Use cases
Several use cases inform the design and development of the DITA learning and training
specializations.
- Enable indexing, searching, and retrieval of learning content
- By structuring content with DITA topics and maps as self-contained learning objects that are matched with appropriate DITA metadata, it is possible to enable fast indexing, search, and retrieval of learning content that meets specific learning goals and objectives.
- Creating custom courses quickly
- A company has a large inventory of topic-based content that is used to provide technical and troubleshooting information about a set of componentized software products. The company wants to enable field engineers to quickly identify technical content that is suitable for providing on-site training. The DITA learning and training specializations enable field engineers to draw on their inventory of topics and quickly assemble learning content to meet specific customer needs.
- Making technical content available for direct sharing and reuse in learning and training
- A DITA learning specialization makes it possible to define a context for and directly assemble and use existing technical content for delivery as learning and training. The DITA approach identifies consistent structures and patterns and leverages them to enable a consistent approach for sharing content across teams. The result is much more opportunity to share content between different providers and across areas of expertise, to learn from each other, and to deliver content and the learning experience consistently. As a result, instead of copy, paste, and make unique as the norm, we have write once and share with others as the new norm.
- Creating tests and test preparation material
- A company publishes test preparation books that support students who are preparing for standardized tests. The company maintains a library of thousands of questions from which they can produce sample tests and set preparation materials for a specific test, grade level, region, and more. The company uses classifying metadata within the questions to associate them with the subjects, learning standards, grade levels, specific and standardized tests to which the questions apply. Using this metadata, they can quickly find relevant questions when developing new or updated publications. The questions include not just the question text but also indication of the correct answer, feedback for correct and incorrect answers, and feedback on the question as a whole. The learning interaction specializations make it possible to create and manage this library of questions. Because the interaction structures have been designed to be consistent with standards for electronic testing, the questions can be used to produce both print publications and interactive online learning and testing deliverables.