CoLiDeS and SNIF-ACT : Complementary Models for Searching and Sensemaking on the Web

CoLiDeS and SNIF-ACT are empirically-validated, complementary models. SNIF-ACT applies rational analyses to information foraging anywhere on the Web. CoLiDeS describes how people attend to and comprehend information patches on individual webpages. Integrating CoLiDeS and SNIF-ACT would better predict how people forage the Web for information to solve everyday ill-structured problems. CoLiDeS and SNIF-ACT 2 CoLiDeS and SNIF-ACT: Complementary Models for Searching and Sensemaking on the Web Information foraging theory depicts the human species as hungry for information, and as Pirolli (2005) has perceptively pointed out, navigating the Web has become a common way to find information needed to solve such ill-structured everyday problems as selecting treatment for a medical condition. Information foraging theorists have used ACT-R spreading activation models of information scent to generate reliable predications of how people navigate the Web by following an information scent trail. They have used mathematical models from rational analyses to calculate and compare utility values and accurately describe how people decide which particular information patch to graze in, when to select links to move to another webpage, when to back up to a previously visited information patch, and when to abandon a website and search for a new and hopefully better information patch (Pirolli & Card, 1999; Pirolli, 2005). Although everyone has ill-structured everyday problems to solve, due to differences in background knowledge people vary enormously in their ability to comprehend the information available on the Web. Information foraging theory depicts people as hungry for information, but people in reality consume only information that they can comprehend. Information is useless to a person unless the person can comprehend the information. Due to differences in background knowledge people also vary in search strategies and attention management, ability to predict what links might be nested under superordinate categorical headings, and consequent ability to scan headings to identify what is in different patches. As a result of these differences in comprehension ability and attention management, people vary in both their ability to comprehend the information they find on the Web and their ability to find information by navigating the Web. Differences in background knowledge result from differences in culture, general reading knowledge, and amount of experience using Web browsers and computers, and researchers developing the CoLiDeS cognitive model and the Cognitive Walkthrough for the Web (CWW) have used the semantic spaces in Latent Semantic Analysis to generate reliable predictions for users that differ in general reading knowledge and culture (Blackmon, Mandalia, Kitajima, & Polson, 2007). The SNIF-ACT model (Pirolli, 2005; Pirolli & Fu, 2003; Fu & Pirolli, in press), exemplifies the information foraging and rational analysis approach to predicting information search behavior anywhere on the Web. In contrast, the CoLiDeS (Kitajima, Blackmon, & Polson, 2000, 2005) model exemplifies the comprehension-based approach to predicting information foraging behavior at the microcosmic level of individual webpages, building bottom-up from the perspective of actions taken on an individual webpage. Whereas SNIF-ACT is founded on the ACT-R computational model, CoLiDeS is founded on Kintsch's (1998) Construction-Integration model of text comprehension, action planning, and problem solving – useful for understanding how people solve such ill-structured problems as comprehending and selecting treatment for a medical condition. The core argument of this paper will be that integrating these two complementary, empirically well-validated models of Web navigation – CoLiDeS and SNIF-ACT – would improve our ability to predict information search and sensemaking on the Web for the full gamut of human users of varying abilities. Information foraging anywhere on the Web CoLiDeS and SNIF-ACT are complementary models, both starting with a user's goal to search for information. SNIF-ACT focuses on decisions to forage in a particular information patch, usually defined CoLiDeS and SNIF-ACT 3 as a complex website, or to leave the patch in search of patches of information with higher levels of information scent for the user's goal. As Figure 1 illustrates, an information patch can be defined at many different levels, from a particular website in the huge universe of websites on the Internet down to a collection of patches that compose a single webpage. SNIFACT computes the utility of staying within the current information patch compared to going back a page, clicking a link to go forward to a new page, or leaving the website. To date SNIF-ACT treats a webpage as a single information patch (Fu & Pirolli, in press), but there is no known barrier to extending SNIF-ACT to deal with a webpage as a collection of patches. In contrast, CoLiDeS considers the current webpage as a collection of patches – called subregions in earlier publications (e.g., Kitajima, Blackmon, & Polson, 2005) – and uses information scent to select which particular patch to forage. Figure 2 illustrates a collection of patches on a single webpage. When either CoLiDeS or a human user is drawn to a patch with high information scent for the goal, the consequences are good if the patch actually contains a link that is on the solution path. In many cases, however, a human user is drawn to a patch with high information scent, where there are multiple highscent links, none of which are on the solution path. This situation usually results in the user clicking many high-scent links that are not on the solution path (Blackmon et al, 2005, 2007). In these cases, information scent actively misleads the user, and the situation commonly occurs where items can be cross-classified but the Web designer makes the item accessible only by a link within one of categories. Two other closely related problems can shackle persons who follow an information scent trail. One is the problem posed when a "correct patch" has relatively high scent but the "correct link" within that patch has very weak scent. Based on the mathematical models of rational utility of when to abandon a patch – and confirmed by empirical evidence (Blackmon, Kitajima, & Polson, 2005) – weak-scent correct links pose serious difficulties because people tend to abandon the patch without clicking the weak-scent correct link. The second closely related problem – discussed in the next section – is that clusters of links are often highly general categories that have some information scent for most goals but relatively low scent for any one particular goal. This dilemma calls attention to even deeper problems of how people select patches anywhere on the Web, because (a) website-level patches will have very low scent, except for webpages deep in the hierarchy listed in the results webpages of a search engine like Google, and (b) information found by search engines like Google is liable to be very unreliable despite high scent. Figure 1. Information patches at all levels: individual websites within the universe of all websites on the Web, subsites, webpages, or patches within webpages CoLiDeS and SNIF-ACT 4 Figure 2. Patches within an individual webpage CoLiDeS and SNIF-ACT 5 Sensemaking for information foraging on the Web Information foraging theory draws from earlier models of foraging for food, and such models always take into account the nutritional content of the food – for example, calorie count, protein content, salt, minerals, and vitamins – and the tendency of organisms to avoid harmful constituents in the food source – for example, bacteria or toxins in the food or water that would cause the animal to become ill after eating the food. Sensemaking is a crucial element of information foraging, the analog of nutritional content of food and avoidance of constituents that would be harmful to the animal's health. CoLiDeS is founded in the construction-integration architecture for text comprehension, action planning, and problem solving. Based on a theory of comprehension we can make three claims about sensemaking in Web navigation: (a) information discovered through information foraging is worthless to a person unless the person has the background knowledge required to comprehend it, (b) unreliable, untrue information is harmful and should be avoided, and (c) inability to adequately comprehend links, headings, and/or page layout conventions can seriously lower a person's success in finding the information needed or desired for solving an ill-structured everyday problem (see evidence on unfamiliar links reported in Blackmon, Kitajima & Polson, 2005). Figure 2 shows an example of an unfamiliar link, "Oceania," that is unfamiliar even for college-level readers. The Oceania link is liable to cause problems for a user searching for trails in New Zealand, because even college-level readers are unlikely to know that New Zealand can be considered part of Oceania. Comprehension of the information found. In an extensive body of research, Kintsch has demonstrated the necessary role of background knowledge in constructing a situation model of the text. The situation model is required for text comprehension, for learning from text, for action planning and for problem solving (see review of this research in Kintsch, 1998). For example, in regard to finding information to solve the everyday ill-structured problem of finding information to select medical treatment, Patel and colleagues (e.g., Patel, Arocha, & Kushniruk, 2002) have documented patients' problems comprehending medical information about their condition, especially patients who have a narrative model of their disease and not a biomedical model like physicians and other medical professionals have. Reliability of the information found. As Bhavnani et al. (2003) have argued, background knowledge is also crucial for det