Abstract
In the recent literature, many studies have addressed the evaluation of the user interface in interactive systems. However, there are few theoretically based methodologies for this purpose. This study is an attempt to develop a methodology for examining the complex division of information processing labor between user and computer. A special concern was the computer-naive user searching for information using a self-teaching system. Our test bed was an emergency poison information center whose functioning depended on fast, accurate processing of patient and antidote data by a nurse. We augmented the nurses' traditional information support--a manual card file and reference books--with an interactive software system which summarized and suggested inferences from data on past successful treatment of patients. Analysis of recordings of user comments and user-system interactions showed that: (1) the support system should be more robust and have more "reasoning" power; and (2) the users' expressed information needs changed after the new support was introduced. From the results, we abstracted elements of an effective naive user-support system division of labor: (1) the support system should "actively" help the user's error recovery; (2) the system should have a sufficient knowledge base to allow "intelligent" conversation about the problem domain; and (3) the support system should allow the user to reconceptualize his information problem as his environment changes. Our method of recording user-system interactions and verbal protocols was time consuming, but did yield significant insight into the user-system division of labor. Also, considering the poison center as a living system, analysis of processing by the nurse and the traditional, the new, or an envisioned information support system showed that a highly dispersed associator and effective internal transducer promoted the functioning of the entire group.
Published Version
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