Fostering Information Seeking

Easiness of navigation within a website is an important factor for information seeking performance. Several cognitive models exist that simulate the web-navigation process. These models are based on different information processing components. In this paper we propose a new cognitive model, CoLiDeS++Pic (Comprehension-based Linked model of Deliberate Search), which uses information scent and path adequacy, applies backtracking, and also takes the semantics of pictures into consideration. We hypothesized that in this way information seeking performance can be better modeled when compared to previous models. This was verified by simulating the model on a mock-up website and comparing the results with previous models. The results support our hypothesis. We also present briefly the results of an experiment with tool-support based on the new model CoLiDeS++Pic. The results prove that model-generated support is fostering information seeking performance and helps in search tasks. We further discuss the challenges and advantages of automating navigation support using the proposed model.