OER and open licenses: the dual-pub solution

OER are teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use or re-purposing by others. The global standard for open licenses is the suite of Creative Commons (CC) licenses; however, there are several different types of CC licenses, and deciding which licenses are appropriate for different circumstances remains a significant point of contention for the OER community. Herein, we recommend that the debate shift focus, from "Which license?" to "Which assets (and when)?" It is widely understood that only the CC BY license (and, in certain circumstances, the CC BY-SA license) provides users with all of the necessary permissions to build on a global learning commons3. Thus, we recommend that OER be licensed CC BY plus in an open format, but we accept that resource publishers may only want to publish a subset of their assets as OER, thereby retaining additional rights on key assets for technical and business reasons. We believe that this approach substantially simplifies the OER landscape, gives clear opportunities to build sustainability and value-add models around OER publishing, and will ultimately increase the impact of OER in transforming educational access and practice

Towards a Global Learning Commons: ccLearn

Though open educational resources (OER) promise to transform the conditions for teaching and learning worldwide, there are many barriers to the full realization of this vision. Among other things, much of what is currently considered "free and open" is legally, technically, and/or culturally incompatible. Herein, the authors give a brief history of open education, outline some key problems, and offer some possible solutionsThis article was originally published in Educational Technology 4(6). Nov-Dec 2007

Enhanced Search for Educational Resources - A Perspective and a Prototype from ccLearn

Users of search tools who seek educational materials on the Internet are typically presented with either a web-scale search (e.g., Google or Yahoo) or a specialized, site-specific tool. The specialized search tools often rely upon custom data fields, such as user-entered ratings, to provide additional value. As currently designed, these systems are generally too labor intensive to manage and scale up beyond a single site or set of resources.However, custom (or structured) data of some form is necessary if search outcomes foreducational materials are to be improved. For example, design criteria and evaluative metrics are crucial attributes for educational resources, and these currently require human labeling and verification. Thus, one challenge is to design a search tool that capitalizes on available structured data (also called metadata) but is not crippled if the data are missing. This information should be amenable to repurposing by anyone, which means that it must be archived in a manner that can be discovered and leveraged easily.In this paper, we describe the extent to which DiscoverEd, a prototype developed by ccLearn, meets the design challenge of a scalable, enhanced search platform for educational resources. We then explore some of the key challenges regarding enhanced search for topic-specific Internet resources generally. We conclude by illustrating some possible future developments and third-party enhancements to the DiscoverEd prototype

Enhanced search for educational resources

The hurdle for those who seek educational resources on the Internet is not a lack of materials, but the difficulty of discovery of appropriate and desired materials.  Users of search tools who seek educational materials on the Internet are typically presented with either a web-scale search (e.g., Google or Yahoo) or a specialized, site-specific tool. The specialized search tools often rely upon custom data fields, such as user-entered ratings, to provide additional value. As currently designed, these systems are generally too labor-intensive to manage and scale up beyond a single site or set of resources. However, custom (or structured) data of some form is necessary if search outcomes for educational materials are to be improved. For example, design criteria and evaluative metrics are crucial attributes for educational resources, and these currently require human labeling and verification. Thus, one challenge is to design a search tool that capitalizes on available structured data (also called metadata) but is not crippled if the data are missing. This information should be amenable to repurposing by anyone, which means that it must be archived in a manner that can be discovered and leveraged easily. This paper describes the extent to which DiscoverEd, a prototype developed by ccLearn, meets the design challenge of a scalable, enhanced search platform for educational resources. We then explore some of the key challenges regarding enhanced search for topic-specific Internet resources generally. We conclude by illustrating some possible future developments and third-party enhancements to the DiscoverEd prototype. This report was researched and written by ccLearn, comprised in part of Ahrash Bissell (Executive Director) and Jane Park (Research Assistant and Communications Coordinator), and Creative Commons, comprised in part of Nathan Yergler (CTO) and Mike Linksvayer (VP

Architecture and Impact of an Open, Online, Remixable, and Multimedia-Rich Algebra 1 Course

The question we face is whether technology in general, and OER in particular, might offer some solutions for improving math scores across the nation

Web Syndication Approaches for Sharing Primary Data in "Small Science" Domains

In some areas of science, sophisticated web services and semantics underlie "cyberinfrastructure". However, in "small science" domains, especially in field sciences such as archaeology, conservation, and public health, datasets often resist standardization. Publishing data in the small sciences should embrace this diversity rather than attempt to corral research into "universal" (domain) standards. A growing ecosystem of increasingly powerful Web syndication based approaches for sharing data on the public Web can offer a viable approach. Atom Feed based services can be used with scientific collections to identify and create linkages across different datasets, even across disciplinary boundaries without shared domain standards