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2.5.1.1 Search tasks

Information seeking or searching actions are initiated to fulfill individuals’ information needs. Tasks reflect people’s information needs (Belkin et al., 1982; Ingwersen, 1992; Ingwersen & Järvelin, 2005). Thus information related behaviors need to be investigated and explained within the context of tasks (Byström & Hansen, 2005; Wildemuth & Hughes, 2005; Vakkari, 2003). Tasks also play an essential role in designing system functions and assessing system usability (Nielsen, 1989). Information systems are designed to serve

specific purposes by supporting certain tasks or subtasks. Task analysis is an important analytic tool for system design. GOMS, for instance, a widely recognized cognitive model to inform system design in HCI, functions by representing a set of tasks as Goals,

Operators, Methods, and Selection rules (Card, Moran, & Newell, 1983).

Tasks have different levels of granularity. In some studies, tasks are conducted to meet an overarching goal, such as writing a research proposal. The information searching process to accomplish this type of tasks is often very complex. A number of different subtasks, such as selecting the topic, articulating the problem, selecting sources, or

gathering information, can occur (Allen, 1996). Research questions concerning this type of task are preferably addressed by longitudinal studies.

Another type of task is often associated with specific communication media or information systems (Allen, 1996), and they are conducted to fulfill specific search goals. These tasks are often termed search tasks (Ingwersen, 2005; Vakkari, 2003; Wildemuth & Hughes, 2005). Search tasks could be natural search goals generated by subjects. The fully self generated tasks reflect searchers’ real information needs and maintain the context for information searching behavior. Search tasks also could be assigned by researchers.

Assigned tasks do not reflect the information needs of the subject, but they provide a useful means for researchers to control the effects of the tasks on search performance

(Hancock-Beaulieu, et al., 1996). In most IR experiments, search tasks are assigned tasks. In order to sustain the merits of both types of tasks, simulated search tasks have been

proposed (Borlund, 2000; Borlund & Ingwersen, 1997). In such tasks, researchers fabricate a realistic (though not real) scenario that may lead to information searching. Simulated search tasks allow individuals to interpret the situation and choose aspects of interest to them, as in real life tasks (Bilal, 2002; Vakkari, 2003).

2.5.1.2 Task complexity

Search tasks can be categorized based on different criteria in information behavior research, such as general vs. specific tasks (e.g., Qiu, 1993), topical vs. factual tasks (e.g., Kim, 2000), research vs. fact based tasks (Bilal, 2001), known item search vs. subject search (Kim & Allen, 2002), open vs. closed tasks (e.g., Marchionini, 1989b), and simple vs. complex tasks (e.g., Borgman, 1986; White, Ruthven, & Jose, 2005). Among these classifications, task complexity is the one that has been most implemented and discussed in the literature.

Different authors have used the term task complexity to refer to different constructs. Campbell (1988) defined task complexity based on four task related characteristics: multiple potential paths to a desired end-result, the presence of multiple desired outcomes, the presence of conflicting interdependence among paths to multiple outcomes, and uncertainty regarding paths. Rasmussen, Pejtersen, and Schmidt (1990) defined the complexity of a task based on the amount of information to be considered, the number of goals to be fulfilled, and the coupling of goals and contextual constraints. Byström and Järvelin (1995) defined task complexity as the predeterminability of information

requirements (what information is required), processes (how to find the information), and output of the task (how to assess relevance). In a less complex task, the types of task results, the associated work processes, and the output of the task are known by the searcher in advance; whereas in a complex task, none of the aspects are determined in advance. Marchionini (2006) defined the complexity of a task in terms of its cognitive demand. Based on the cognitive activities involved in tackling a task, he classified tasks as lookup tasks and exploratory tasks. Lookup tasks often have a definite answer and are less cognitively demanding, whereas exploratory tasks have less definite answers and require more complex cognitive processes such as analyzing, synthesizing, and evaluating information. Due to a higher demand on cognitive resources, exploratory tasks are more complex than lookup ones.

Task complexity is also a psychological experience (Campbell, 1998). Personal factors, such as the subjects’ prior knowledge and their search strategies, can affect their assessment of the complexity of a task (Vakkari, 1999). Bell and Ruthven (2004) considered task complexity as a measure of people’s uncertainty with a search task and pointed out that task complexity is a dynamic construct. It can be amplified or reduced by factors such as the searcher’s interest in the topic.

It is apparent that task complexity is a multidimensional construct. In empirical IR studies, different authors have characterized task complexity in different ways. Bilal (2000, 2001) used the number of facets involved in and the cognitive demand of a task to denote

task complexity. Complex research tasks had more facets and required more critical thinking than fact-based simple tasks. Bell and Ruthven (2004) implemented tasks with three levels of complexity based on criteria proposed by Byström and Järvelin (1995): subjects’ pre-knowledge about information requirements, search processes, and outcome of the task. White, Ruthven, and Jose (2005) determined task complexity by the number of potential information sources and types of information required. Capra et al. (2007) created three types of tasks with increasing levels of complexity based on three factors: the number of facets to be combined to get the result, the extent to which higher level thinking is required, and the navigation path to the result page.

2.5.1.3 Effects of task complexity on mental models

Characteristics of tasks have effects on mental models (van der Velden & Arnold, 1992). Savage-Knepshield (2001) has investigated the effects of task combinations on mental models. She found that subjects who performed the same task over two different trials (one week apart) did not increase their mental models on accuracy and completeness. However, improvement on mental models’ congruency was observed on subjects who performed different tasks in the two trials.

Mental models are dynamic. They are developed, validated, and modified during people’s interactions with systems as they complete particular tasks. These tasks provide a context for people’s information behavior, as well as for the construction of mental models. In other words, the development of a mental model is, at least, partially embedded in the

context of the current task. Certain aspects of the task will inevitably affect the development of mental models. However, these effects are heavily underresearched. Compared to the large amount of research on mental models’ effects on subjects’

performance on different types of tasks (e.g., Borgman, 1986), the research on tasks’ effects on mental models is sparse. Given the significant role that tasks play in information

searching and task performance (e.g., Bysträm & Järvelin, 1995; Kellar, Watters, &

Shepherd, 2007; Solomon, 2002), it is worthwhile to explore the effects of task complexity on people’s mental models of the system.