Athabasca University has made the commitment to put all of its courses online as part of its Strategic University Plan. In pursuit of this goal, it has participated in the eduSource project, a pan-Canadian effort to build the infrastructure for an interoperable network of learning object repositories based on and incorporating international standards and specifications . At AU, this initiative has brought together professionals, academics, and other researchers into a team that has synchronized the efforts of different university centers in the creation of a common enterprise-wide university repository for learning objects. The project participants have created open source applications and intelligent agents, as well as a suite of software tools that complement those of the other eduSource partners.
Athabasca University (AU), Canada's Open University, has been a partner in the pan-Canadian eduSource project, sponsored by CANARIE, Canada's advanced Internet development organization (CANARIE, 2004). AU, along with its five eduSource Canada partners, has built the components and best practice guidelines to develop the infrastructure for a pan-Canadian testbed of linked and interoperable learning object repositories, which are based on national and international standards.
AU has produced an open source suite of tools for creating learning object repositories. The applications are based on and incorporate international standards and specifications and include a learning object repository (LOR) input application called ADLib, a digital reading room (DRR), and an application for converting library records in MARC format to IEEE LOM records, which is the international standard for learning object metadata. There is an intelligent agent for enabling learners to quickly access answers to questions and other agents check for broken Web links and make recommendations to users. The software suite of tools includes Java bindings and interfaces to the LOR, as well as identification and validation services.
Here's a closer look at each of the offerings.
The Digital Reading Room
The AU Digital Reading Room (DRR) began as an online repository of reserve articles and other course materials that were tagged for use in specific courses. Development of the DRR had to meet the administrative and pedagogical needs of the AU users. Administrative users required a stable but flexible system, capable of incorporating different types of learning object resources into the DRR. Reliable authentication was considered essential, but ease of use, including a user-friendly method of data entry, modification, and retrieval were considered to be paramount by faculty. Student users also required stability and assured, reliable access to multiple types of learning resources at any hour, along with the capacity to connect, view, and/or manipulate search results. In March 2003, there were 40 Digital Reading Files (DRF) with 2,100 learning objects. By February 2004, there were 80 DRFs with 4,100 learning objects.
The DRR was originally based on an SQL database, running on a Linux server. The eduSource Canada Project brought to light a deficiency in the original DRR implementation. Namely, it was not interoperable with other repositories because it wasn't based on international standards. The implementers recognized the importance of rendering it interoperable using the IEEE LOM standard (IEEE 2003) based on the CanCore metadata implementation profile (Athabasca University 2004). At this time, further development of the DRR, other than essential operations, was suspended and work on an interoperable repository commenced. The DRR is being integrated into ADLib (Athabasca University Digital Library), which is presently based on a PostGreSQL database.
For more information on the DDR, visit http://library.athabascau.ca/drr.
AU has developed an IEEE LOM/CanCore-compliant metadata repository application called ADLib. ADLib is a Web application for creating and storing standards-compliant metadata records, and for storing their corresponding learning objects in the repository.
Full courses, units of courses, tutorials, and articles are all learning objects at different levels of granularity that can be stored in the repository. The learning object metadata is used for searching and accessing learning objects. Metadata is simply a description of the learning object and it contains information such as title, description, and keywords. The advantage of this approach is that once the learning object has metadata, they become searchable. The ADLib repository can also be used by authors to keep track of their own material (e.g., My Metadata and My Objects tools).
ADLib also facilitates the implementation of (and access to) single metadata records and learning objects. But, it also enables users to group records or objects or create relationships between different objects. For example, a group of objects can be linked together to form a lesson that is linked together to form a course. The course can then be related to a particular program. There are parallel relations among different LOM datasets or between the LOM records and the learning objects to which they refer.
ADLib also supports different modes, one for experienced users who are familiar with the IEEE LOM standard and another for novices. There are also tools for supporting different vocabularies. For example, ADLib provides the optional use of some AU-specific vocabularies along with IEEE LOM standard vocabularies. Vocabularies and modes can be easily set by the user.
Interoperability of both the metadata and the learning objects has been implemented at AU using Java Metadata software and Java Repository software. Presently code is available for linking to AU legacy systems, to CAREO (Campus Alberta Repository of Educational Objects), and to the CanLOM repository (formerly the TeleCampus).
For more information about ADLib, visit http://edusource.athabascau.ca/ADLib.html.
FAQ Intelligent Agent
AU developed an FAQ agent to aid users in answering frequently asked questions (FAQs) about eduSource, learning objects, the Digital Reading Room/ADLib, and the Library. FAQ agent users have the option of
- searching by keywords, phrases
- asking a question
- searching using natural language
- browsing a list of questions in the database and linking directly to the answer
- browsing the list of keywords in the database and linking to questions and answers containing these keywords.
The agent provides an online interface for administrators, the Webmaster, or course designers to manage (add, delete, classify, and modify) the content of the FAQ database storing question-answer pairs.
The success of a FAQ agent is dependent on a FAQ knowledge management system. FAQ knowledge is organized in a hierarchy for quick access. To be effective, the knowledge base must be populated and maintained with current and relevant content. We took an AU-centric approach to this challenge by creating state-of-the-art technology and augmenting it with an effective knowledge management process. The team combined the efforts of highly trained knowledge engineers with those of content experts who reviewed unanswered questions and worked to create new content to address these questions. They also adjusted the system configuration to improve search results. Because the FAQ agent is integrated with other AU and external repositories, the knowledge engineers were able to mine various logs for valuable content. This FAQ agent can be easily integrated with different learning management systems for quick implementation.
The FAQ agent is available at http://ADLibx.athabascau.ca/faqagent/jsp/kmanagement/faq.jsp.
Broken Link Checking Agent
The broken link checking agent consists of a spider-like checking agent and an online interface. The checking agent can monitor all the links on the page of a specific URL. The online interface is very simple. From the interface, users can cut and paste or enter a full URL that is of interest. Clicking on the "Submit" button activates it. If the agent detects any broken links in the Webpage of the URL, the URLs of the broken links will be displayed on the interface.
This agent is available at http://220.127.116.11:8080/examples/servlets/brokenlink.html.
Learning Object Recommendation Agent
This agent is designed to support the user in identifying and accessing learning objects according to personalized specifications that have been dynamically interpreted. The agent works on behalf of the user, monitoring the new arrival of learning objects in the learning object repository, notifying the user when relevant learning objects are deposited in the repository.
This agent is available at http://ADLibx.athabascau.ca/lora/jsp/lora/index.jsp.
Globally Unique Identifiers
Important work has also been completed on unique identifiers. On the Web, most documents are referenced (and linked to) by the URL representing their network location. This works reasonably well when a document only has a single location, but naturally leads to a number of problems when copies of a document are made available from multiple locations. A major objective of the eduSource project was to create a system of sharing and reuse among documents, making a single location for a document. Therefore, identification using location as the search criterion is not possible. This problem can be solved by assigning each document a globally unique label. Documents are then free to automatically replicate throughout the network, and links can be created using identifiers.
However, once you have a location-independent, globally unique identifier, you still ultimately need some location from which to actually retrieve that document. Given an identifier, a resolution service is needed to determine the location from which a client can retrieve a desired document. What factors are relevant to the design and implementation of a resolution service? Any robust solution needs the ability to scale globally. This generally means that, like the Internet itself, it needs to be distributed.
In the long run, you can't have one server resolving identifiers for everyone. A distributed system means you have no single point of failure, which creates fault tolerance, as well as scalability by dividing out the workload. A suitable architecture also needs to be open; it shouldn't force users into using any single implementation or proprietary or commercial technology. And the service needs to be available, or suitable for implementation, on a variety of hardware and software platforms. For these reasons, the service should be architected using existing standards wherever possible.
These open source applications, agents, and tools have been developed by AU as part of its obligations in the eduSource project and as part of its commitment to put all of its courses online as part of the Strategic University Plan. These are designed not only for the implementation of a learning object repository infrastructure at AU, but also to ensure the interoperability of AU's repository with other Canadian and international LOR initiatives. At AU, this initiative has been used to create the tools necessary for implementation as well as bringing together professionals, academics, and other researchers into a team that has synchronized the efforts of different university centres in the creation of a common enterprise wide university repository for learning objects.