Reusing database queries by adapting them to satisfy new information requests is an attractive strategy for extracting information from databases without involving database specialists. However, the reuse of information systems artifacts has been shown to be susceptible to the phenomenon of anchoring and adjustment. Anchoring often leads to a systematic adjustment bias in which people fail to make sufficient changes to an anchor in response to the needs of a new task. In a study involving 157 novice query writers from six universities, we examined the effect of this phenomenon on the reuse of Structured Query Language (SQL) queries under varying levels of domain familiarity and for different types of anchors. Participants developed SQL queries to respond to four information requests in a familiar domain and four information requests in an unfamiliar domain. For two information requests in each domain, participants were also provided with sample queries (anchors) that answered similar information requests. We found evidence that the opportunity to reuse sample queries resulted in an adjustment bias leading to poorer quality query results and greater overconfidence in the correctness of results. The results also indicate that the strength of the adjustment bias depends on a combination of domain familiarity and type of anchor. This study demonstrates that anchoring and adjustment during query reuse can lead to queries that are less accurate than those written from scratch. We also extend the concept of anchoring and adjustment by distinguishing between surface-structure and deep-structure anchors and by considering the impact of domain familiarity on the adjustment bias.
Conceptual modeling is fundamental to information systems requirements engineering. Systems analysts and designers use the constructs and methods of a conceptual modeling formalism to represent, communicate, and validate the contents, capabilities, and constraints of an envisioned information system within its organizational context. The value of such a representation is measured by the degree to which it facilitates a shared understanding among all stakeholders of (1) the organizational information requirements and (2) the ability of the envisioned information system to meet them [Wand and Weber, 2002]. We propose using the social ontology developed by John Searle [1995, 2006, 2010] as the basis for conceptual modeling and present a meta-model based on that ontology.
Information systems researchers frequently face quandaries in their professional lives. We present the results of a study of academic IS researchers that assesses their judgments and the prevalence of 29 questionable research-related behaviors. We find that the focus and stages of researchers' careers influence their judgments of these behaviors. Membership in the Association for Information Systems (AIS) and adherence to the AIS Code of Research Conduct are also associated with IS researchers' judgments. There is strong evidence to suggest that IS researchers expect to engage in questionable behaviors more in the future than they report having done in the past. As a result of the study, we recommend that the IS community revisit the AIS Code of Research Conduct on a regular basis and take active steps to both educate its members on professional normative standards and to uphold the standards of our community.
It is common for university students either to have introductory skills in the basic desktop software packages or to obtain these skills by self-study modules or short courses. What students lack is an understanding of how to use desktop packages effectively to improve their productivity. This is the missing link in the curriculum. This tutorial describes one solution: the IS'97.2 course on Personal Productivity with Information Technology. An appendix presents a sample lesson used with this course.
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