The State of Theoretical Diversity

Theory provides the medium for organizing and communicating knowledge that enables scientific collaboration. Review of five years of published work in two major IS journals, Management Information Systems Quarterly and Journal of Management Information Systems, describes the nature of this theoretical diversity in IS research. Two-hundred-seventy-three articles were evaluated for theoretical citations to identify the range of theories in Information Systems. Approximately half of the papers explicitly cited one of the 111 theories identified. Thirty of the theories were cited multiple times, representing 55% of the citations. The large number of theories used and the small number used more than once indicate that theoretical diversity clearly exists in information systems research. Based on the results, no theory emerged as a potential candidate for the role of grand/unified theory of information systems

Spreadsheet Accuracy Theory

Electronic spreadsheets have made a major contribution to financial analysis and problem solving processes. Decisions made using these tools often involve substantive consequences for the organizations. However, academic literature reveals that experienced professionals and students make many errors when developing spreadsheets. Practitioners recognize the importance of accuracy and have published many techniques they use for improving the accuracy of their spreadsheets. Systematic evaluation of this literature provides a basis for understanding practitioners’ perceptions of how and why errors occur in spreadsheets and is also valuable source from which to identify a theory of spreadsheet accuracy and capture the knowledge of experienced spreadsheet developers. The analysis of this literature suggests three categories of issues spreadsheet developers must address to create more accurate spreadsheets including: planning and design; formula complexity; and testing/debugging. Spreadsheet accuracy theory explains and predicts how changes in development processes can be expected to impact spreadsheet accuracy

Context Counts: Effects of Work versus Non-Work Context on Participants’ Perceptions of Fit in E-mail versus Face-to-Face Communication

There is a general need to understand better how context can affect evaluation, usage, and productivity of IT in research and practical settings. This paper investigates how perceived effectiveness of e-mail-style computer-mediated communication (CMC) differs between work and non-work contexts of use, and contrasts these differences with perceived effectiveness of face-to-face communication (FtFC). From the prior literature, we identified seven major activity domains that are prominent in CMC research. We developed a set of activity scales and corresponding measures of normative cognitive effort (NCE) for these domains and conducted an initial study to evaluate the overall instrument. In a second study, we measured perceived effectiveness of the communication mode within each activity domain among subjects who had communicated via e-mail and FtFC over a 15-week period. Some subjects communicated to support team-based software development (work context), and others communicated for personal interest (non-work context). We find communication technologies, activities, and contexts of use jointly determine perceived effectiveness; context influences perceived effectiveness primarily through interactions; and NCE successfully predicts perceived effectiveness based upon normative differences among activities. Our findings extend prior research in the area of task-technology fit to incorporate context effects, suggest that context is an important consideration in designing research, and introduce NCE as a method for predicting fit that can be applied even prior to system design. We conclude that the differential effects of work vs. non-work contexts are too large to be ignored, and we recommend an increased focus on context effects in CMC research and practice

The Role of Work Pressure in IT Task Groups: Identifying Theoretical Constructs

This paper introduces the study of group work pressure (GWP) in information technology (IT) task groups. We theorize that GWP arises from demands and resources in group work and that high levels of GWP inhibit group performance. To identify the constructs of a new group task demands-resources (GTD-R) model, we solicit subjects’ descriptions of factors associated with high and low pressure group work situations they have experienced. We find that GWP is composed of characteristics of the task, group, environment, and individuals in the environment. Group characteristics include expertise of the group, group history, and degree of interpersonal conflicts. Individual characteristics include task motivation, personal expertise, and positive/negative consequences. Task complexity, time pressure, and external resources available to the group complete the model tasks. The findings extend prior demands-resources research, suggesting a research model for future study and practical mechanisms for reducing undesirable effects of GWP

Integrating Computational Thinking into Information Systems and Other Curricula

Computational thinking (CT) is a fundamental skill needed to function in modern society. Despite widespread use of computers as productivity tools, existing curricula in information systems (IS) and other disciplines have not fully embraced CT concepts and skills. Increasing cross-disciplinary integration of CT into these curricula can help develop students’ problem-solving ability and provide educators with useful resources. Our collaborative initiative, named the Living in the Knowledge Society (LIKES) community building project, supports the integration of CT into college-level curricula by building a community of scholars and educators who will define the way to make systemic changes in how computing and IT concepts are taught and applied in both computing and other fields, thus better preparing the next-generation Knowledge Society builders. We describe the workshops, community-building activities, outcomes achieved, and case studies of developing teaching modules, curriculum guidelines, and teacher adoption strategies. Our work should benefit educators interested in integrating CT in their curricula, computing researchers interested in collaborating with other domain experts, and current students who aspire to become educators

LIKES: Educating the Next Generation of Knowledge Society Builders

Although information technology (IT) is used extensively in the education of all disciplines, the computing-related fields are facing tremendous challenges, such as declining student enrollment and a lack of representation from minorities and women. Strengthening the connection between computing and other fields could help instructors to integrate IT in their teaching and to support the learning of students, who will become the next generation of Knowledge Society builders. Presently, this connection is weak due to the lack of interdisciplinary collaboration and mutual understanding among faculty in computing and other fields. Our ongoing effort entitled “Living in the KnowlEdge Society (LIKES) Community Building Project” aims to build a community that will define a socially-relevant way to make systemic changes in how computing and IT concepts are taught and applied in both computing and other fields. In this paper, we review previous efforts in this area and summarize our project’s achievements and lessons learned. We also provide recommendations on integrating IT into other curricula and on strengthening interdisciplinary collaborations

CTRnet DL for disaster information services

We describe our work in collecting, analyzing and visualizing online information (e.g., Web documents, images, tweets), which are to be maintained by the Crisis, Tragedy and Recovery Network (CTRnet) digital library. We have been collecting resources about disaster events, as well as campus and other major shooting events, in collaboration with the Internet Archive (IA). Social media data (e.g., tweets, Facebook data) also have been collected and analyzed. Analyzed results are visualized using graphs and tag clouds. Exploratory content-based image retrieval has been applied in one of our image collections. We explain our CTR ontology development methodology an