The state of knowledge-based systems
Communications of the ACM
Deep versus compiled knowledge approaches to diagnostic problem-solving
International Journal of Human-Computer Studies - Special issue: 1969-1999, the 30th anniversary
Explanations from knowledge-based systems and cooperative problem solving: an empirical study
International Journal of Human-Computer Studies
Constraint-Based Scheduling
The division of labor between human and computer in the presence of decision support system advice
Decision Support Systems
Navigation behavior models for link structure optimization
User Modeling and User-Adapted Interaction
The effects of transparency on trust in and acceptance of a content-based art recommender
User Modeling and User-Adapted Interaction
User interaction with user-adaptive information filters
UI-HCII'07 Proceedings of the 2nd international conference on Usability and internationalization
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This paper explores the interaction between human and artificial problem solvers when interacting with an Intelligent Scheduling System. An experimental study is presented aimed at investigating the users’ attitude towards two alternative strategies for solving scheduling problems: automated and interactive. According to an automated strategy the responsibility of solving the problem is delegated to the artificial solver, while according to an interactive strategy human and automated solvers cooperate to achieve a problem solution. Previous observations of end-users’ reactions to problem solving systems have shown that users are often skeptical toward artificial solver performance and prefer to keep the control of the problem solving process. The current study aims at understanding the role played by both the users’ expertise and the difficulty of the problem in choosing one of the two strategies. Results show that user expertise and task difficulty interact in influencing this choice. A second aspect explored in the paper concerns the context in which the end-users rely on explanations to understand the solving process. Explanations are in fact expected to play an important role when artificial systems are used for cooperative and interactive problem solving. Results support the hypothesis that explanation services are more often called into play in case of problem solving failures.