Abstract:

Ensuring that courses touch upon desired goals and objectives is a problem that has long plagued instructional design. While keyword and metadata strategies have provided some benefit these methods suffer from a lack of robustness. As such, they provide only incremental improvements to what remains a highly manual process. A research team at American Public University System addressed these interrelated problems by employing an open source repository and semantic engine for analysis and alignment of content, materials, and learning activities across all courses within the School of Business. The result was a highly detailed, accurate mapping of the programs' knowledge base to established goals and objectives.

Content and activities from 29 courses in the APUS Business Program were federated in Common Library. Disaggregation of content yielded 5227 granular level assets and ontological ordering, using Dirichlet analysis, was conducted and categorical structuring was implemented using an iterative, multi-pass approach. A total of 538 goals and objectives, from both the program and course level, were input into the system. Using a natural language approach, these goals and objectives were specified as being representative of over-arching ontological structures.

By automating the meta-tagging and gap analysis process, semantic analysis allows one to not only smartly survey existing learning objects in a specific curriculum area, but examine more learning objects across unrealized curriculums. The ability to determine content interrelationships through the mapping of assets across the content universe enables one to effectively and efficiently facilitate object reusability towards curricular goal and objective fulfillment. This process allows for the actualizing of opportunities to locate learning objects to fulfill course level objectives for alignment across course level objectives, programmatic outcomes and industry standards. Improvement of instructional outcomes, through the ingestion of work products from implementation of content distillation and semantic analysis, increases return on investment and time on task. The opportunity to provide detailed analysis reporting that demonstrates curricular alignment to accrediting bodies and others is effectuated.

Keywords:

Semantic analysis, data driven decision making, curricular improvement.