Key Aspects of Cyberlearning Resources with Compelling Results


2013 ASEE Annual Conference, Atlanta, Georgia.

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2013 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference.



Thanks to resources like Scratch, PhET, and the Mobile Studio, cyberlearning is facilitating the development of 21st century skills. With these tools, learners are creating and sharing interactive media, manipulating computer simulations to understand physics in the world around them, and tweeting about the fascinating outputs generated by their personalized circuit boards. This is just a subset of the infinite possibilities cyberlearning affords, and Program Officers (PO) in the Division of Undergraduate Education (DUE) at the National Science Foundation (NSF) are interested in exploring more. Such interest was the impetus for this study.NSF defines cyberlearning as “the use of networked computing and communications technologies to support learning (NSF Task force on Cyberlearning, 2008, p.5). The positive outcomes of existing cyberlearning resources hint at the promise cyberlearning holds from satisfying DUE’s mission to promote excellence in undergraduate science, technology,engineering, and mathematics (STEM) education. As part of moving forward, however, there is a need to understand elements of the existing resources that have already achieved positive outcomes. Thus, the purpose of this study is to identify and highlight key elements of existing cyberlearning resources with compelling results.A sequential explanatory mixed methods research design (Creswell, 2011) was used to address this topic. Initially, a population of approximately 100 cyberlearning awards was generated from among over 1,000 NSF-funded projects POs have highlighted in the NSF Highlights over the past 10 years. Selection criteria were used to identify cyberlearning awards with compelling results to serve as exemplars. One-hour interviews were conducted with developers of the 15 cyberlearning resources selected to garner insights on their approached to development,implementation, and dissemination. Interview responses were analyzed by coding, and identify themes. Insights about their keys to the positive outcomes they have achieved will discussed in this paper.


2013, ASEE, cyberlearning

Date of this Version


This document is currently not available here.