Evaluation is central in research and development of information retrieval (IR). In addition to designing and implementing new retrieval mechanisms, one must also show through rigorous evaluation that they are effective. A major focus in IR is IR mechanisms' capability of ranking relevant documents optimally for the users, given a query. Searching for information in practice involves searchers, however, and is highly interactive. When human searchers have been incorporated in evaluation studies, the results have often suggested that better ranking does not necessarily lead to better search task, or work task, performance. Therefore, it is not clear which system or interface features should be developed to improve the effectiveness of human task performance. In the present article, we focus on the evaluation of task-based information interaction (TBII). We give special emphasis to learning tasks to discuss TBII in more concrete terms. Information interaction is here understood as behavioral and cognitive activities related to task planning, searching information items, selecting between them, working with them, and synthesizing and reporting. These five generic activities contribute to task performance and outcome and can be supported by information systems. In an attempt toward task-based evaluation, we introduce program theory as the evaluation framework. Such evaluation can investigate whether a program consisting of TBII activities and tools works and how it works and, further, provides a causal description of program (in)effectiveness. Our goal in the present article is to structure TBII on the basis of the five generic activities and consider the evaluation of each activity using the program theory framework. Finally, we combine these activity-based program theories in an overall evaluation framework for TBII. Such an evaluation is complex due to the large number of factors affecting information interaction. Instead of presenting tested program theories, we illustrate how the evaluation of TBII should be accomplished using the program theory framework in the evaluation of systems and behaviors, and their interactions, comprehensively in context.

In real-life, information retrieval consists of sessions of one or more query iterations. Each iteration has several subtasks like query formulation, result scanning, document link clicking, document reading and judgment, and stopping. Each of the subtasks has behavioral factors associated with them. These factors include search goals and cost constraints, query formulation strategies, scanning and stopping strategies, and relevance assessment behavior. Traditional IR evaluation focuses on retrieval and result presentation methods, and interaction within a single-query session. In the present study we aim at assessing the effects of the behavioral factors on retrieval effectiveness. Our research questions include how effective is human behavior employing search strategies compared to various baselines under various search goals and time constraints. We examine both ideal as well as fallible human behavior and wish to identify robust behaviors, if any. Methodologically, we use extensive simulation of human behavior in a test collection. Our findings include that (a) human behavior using multi-query sessions may exceed in effectiveness comparable single-query sessions, (b) the same empirically observed behavioral patterns are reasonably effective under various search goals and constraints, but (c) remain on average clearly below the best possible ones. Moreover, there is no behavioral pattern for sessions that would be even close to winning in most cases; the information need (or topic) in relation to the test collection is a determining factor.

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Real life information retrieval takes place in sessions, where users search by iterating between various cognitive, perceptual and motor subtasks through an interactive interface. The sessions may follow diverse strategies, which, together with the interface characteristics, affect user effort (cost), experience and session effectiveness. In this paper we propose a pragmatic evaluation approach based on scenarios with explicit subtask costs. We study the limits of effectiveness of diverse interactive searching strategies in two searching environments (the scenarios) under overall cost constraints. This is based on a comprehensive simulation of 20 million sessions in each scenario. We analyze the effectiveness of the session strategies over time, and the properties of the most and the least effective sessions in each case. Furthermore, we will also contrast the proposed evaluation approach with the traditional one, rank based evaluation, and show how the latter may hide essential factors that affect users' performance and satisfaction -and gives even counter-intuitive results.