ―Hackathorn, 2007; del Alamos, 2007; Bertolini, 2007

Community hubs nanoHUB Science gateway for nanotechnology Learning modules: lectures, podcasts Industry-level tools Community

Cyberlearning Access to educational resources, mentors, experts, online activities, virtual environments Engage with ―Scientific models ―Simulations ―Data sets ―Sensors ―Instruments —Borgman, et al., 2009

Engagement of distributed communities Virtual organizations Distributed across space: participants span locales and institutions (can include ‘citizen scientists’) Distributed across time: synchronous and asynchronous Computationally enabled: collaboration support systems Computationally enhanced: simulations, databases, analytic services Establishing trust, reputation —NSF, 2008

Data as an infrastructure ―Campolargo, 2008; Borgman et al., 2009 Large collaborations are emerging to collect and aggregate data Vast amounts of data allow use to ask new questions in new ways Learner data can be valuable to educators Policy issues emerge for using and managing data

Infrastructure for innovation Digital libraries ―Books, journals ―Artifacts ―Data sets Place for social interaction Community exchange Rapid prototyping Embedded sensors Computational approaches ―Henry, 2009

Policies needed Managing and using massive data stores Interoperability and common standards Open access to data and educational resources Identity management Security, privacy Confidentiality, FERPA Data breach policies Indemnification Sustainability plans