Facilitate Knowledge Acquisition Research Articles

Preceptor leadership style and the nursing practicum.

Preceptors are clinically based nurses that agree to participate with nursing students in an effort to provide them with opportunities to reinforce their knowledge with clinical experience. Preceptors serve as nursing role models to students and can facilitate their understanding and socialization into the reality of nursing. Studies on preceptorships have focused traditionally on the experience of precepting from the perspectives of student, employer, and preceptor. Literature related to methods for matching preceptors and students is very limited. Selection of preceptors to serve as role models for students should not be limited to clinical skill alone. Student learning and clinical experience can be influenced directly by the leadership characteristics that a preceptor possesses. To make the experience of precepting positive and beneficial for preceptor, student, and faculty, an examination and discussion of the potential preceptor's leadership style should be conducted. Situational leadership and the four different styles of leadership identified by Hersey and Blanchard provide a useful model for identifying leadership traits in preceptors that nursing faculty will find useful as they seek to match preceptors in a way that will facilitate knowledge acquisition and application for nursing students in the clinical setting.

Distributed Cognition in Shared Information Spaces

This study examined higher order perception, cognition, and individual-cultural differences as a basis for the rapid use of knowledge in complex problems requiring distributed team members. Previous research suggests that when complex problem-solving teams acquire perceptually anchored knowledge and engage in perceptual contrasts and comparisons, team members may spontaneously access knowledge given similarly situated problems. Our premise is that perceptual anchors may provide the basis for formulating shared mental models, which can be used to assess situations and resolve differences in individual, unique knowledge. However, distributed cognition settings may diminish the development of these models despite the advantages of perceptual anchors. Because distributed cognition often incurs through shared information spaces, this study utilized chatrooms to enact a distributed environment. Initial analyses partially support previous research (McNeese, 2000) that has examined the role of cognitive processes in facilitating knowledge acquisition and transfer. Individual problem solvers show positive transfer but distributed team members do not. Gender and ethnicity may also impact acquisition and transfer results. Results suggest the need for intelligent interfaces/collaborative technologies to improve effectiveness and efficiency in appropriating perceptual differentiation in distributed cognition.

Educating NHS Direct advisors to support the client with mental health problems: using role-play as a tool to facilitate skill acquisition

NHS Direct has been included in the Government plans to revolutionize Health Care Delivery. There has also been an emphasis placed on NHS telephone support for the mental health user. Mental health calls are a source of stress for NHS Direct Nurse Adviso rs, as only a small number are trained mental health nurses. This paper describes the role of education in helping overcome this stress by facilitating knowledge acquisition, skills attainment and confidence in the use of telephone intervention. Role-pla y is generally seen as a visual learning method. This paper outlines how to break this mould and use role-play as an audio teaching method for nurse advisors. The eventual aim is to provide a safe, sound and supportive service to the mental health user.

The Interaction Of Elaboration-Based Expert Systems And Cognitive Style On Knowledge Development

Expert system research in accounting has focused on knowledge transfer from the expert system to the user. This early research spurred studies on how to appropriately design an intelligent computer-based decision aid so as to positively affect the user’s development of knowledge. Researchers focused on the design of the user interface and pulled from research in cognitive psychology on knowledge acquisition. This research builds upon the existing literature by considering a factor that has yet to be examined, the user’s individual cognitive styles, which may be interacting with the expert system designs thereby affecting knowledge development. Prior research has shown that individuals have measurable differences in cognitive style. These differences have been shown to affect the development of knowledge. Cognitive fit between an expert system and the user may influence the user's reliance on the expert system. This, in turn, may affect knowledge development. This study examines the interaction of the individual’s cognitive style with a particular expert system design to determine whether or not the individual will attend to the expert system at a level great enough to facilitate knowledge acquisition and/or development. Knowledge development is a basic requirement in determining the success of an intelligent decision aid as discussed by Rose and Wolfe (1998). This study examines this interaction to ascertain whether a particular cognitive style is more compatible with expert systems.

Video modelling to educate patients.

Changes in health care delivery in the United States of America due to economic pressures have required nurses to develop innovative instructional materials for educating patients and families. Educational materials such as videotapes, specifically designed to provide information and promote active participation in treatment decisions, can be effective tools for empowering patients. A comprehensive analysis in 1988 concluded that the concept of 'video modelling' or 'behavioural modelling' offered the greatest benefit of videotaped presentations. The purpose of this integrative literature review was to examine the concept of video modelling and its applications in clinical practice. A computer search of the electronic databases of Medline and CINHAL between 1990 and 1999 produced a total of 40 research studies on video instruction for patients. Based on criteria for inclusion, 18 research studies involving video modelling were reviewed and three major uses were identified: (1) assisting decision making regarding treatment options; (2) reducing pre-procedural anxiety and improving coping skills; and (3) teaching self-care practices. The studies reviewed included a variety of research designs, clinical settings, and patient populations. Despite these differences, several benefits to the use of video modelling were found. Patients who viewed videotapes regarding treatment options had a greater understanding of the risks and benefits of those choices and were more apt to be active participants in decision making. Collective results of the studies focusing on stress and coping revealed that preparatory videotapes using video modelling could have a positive effect on reducing anxiety and physiological arousal during stressful procedures. With self-care practices, several of the studies found that there was an increase in desired behaviours in people whose educational programmes included video modelling. The use of video modelling has potential benefits for clinical practice in facilitating knowledge acquisition, reducing preparatory anxiety, and improving self-care. Nurses must become more actively involved in evaluating various teaching approaches used with patients to enhance practice and outcomes.

The effects of system design alternatives on the acquisition of tax knowledge from a computerized tax decision aid

Accounting firms are intensifying their reliance on experiential learning, and experience increasingly involves the use of computerized decision aids [Messier, W. (1995) Research in and development of audit decision aids. In R. H. Ashton & A. H. Ashton, Judgment and decision making in accounting and auditing (pp. 207–230). New York: Cambridge University Press]. Accountants are expected to learn from automated decision aid use, because the aids are not always available when dealing with the aid's topical matter, and the knowledge inherent in the aid is needed for competency on broader issues. To facilitate knowledge acquisition and explain the logic of the underlying processes, computerized decision aids provide the rationale for their calculations in the form of online explanations. We study how the location of explanations in a computerized decision aid affects learning from its use. Specifically, this research extends the existing literature by using a framework for the study of learning from decision aid use and by using cognitive load theory to explain the failure of certain decision aid design alternatives to promote learning. We define learning as the acquisition of problem-type schemata, and an experiment is performed in which cognitive load is manipulated by the placement of explanations in a computerized tax decision aid to determine its effect on schema acquisition. Schemata are general knowledge structures used for basic comprehension, and cognitive load refers to the burden placed on working memory when acquiring schemata. We find that increased cognitive load produced by the location of explanations in a decision aid leads to reduced schema acquisition. Our results indicate that when explanations in a computerized decision aid are integrated into its problem solving steps, cognitive load is reduced and users acquire more knowledge from aid use. This appears to be an important design consideration for accounting firms buying or building computerized decision aids.

Organizational Mechanisms for Enhancing User Innovation in Information Technology

Fostering information technology innovation has assumed primacy in discussions of information systems management. Changes in the nature of available information technologies and their potential applications underscore the importance of creating new knowledge for deploying a technology within an organization rather than transferring such knowledge from external sources. Technology users remain a largely untapped source for such knowledge creation. This paper argues that deliberate organizational design actions in the form of mechanisms can enhance technology users' propensity to innovate in information technology. Specifically, a taxonomy of organizational mechanisms is developed based on the ability of various mechanisms to facilitate knowledge acquisition and knowledge conversion. The conceptual taxonomy is populated with specific design actions described in the literature utilizing a Delphi study. The effects of various classes of mechanisms on three key antecedents of user propensity to innovate in IT: technology cognizance, ability to explore a technology, and intention to explore a technology, are tested using a field study. Results provide support for the conceptual taxonomy. Implications for theory and practice are offered.

Prospects for the use of corporate knowledge bases in the generation, management and communication of knowledge at a frontline agricultural research centre

The farming systems research and extension paradigm demands effective integration of knowledge from a range of sources in planning, implementing and evaluating research and extension activities. Constraints to improved research efficacy occur in relation to knowledge acquisition, storage and retrieval of knowledge and use of this information in planning research and in the production of research outputs. The development of knowledge bases through the application of knowledge-based systems technologies is posed as a partial solution to these constraints. Implementing this approach at a corporate level within front-line agricultural research centres may significantly facilitate knowledge acquisition, storage and access and its use in planning research and extension. This proposal is assessed through a needs analysis case study evaluation of flows of knowledge at Pakhribas Agricultural Centre, Nepal, a representative front-line national agricultural research centre.

Do Computer-Based Games Facilitate Knowledge Acquisition and Retention?

This study investigated the effects of a gaming approach on knowledge acquisition and retention in military trainees. Three groups of trainees were presented with subject matter in paper-based prose form (text), paper-based question-and-answer form (test), or computer-based gaming form (game). These conditions were selected to investigate potential benefits of computer-based gaming over traditional paper-and-pencil media in terms of trainee performance and reaction. Results showed that participants assigned to the game condition scored significantly higher on a retention test com- pared to pretest performance. Furthermore, participants assigned to the game condition scored significantly higher on a retention test than did participants assigned to the text condition. Participants assigned to the test and text conditions showed no benefit from training in performance at the retention test. In addition, participants assigned to the game condition rated the training they received as more enjoyable and more ef...

Towards method-independent knowledge acquisition

Rapid prototyping and tool reusability have pushed knowledge acquisition research to investigate method-specific knowledge acquisition tools appropriate for predetermined problem-solving methods. We believe that method-dependent knowledge acquisition is not the only approach. The aim of our research is to develop powerful yet versatile machine learning mechanisms that can be incorporated into general-purpose but practical knowledge acquisition tools. This paper shows through examples the practical advantages of this approach. In particular, we illustrate how existing knowledge can be used to facilitate knowledge acquisition through analogy mechanisms within a domain and across domains. Our sample knowledge acquisition dialogues with a domain expert illustrate which parts of the process are addressed by the human and which parts are automated by the tool, in a synergistic cooperation for knowledge-base extension and refinement. The paper also describes briefly the EXPECT problem-solving architecture that facilitates this approach to knowledge acquisition.

DETECTING DEVICE FAILURES THROUGH SCALE-DRIVEN OBJECT MATCHING

Abstract This article presents a method for detecting device failures using scale-driven object matching and discusses the use of this method to facilitate object-oriented device diagnosis. A device-independent class called scale, introduced to hide the method from the objects, provides abstraction mechanisms that facilitate knowledge acquisition and system integration. Using this class, plans for diagnosis can be generated from the mismatches resulting from comparing prototypical devices with faulty devices.

An investigation into knowledge acquisition using a group decision support system

Group Decision Support Systems (GDSS) previously have been used to facilitate a variety of group activities. This study explores the use of a GDSS to facilitate knowledge acquisition from multiple experts to build a help-service expert system for an information center. Observations from this study indicate that a GDSS can facilitate knowledge acquisition from a group of experts by documenting knowledge electronically, supporting parallel knowledge extraction from several experts, offering a structured process, and providing a collaborative atmosphere which facilitates group interactions, resolves conflicts, and enriches the domain of expertise. The findings show that structured analysis techniques are useful in planning for knowledge acquisition, the participation of end users is important, and that a designated primary expert is helpful when multiple experts are involved.

A model for critiquing based on automated medical records

We describe the design of a critiquing system, HyperCritic, that relies on automated medical records for its data input. The purpose of the system is to advise general practitioners who are treating patients who have hypertension. HyperCritic has access to the data stored in a primary-care information system that supports a fully automated medical record. HyperCritic relies on data in the automated medical record to critique the management of hypertensive patients, avoiding a consultation-style interaction with the user. The first step in the critiquing process involves the interpretation of the medical record in an attempt to discover the physician's actions and decisions. After detecting the relevant events in the medical record, HyperCritic views the task of critiquing as the assignment of critiquing statements to these patient-specific events. Critiquing statements are defined as recommendations involving one or more suggestions for possible modifications in the actions of the physician. The core of the model underlying HyperCritic is that the process of generating the critiquing statements is viewed as the application of a limited set of abstract critiquing tasks. We distinguish four categories of critiquing tasks: preparation tasks, selection tasks, monitoring tasks, and responding tasks. The execution of these critiquing tasks requires specific medical factual knowledge. This factual knowledge is separated from the critiquing tasks and is stored in a medical fact base. The principal advantage demonstrated by HyperCritic is the adaption of a domain-independent critiquing structure. We show how this domain-independent critiquing structure can be used to facilitate knowledge acquisition and maintenance of the system.

Structured matching: a task-specific technique for making decisions

All knowledge-based systems need to make decisions. Typically, these decisions involve selecting one choice out of a small number of alternatives based on a given set of parameters. The knowledge needed to make such decisions can often be expressed with a task-specific knowledge-based technique that we call structured matching, which integrates the knowledge and control for making a decision within a hierarchical structure. We show that structured matching is a common technique by documenting its use in several knowledge acquisition and knowledge-based systems. From a formal description of structured matching, we demonstrate why structured matching is so useful: it is tractable, it is applicable to classification and recognition tasks, and it facilitates knowledge acquisition. We conclude that structured matching is a ubiquitous and powerful technique for characterizing and constructing knowledge-based systems.

MOLE: a knowledge acquisition tool that buries certainty factors

MOLE is a knowledge acquisition tool for helping experts build systems that do differential diagnosis. Diagnostic expert systems often have to rely upon inferences that involve some degree of uncertainty. Typically, the tentativeness of the rules of inference is represented by certainty factors or some other cardinal measure of support. Unfortunately, this information is difficult to acquire from the experts. This paper describes how MOLE is able to dispense with certainty factors. By integrating into its problem-solving method several heuristic assumptions about how evidence relates to hypotheses, and by including in its knowledge acquisition process a way of generalizing the experťs preferences, MOLE does not need to elicit certainty factors from the domain experts or to internally represent the degree of support of an inference rule with certainty factors. This facilitates knowledge acquisition with no loss to diagnostic performance.

Sexuality of the aged and the attitudes and knowledge of nursing students.

Sexuality of the aged is one area of particular concern to nurse educators, because students' lack of knowledge and negative attitude can have far-reaching effects on nursing care of the elderly. This study examined the relationship of the dependent variables, attitude and knowledge, to the independent variables of ethnicity, age, experience in health care, family income, religious affiliation, religiosity, living arrangements, and level of education. One hundred fifty-eight female nursing students completed White's Aging Sexuality Attitude and Knowledge Scale. The study found that higher knowledge was related to more positive attitude scores (r = .25, P less than .004). Age was also significantly related to both positive attitude (r = .44, P less than .001) and higher knowledge (r = .54, P less than .001). Older students had a more positive attitude toward the elderly and were more knowledgeable about aged sexuality than younger students in the sample. One-way analysis of variance was used to test the significance between means of the dependent and independent variables. A statistically significant difference was found between ethnicity and attitude (f = 33.09, P less than .001) and ethnicity and knowledge (f = 18.36, P less than .001). Asian students in this study had a more negative attitude and were less knowledgeable about aged sexuality than Caucasian students. The study suggests that nurse educators need to pay special attention to the age and ethnicity of students when planning gerontological learning experiences designed not only to facilitate knowledge acquisition, but to promote positive attitudes toward the elderly.

Generic tasks as building blocks for knowledge-based systems: the diagnosis and routine design examples

AbstractThe level of abstraction of much of the work in knowledge-based systems (the rule, frame, logic level) is too low to provide a rich enough vocabulary for knowledge and control. I provide an overview of a framework called the Generic Task approach that proposes that knowledge systems should be built out of building blocks, each of which is appropriate for a basic type of problem solving. Each generic task uses forms of knowledge and control strategies that are characteristic to it, and are in general conceptually closer to domain knowledge. This facilitates knowledge acquisition and can produce a more perspicuous explanation of problem solving. The relationship of the constructs at the generic task level to the rule-frame level is analogous to that between high-level programming languages and assembly languages in computer science. I describe a set of generic tasks that have been found particularly useful in constructing diagnostic, design and planning systems. In particular, I describe two tools, CSRL and DSPL, that are useful for building classification-based diagnostic systems and skeletal planning systems respectively, and a high level toolbox that is under construction called the Generic Task toolbox.

MOLE: a knowledge acquisition tool that buries certainty factors

MOLE is a knowledge acquisition tool for helping experts build systems that do differential diagnosis. Diagnostic expert systems often have to rely upon inferences that involve some degree of uncertainty. Typically, the tentativeness of the rules of inference is represented by certainty factors or some other cardinal measure of support. Unfortunately, this information is difficult to acquire from the experts. This paper describes how MOLE is able to dispense with certainty factors. By integrating into its problem-solving method several heuristic assumptions about how evidence relates to hypotheses, and by including in its knowledge acquisition process a way of generalizing the experťs preferences, MOLE does not need to elicit certainty factors from the domain experts or to internally represent the degree of support of an inference rule with certainty factors. This facilitates knowledge acquisition with no loss to diagnostic performance.

Design for acquisition: principles of knowledge-system design to facilitate knowledge acquisition

The problem of knowledge acquisition is viewed in terms of the incongruity between the representational formalisms provided by an implementation (e.g. production rules) and the formulation of problem-solving knowledge by experts. The thesis of this paper is that knowledge systems can be designed to facilitate knowledge acquisition by reducing representation mismatch. Principles of design for acquisition are presented and applied in the design of an architecture for a medical expert system called MUM. It is shown how the design of MUM makes it possible to acquire two kinds of knowledge that are traditionally difficult to acquire from experts: knowledge about evidential combination and knowledge about control. Practical implications for building knowledge-acquisition tools are discussed.