Modeling Successful Performance in Web Searching

Several previous studies have measured differences in the information search success of novices and experts. However, the definitions of novices and experts have varied greatly between the studies, and so have the measures used for search success. Instead of dividing the searchers into different groups based on their expertise, we chose to model search success with task completion speed, TCS. Towards this goal, 22 participants performed three fact-finding tasks and two broader tasks in an observational user study. In our model, there were two variables related to the Web experience of the participants. Other variables included, for example, the speed of query iteration, the length of the queries, the proportion of precise queries, and the speed of evaluating result documents. Our results showed that the variables related to Web experience had expected effects on TCS. The increase in the years of Web use was related to improvement in TCS in the broader tasks, whereas the less frequent Web use was related to a decrease in TCS in the fact-finding tasks. Other variables having significant effects on TCS in either of the task types were the speed of composing queries, the average number of query terms per query, the proportion of precise queries, and the participants’ own evaluation of their search skills. In addition to the statistical models, we present several qualitative findings of the participants’ search strategies. These results give valuable insight into the successful strategies in Web search beyond the previous knowledge of the expert–novice differences