Abstract

Online help for learners can be classified along many dimensions including, passive to active, canned to knowledge-based, generic to task specific, collaborative to autonomous, and centralised to distributed. Across these dimensions, software tools that support online help employ techniques such as dialogue analysis, user modelling, context-specific inferencing, collaborative communication, and task-specific pedagogies. In this paper, we present a framework that seamlessly integrates help tools and techniques to facilitate three-way dialogues between a person who requires help (learner), a person who provides help (helper), and the online assistant help system (Helper's Assistant) that mediates between the learner and the helper. The focus of the framework is to provide personalised and context-specific help. We present a case for the need for such online assistants, review some of the key techniques employed in help systems, discuss the salient features of the framework in assisting online helpers, and describe the design and analysis of a study investigating the effectiveness of Helper's Assistant. The novelty in this approach lies particularly in the fact that the focus of the assistant is helping the helper and not the learner directly.

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