Wilson et al. Wilson et al. speculated that two different ideas of uncertainty exist. Cognitive state uncertainty is associated with more rational judgements about the problem stages. Complex data collection during an empirical investigation of cognitive load will enable a data-driven model to be derived instead of a purely theoretical one. A wider range of task and cognitive data will be collected, enabling new components of cognitive load to be uncovered.
Cognitive load reduces as more domain knowledge is captured.
Cognitive load reduces as the user becomes more confident that their information need can be addressed. The figure below outlines our novel theoretical model of cognitive load for IR during the search process. Useful when domain knowledge is limited and prevents the user from generating their own terms for query expansion. Could be used as a precision tactic but negative relevance judgements are too discriminating within the Web search engine exact match environment. Judgement URF is useful when domain knowledge is sufficient to make accurate document relevancy judgements.