Capturing Multi-Perspective Knowledge of Job Activitiesfor Training

Doctoral Consortium at EC-TEL 2010.

自然科学(总论);计算机科学

Dimoklis Despotakis1

Others  :  http://ceur-ws.org/Vol-709/paper04.pdf
PID  :  42035

来源: CEUR

【 摘 要 】

Using simulated environments for experiential learning gains a growing popularity in professional training.However, simulated contextcannot capture the complexity of real world activities, hindering the adaptationto individual learning needs and real world experiences.On the other hand,there is a vast amount of user contributed content about real world activitywhich represents different viewpoints and contexts.Although this content canbe a useful source for enriching the experiential learning experience insimulated environments, it has not been exploited to date.The main limitationsare the poor structure and the lack of approaches to retrieve the knowledgenuggets embedded in the existing digital content (e.g. videos or user stories)and to relate them to the simulated context.The aim of this doctoral project isto develop a novel approach for capturing multi-perspective knowledge of jobrelated activities from existing digital records and personal experiences.Theproposed approach aims at extracting an advanced context model which willaugment digital records of job activities with semantics, and will provideintelligent search to augment simulated context with real life experiences.