Models of Information Seeking: The Standard Model vs. The Tetris Model

The standard model of information seeking, developed through observation, is one that outlines the basic actions involved in finding information. Variations of the standard information seeking model has been developed through work by Salton and Ennis, Shneiderman, and Broder, among others. The most developed model from Marchionini and White describes the information seeking process as:

• Recognizing a need for information
• Accepting the challenge to take action to fulfill the need
• Formulating the problem
• Expressing the information need in a search system
• Examination of the results
• Reformulation of the problem and its expression, and
• Use of the results

(Marchionini and White in Hearst, 2009)

An interesting criticism of this model came out last year in a paper by Max Wilson called “The Tetris Model of the Information Seeking Process”. The standard information seeking model sees users as formulating their queries, viewing their results, and reformulated their query ad infinitum as needed in a circular process until they reach their desired result. Wilson argues that the stages of information seeking don’t necessarily occur in a linear process but can be better visualized as a Tetris layout where information must be fitted together to reach a goal. In this model, progression, time, and movement between the different stages of information seeking are tracked independently. This model visualizes the quality and complexity of information through the depth of a Tetris block:

While Wilson relates the increasing speed of the Tetris game to the deadlines and time constraints that people face when searching, I see it as also representing the rate which users become familiar and proficient with the search interface. A game that doesn’t speed up could be seen as a metaphor for usability problems. While the model doesn’t assist with aspects of the information seeking process such as query formulation, it does provide new and novel way to visualize how we piece the information of multiple search results together to find an ultimate result.