In his Interfaces article [1994], Robert Levasseur emphasized the need for and importance of “people skills” for students today. While Levasseur discussed the need for students to acquire such skills as interpersonal communication, group dynamics, and leadership, to take it the next step, faculty members need a means to provide students with these essential skills. One such means, the cooperative learning model, provides a way for students to learn “people (or process) skills” as they are learning the content material of their chosen field of study. Cooperative learning is based on structuring learning outcomes and experiences to promote student interaction and to improve student learning. Ultimately, faculty members must consider what knowledge, skills, and abilities students need and how to best prepare them for the changing workplace.
In recent years there has been a tremendous increase in the development of Expert Systems (ESs) in organizations. This increased development is straining the already limited supply of qualified ES developers. These ES developers have come to be know as Knowledge Engineers (KEs), and their job as Knowledge Engineering. The process of Knowledge Engineering is divided into two tasks: Knowledge Acquisition (KA) and ES construction. KA has been defined as "The process of extracting, structuring, and organizing Knowledge from several sources, usually human experts, so it can be used in a program." (Waterman, 1986; p. 392) This process of KA has been identified as the "bottleneck" that currently constrains the development of ESs.This paper summarizes what is known about the KA process in an effort to identify what the key factors are that influence the success of the KA phase of the Knowledge Engineering process. Due to the similarities that exist between ESs and traditional systems development, the literature that pertains to traditional Information Requirements Determination and to Systems Analysts will be utilized to guide this exploration. Case study reports of actual ES development projects and the practitioner literature from this highly applied field will also be referenced. A model of the knowledge Engineering process has been developed and will be used to help determine and discuss the key factors that influence the KA process.Five key factors have been identified and will be discussed in detail. These factors are: the attributes of the participants in the ES development process; elicitation techniques utilized in the process; the development of external representations; representation selection problems; and the verification of the ES by the Domain Expert who participates in its continued development via the user-system interface. These factors are presented, key issues identified, and research questions suggested for each area.It is hoped that the analysis of the key factors in KA will lead to the identification of the skills and techniques necessary to successfully perform the KA process. Once these skills have been identified, training programs can be developed to help reduce the shortage of qualified KEs and, ultimately, facilitate the increased development of ESs in organizations.
Information Systems (IS) organizations have begun to search for ways to promote creative and innovative solutions to many of the problems they must address in today's dynamic business environment. The purpose of this paper is to describe how Groups Support Systems (GSS) can be used to promote creativity in IS organizations. A discussion of GSS concepts and tools is presented first. A model of the creative problem solving process in organizations is then described. An in-depth discussion of the benefits of using GSS to promote creativity as well as examples of actual and potential application of GSS tools for IS applications follows.Finally, limitations of current GSS, opportunities for the development of future GSS, and research directions for this area are presented. This paper concludes with a challenge to IS researchers and practitioners to investigate and explore the potential of GSS to promote creativity in IS organizations and to share their results.
Group Support Systems (GSS) and their effects on group processes and outcomes have been an object of intense study for 10 years. This article takes a different perspective on the involvement of GSS in research. The authors address how GSS tools can facilitate the process of developing and implementing research. A generic model of the research process is used to describe specific suggestions and examples-including three scenarios-for improving researcher efficiency and effectiveness. GSS can provide a variety of benefits to researchers, including basic meeting support for multiple researchers in developing elements of a research project; electronic recording of data from subjects; data analysis; and integration of information and data across the entire research process. Benefits of using GSS to facilitate/support the research process, the limitations of this approach, and the use of GSS to extend the research process beyond its current boundaries are reviewed
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