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Geospatio-temporal conceptual models provide a mechanism to explicitly represent geospatial and temporal aspects of applications. Such models, which focus on both "what" and "when/where," need to be more expressive than conventional conceptual models (e.g., the ER model), which primarily focus on "what" is important for a given application. In this study, we view conceptual schema comprehension of geospatio-temporal data semantics in terms of matching the external problem representation (that is, the conceptual schema) to the problem-solving task (that is, syntactic and semantic comprehension tasks), an argument based on the theory of cognitive fit. Our theory suggests that an external problem representation that matches the problem solver's internal task representation will enhance performance, for example, in comprehending such schemas. To assess performance on geospatio-temporal schema comprehension tasks, we conducted a laboratory experiment using two semantically identical conceptual schemas, one of which mapped closely to the internal task representation while the other did not. As expected, we found that the geospatio-temporal conceptual schema that corresponded to the internal representation of the task enhanced the accuracy of schema comprehension; comprehension time was equivalent for both. Cognitive fit between the internal representation of the task and conceptual schemas with geospatio-temporal annotations was, therefore, manifested in accuracy of schema comprehension and not in time for problem solution. Our findings suggest that the annotated schemas facilitate understanding of data semantics represented on the schema.

In this paper, we examine the state of computer science (CS) research from the point of view of the following research questions:1.What topics do CS researchers address? 2.What research approaches do CS researchers use? 3.What research methods do CS researchers use? 4.On what reference disciplines does CS research depend? 5.At what levels of analysis do CS researchers conduct research? To answer these questions, we examined 628 papers published between 1995 and 1999 in 13 leading research journals in the CS field. Our results suggest that while CS research examines a variety of technical topics it is relatively focused in terms of the level at which research is conducted as well as the research techniques used. Further, CS research seldom relies on work outside the discipline for its theoretical foundations. We present our findings as an evaluation of the state of current research and as groundwork for future CS research efforts.

In this paper, we examine the state of software engineering (SE) research from the point of view of the following research questions: 1. What topics do SE researchers address? 2. What research approaches do SE researchers use? 3. What research methods do SE researchers use? 4. On what reference disciplines does SE research depend? 5. At what levels of analysis do SE researchers conduct research? To answer those questions, we examined 369 papers in six leading research journals in the SE field, answering those research questions for each paper. From that examination, we conclude that SE research is diverse regarding topic, narrow regarding research approach and method, inwardly-focused regarding reference discipline, and technically focused (as opposed to behaviorally focused) regarding level of analysis. We pass no judgment on the SE field as a result of these findings. Instead, we present them as groundwork for future SE research efforts.

Object-oriented databases (OODBs) provide an effective means for capturing complex data and semantic relationships underlying many real-world database applications. Because users' interactions with databases have increased significantly in today's era of client–server computing, it is important to examine users' ability to interact with such databases. We investigated a number of factors that potentially affect performance in writing queries on an OODB. First, we evaluated the utility of graphical and textual schemas associated with emerging OODBs from the perspective of database querying. Second, we examined the use of two different strategies (navigation and join) that could be used in writing OODB queries. Third, we examined a number of factors that potentially contribute to the complexity of an OODB query. Our exploratory study examined the performance of 20 graduate students in an experiment in which each participant wrote queries for two problems, one using a graphical OODB schema and the other a textual OODB schema. The participants had no prior exposure to the object-oriented data model. We found that there was no difference in query writing performance (either accuracy or time) using the graphical and textual schemas. Examination of query strategy revealed that a significant number of participants used a join strategy, rather than the navigation strategy that matches the database structure. Use of the join strategy resulted in significantly less accurate and slower query writing than did the navigation strategy. From the viewpoint of complexity, the number of objects referenced in a query, the number of starting points in the “from” clause, and the presence of special operators influenced both the accuracy and time of query writing.

ERP implementations remain problematic despite the fact that many of the issues are by now quite well known. In this paper, we take a different perspective from the critical success factors and risks approaches that are common in the information systems discipline to explain why ERP implementations fail. Specifically, we adapt Sitkin’s theory of intelligent failure to ERP implementations resulting in a theory that we call “learning from failure.” We then examine from the viewpoint of this theory the details of two SAP R/3 implementations, one of which failed while the other succeeded. Although it is impossible to state, unequivocally, that the implementation that failed did so because it did not use the approach that was derived from the theory, the analysis reveals that the company that followed many of the tenets of the theory succeeded while the other did not.

Interruptions are a common aspect of the work environment of most organizations. Yet little is known about how interruptions and their characteristics, such as frequency of occurrence, influence decision-making performance of individuals. Consequently, this paper reports the results of two experiments investigating the influence of interruptions on individual decision making. Interruptions were found to improve decision-making performance on simple tasks and to lower performance on complex tasks. For complex tasks, the frequency of interruptions and the dissimilarity of content between the primary and interruption tasks was found to exacerbate this effect. The implications of these results for future research and practice are discussed.

We assessed the ability of the cognitive fit theory to explain the performance of certain display formats on multiattribute judgment tasks. This theory suggests that for most effective and efficient problem solving to occur, the problem representation and any tools or aids employed should all support the strategies (methods or processes) required to perform that task. The theory was tested by assessing performance with schematic faces, graphs, and tables on a bankruptcy prediction task. Bankruptcy prediction involves integrating a large amount of data (a number of financial indicators over a number of years), as well as referring to ranges and/or levels of financial indicators. Schematic faces provide a cognitive fit with such tasks since the information in a face can be processed holistically; however, they do not permit decision makers to refer to the underlying data. Graphs facilitate a different integrating process; further, they preserve characteristics of the underlying data. Tables, on the other hand, do not aid the decision maker in integrating information; they provide only the underlying data values. It was hypothesized that graphs would provide the best cognitive fit for the bankruptcy prediction task since they permit processing both integrated and discrete data. Participants made judgments with two of the three display formats, at two levels of information load, in a fractional factorial design. The information load manipulation was designed to provide meaningful and meaningful plus redundant information to the decision maker in a test of information load “per se.” The research findings provided substantial support for the theory of cognitive fit. The findings also have implications for the study of information load.

This article summarizes a workshop organized and conducted by the authors on April 1 and 2, 1993, under the auspices of Portland State University and the Oregon Center for Advanced Technology Education. This workshop provided a uniquely comprehensive and realistic look at the state of the art and practice of object-oriented programming. Issues discussed at the workshop and summarized here include the naturalness of object-oriented technology, reuse potential, programming support and evaluation tools, and the cost of converting to an object-oriented design technology. The findings should be of interest to researchers, organizations, and individuals who are exploring and/or using the object-oriented approach to software development. The article concludes by offering some recommendations for the use of objectoriented technology.

There are two conflicting views of the complexity of software development: ‘anyone can do it’, or ‘it is the most complex activity the human mind has ever undertaken’. We address this difference empirically in two exploratory studies that examined the intellectual (non-routine) and clerical (routine) nature of software tasks. The first study sought to determine the proportion of software tasks that can be regarded as intellectual or clerical in nature. Taxonomics of software tasks were classified based on the assessment of highly experienced raters. The second study examined the length of time novice systems analysts spent in carrying out tasks during the information requirements specification phase of the systems development life cycle. The experiment used protocol and videotape analysis. Results show that the numbers of intellectual tasks in software development, and the time spent on those tasks, both predominate over clerical tasks by 4 to 1. These initial results suggest that even simple tasks are more intellectual than the ‘anyone can do it’ or the ‘software development can be automated’ viewpoints frequently expressed in the literature.

A considerable amount of research has been conducted over a long period of time into the effects of graphical and tabular representations on decision-making performance. To date, however, the literature appears to have arrived at few conclusions with regard to the performance of the two representations. This paper addresses these issues by presenting a theory, based on information processing theory, to explain under what circumstances one representation outperforms the other. The fundamental aspects of the theory are: (1) although graphical and tabular representations may contain the same information, they present that information in fundamentally different ways; graphical representations emphasize spatial information, while tables emphasize symbolic information; (2) tasks can be divided into two types, spatial and symbolic, based on the type of information that facilitates their solution; (3) performance on a task will be enhanced when there is a cognitive fit (match) between the information emphasized in the representation type and that required by the task type; that is, when graphs support spatial tasks and when tables support symbolic tasks; (4) the processes or strategies problem solvers use are the crucial elements of cognitive fit since they provide the link between representation and task; the processes identified here are perceptual and analytical; (5) so long as there is a complete fit of representation, processes, and task type, each representation will lead to both quicker and more accurate problem solving. The theory is validated by its success in explaining the results of published studies that examine the performance of graphical and tabular representations in decision making.

This study presents theory that formalises, and generalises to problems of different levels of structure, the role of the application domain in IS problem solving. It does so by developing a unifying theory to explain the diverse findings from two experiments that focused on the role of the application domain in IS problem solving. The theoretical framework that we use to form the structure for our theory is a dual-task problem-solving model based on the theory of cognitive fit. Cognitive fit applies to problem solving in each of the contributing domains (application and IS), as well as to the interaction between the two. The theory of cognitive fit allows us to distinguish different types of interactions between the tasks that must be conducted in the IS and application domains when the two types of tasks 'match' and when they do not. Those interactions may be supportive, neutral, or conflicting, depending on whether the problem under investigation is well-or ill-structured.

A great deal of progress has been made in the computing field by studying solution approaches that are independent of the problem to be solved. But there is now general agreement that further such progress is becoming increasingly difficult; it is now vital to begin considering solution approaches that address the particular problem at hand. Such approaches are called "application-domain specific". Many communities within the field are addressing this problem. But how much progress are they making in coming up with domain-focused approaches? The authors address the status of each of several of those communities-domain analysis, patterns, architecture, method engineering, languages, and more. The paper shows that, while some progress is being made, much more is needed before the field can say it has made worthwhile inroads into the domain-focused approach.

The paper reports the results of an initial, exploratory investigation into the desired features of a work group support tool. A model of the type of support needed for systems development work groups in multiuser CASE tools was first developed. This model was then used to develop an evaluation instrument reflecting desired features of such tools. Finally, this instrument was used to assess the effectiveness of certain commercially-available CASE tools in supporting work groups. In general, support for work groups in the tools investigated was weak. The research also led to a model of work group support architecture. >

This paper takes a first step in aiding researchers to improve the relevance of their research to practice. By proposing that Information Systems researchers conduct applicability checks with practitioners on the research objects (for example, theories, models, frameworks, processes, technical artifacts, or other theoretically based IS artifacts) they either produce or use in theory-focused research, our paper presents an actionable, systematic approach to evaluating, establishing, and further improving research relevance. Furthermore, because it is an approach that can be conducted as an additional step either at the beginning or the end of the traditional research life cycle, it leaves untouched the rigorous methods used to conduct the study, that is, it does not compromise traditional research models. The approach we propose is based on the analyses of three dimensions of relevance that are critical to practitioners' attempts to internalize IS research findings (importance, accessibility, and suitability), and a comprehensive set of solutions that can be used to address them. Our analysis reveals that the most critical dimension for practice is the importance of the research to the needs of practice. The solution we propose to address that need is to conduct an applicability check on the research objects of interest. The applicability check forms an integral part of the research process, either prior to or following engagement in a typical research process. We present principles and criteria for the conduct and evaluation of an applicability check, which is primarily based on the focus group method, and secondarily on a modified nominal group technique.

Prior research supports the superiority of the nested conditional over the branch-to-label conditional. However, when examining programmer performance using these two forms of the conditional, the prior research has confounded several programming tasks. If these tasks are disentangled and programmers are trained to perform the tasks using language-independent paradigms, the relative performance of the nested conditional versus the branch-to-label conditional is no longer clear-cut.

In spite of the widespread acceptance by academics and practitioners of structured programming precepts, relatively few formal empirical studies have been conducted to obtain evidence that either supports or refutes the theory. This paper reviews the empirical studies that have been undertaken and critiques them from the viewpoints of the soundness of their methodology and their ability to contribute to scientific understanding. In general, the evidence supporting programming precepts is weak. A framework for an ongoing research program is outlined.

Expertise in a given domain is regarded as being manifested in the knowledge structures or chunks that experts possess. This research sought to use the chunking hypothesis of expertise, operationalized via computer program recall, to distinguish the more expert from the less expert computer programmers in a group of programming professionals. Two expertise levels were required to investigate differences in debugging processes of expert and novice programmers. The programmer classification produced by the recall pretest, however, explained little variation in debug time and the number of errors subjects made, when compared with a programmer classification based on the effectiveness of subjects’chunking processes. Subjects’ recalled programs were examined to determine whether the information structures in the program used for recall matched the declarative knowledge structures programmers could be expected to possess. Examination of the program suggests that programmers may not have been expected t...

There has been considerable interest over the years within the IS research community into how to shape articles for successful publication. Little effort has been made, however, to examine the reviewing criteria that make a difference to publication. We argue that, to provide better guidance to authors, more solid evidence is needed into the factors that contribute to acceptance decisions. This paper examines empirically the outcomes of the reviewing processes of three well-known IS conferences held in 2007. Our analyses reveal four major findings. First, the evaluation criteria that influence the acceptance/rejection decision vary by conference. Second, those differences can be explained in terms of the maturity and breadth of the specific conference of interest. Third, while objective review criteria influence acceptance/rejection decisions, subjective assessment on the part of the program committees may also play a substantial role. Fourth, while high scores on objective criteria are essential for acceptance, they do not guarantee acceptance. On the other hand, low scores on any criterion are likely to result in rejection.

The ability to estimate the personnel time and costs required for the completion of programming and systems projects is an important managerial tool for the information systems department. This article presents a survey of the estimation techniques found in the literature by describing each technique and discussing its strengths and weaknesses. Some empirical evidenc3e on how the various program and programmer/analyst characteristics affect project time and cost are also reported.

Information Systems (IS) is facing a dilemma: software is absorbing an ever-increasing portion of the total IS budget while maintenance is absorbing an ever increasing proportion of the software budget. In the not too distant future, unless this trend is arrested, or reversed, nearly all software resources may be required for maintenance. There are certain projected developments which give hope for the future ᾢ though not in the short term. In the meantime IS management must use other approaches, approaches that are available today, but that have been adopted very slowly. This article discusses one viable approach ᾢ the use of automated programmer productivity tools. It presents a classification of programmer productivity tools presently on the market and outlines the ways in which each class addresses productivity. It also discusses the important considerations IS management must make when evaluating the adoption of such tools.

Synthetic specimens of 1,3,6,8-tetramethoxyanthraquinone and its 4-methoxy and 4-methoxycarbonyl derivatives have been prepared for comparison with products derived from the degradation of the pigments of the crinoids, Comatula pectinata and C. cratera.