Affordances of machine-processable competency modelling
Onjira Sitthisak, Lester H. Gilbert · ePrints Soton (University of Southampton) · 2009
Existing e-learning competency standards such as the IMS Reusable Definition of Competency or Educational Objective (IMS RDCEO) specification and the HR-XML standard are not able to accommodate the level of a competency described separately from its narrative description; the grading scale of a competency; the success threshold of a competency; or the structure of competency trees or hierarchies. The proposed competency model addresses these problems and reflects all relevant features of the learner’s behaviour and their knowledge, skills, and attitudes that affect their learning and performance. Statements of competency are machine-readable. Machine processing can offer interoperable and reusable resources and applications that are pedagogically effective for e-learning and assessment. A competency statement which can be read, processed, and interpreted by machine contributes to the automatic generation of questions, distractors, and question sequences, and offers a semantic structure for further processing.