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To apply the concept of ill‐structured problems and learner expertise to the reference consultation.

Research literature from the 1960s forward regarding ill‐structured problems and learner expertise in a variety of disciplines was surveyed. Resulting characteristics of expert problem‐solvers were used to suggest applications to the reference consultation.

Librarians can structure the reference consultation to better meet students' needs as information problem solvers.

The method described appears to have sound basis in research into cognitive development and reflective thinking, but it has not been empirically demonstrated in the reference environment. Empirical research with reference librarians and students would be a logical next step.

Research into ill‐structured problems and learner expertise is ongoing in information retrieval systems. It has not been applied to the reference consultation.

The purpose of this paper is to develop a set of generic prompting principles and a framework of prompts that have the potential to foster learning and skill acquisition among adult novices when performing complex, ill-structured problems.

Relevant research in the literatures surrounding problem structure, sensemaking, expertise, metacognition, scaffolding, and cognitive load were reviewed and synthesised in order to derive generic prompting principles and guidelines for their implementation.

A framework of generic principles and prompts is proposed. Differentiation between prompts supporting cognition either within, or after an ill-structured problem-solving task was supported.

Prompts such as those proposed in the framework developed presently can be designed into technology-enhanced learning environments in order to structure and guide the cognitive processes of novices. In addition, prompts can be combined with other learning support technologies (e.g. research diaries, collaborative discourse) in order to support learning. Empirical testing will be required to quantify the potential benefits (and limitations of) the proposed prompting framework.

The prompts developed constitute a framework for structuring and guiding learning efforts in domains where explicit, actionable feedback is often unavailable. The proposed framework offers a method of tailoring the scaffolding of prompts in order to support differing levels of problem structure and may serve as the basis for establishing an internalised and adaptive learning approach that can be transferred to new problems or contexts.

This paper is an exploratory study of one approach to incorporating situational information into information retrieval systems, drawing on principles and methods of discourse linguistics. A tenet of discourse linguistics is that texts of a specific type possess a structure above the syntactic level, which follows conventions known to the people using such texts to communicate. In some cases, such as literature describing work done, the structure is closely related to situations, and may therefore be a useful representational vehicle for the present purpose. Abstracts of empirical research papers exhibit a well‐defined discourse‐level structure, which is revealed by lexical clues. Two methods of detecting the structure automatically are presented: (i) a Bayesian probabilistic analysis; and (ii) a neural network model. Both methods show promise in preliminary implementations. A study of users' oral problem statements indicates that they are not amenable to the same kind of processing. However, from in‐depth interviews with users and search intermediaries, the following conclusions are drawn: (i) the notion of a generic research script is meaningful to both users and intermediaries as a high‐level description of situation; (ii) a researcher's position in the script is a predictor of the relevance of documents; and (iii) currently, intermediaries can make very little use of situational information. The implications of these findings for system design are discussed, and a system structure presented to serve as a framework for future experimental work on the factors identified in this paper. The design calls for a dialogue with the user on his or her position in a research script and incorporates features permitting discourse‐level components of abstracts to be specified in search strategies.

This paper demonstrates the capability of staggered solution procedure for coupled fluid‐structure interaction problems. Three possible computational paths for coupled problems are described. These are critically examined for a variety of coupled problems with different types of mesh partitioning schemes. The results are compared with the reported results by continuum mechanics priority approach—a method which has been very popular until recently. Optimum computational paths and mesh partitionings for two field problems are indicated. Staggered solution procedure is shown to be quite effective when optimum path and partitionings are selected.

We extend the classical garbage can model to examine how individual differences in ability and motivation will influence organizational performance. We find that spontaneous coordination provided by an organized anarchy is superior when agents are equally competent. The Weberian bureaucracy of planned coordination is effective when problems require specialist knowledge. However, errors in matching problems to specialized agents are a central challenge for bureaucracies. Actual organizations, therefore, combine elements of organized anarchies and bureaucracies. Heterogeneous motivation compounds coordination problems, but is usually less important than competence. Our findings point to matching and interactive learning as fruitful areas for further study.

Problem‐solving techniques for poorly structured problems have been the subject of recent academic research and popular press texts. The purpose of this paper is to explain the use of one of the Theory of Constraints thinking process (TP) tools — the Current Reality Tree (CRT). The purpose of the tool is to clearly identify the root problem or problems that cause the surface problems or undesirable effects occurring in an organization.

One must fully understand the core problems in the environment before proposing a system solution to these core problems. Without this systems perspective, a proposed solution may create more problems than it solves. Through the use of an actual white‐collar service case, the paper explains how the CRT is created.

The overall objective of this research is not to propose solutions to the case but to demonstrate how the CRT might provide structure by identifying and logically linking the surface problems encountered in each area to the core problems. In this manner, the reader is introduced to the power of the CRT to address poorly structured problems.

The paper uses only one case as an example of the power of the TP tools. However, numerous testimonials from industry (many are cited in the text) provide evidence of the effectiveness of the TP tools.

The paper provides evidence that the TP tools might be an effective method to provide structure to ill‐structured problems which in many case have been addressed by management as if the problem were unstructured or, worse, unstructurable.

The paper is the first (to the authors' knowledge) to specifically address the issue of ill‐structured problems from the perspective that structure might be provided by the TP tools.

This paper has two parts, namely, Part 1 and Part 2. The purpose of this paper (Part 1) is to explain an adaptive relational paradigm that can efficaciously respond to the complex issues in wicked problems. A relational paradigm can work across the disciplines and fields that characterise wicked problems. It is also methodologically plural – that is it uses various inquiry instruments together. It becomes a hybrid approach when involving narratives and structured processes enabling the adopted instruments to converge to a coherent (living) story. The purpose of Part 2 will be to provide a theoretical framework that with illustration responds to Part 1.

Wicked problems and their issues do not respect academic disciplines, and as they are multidisciplinary, they require a cross-disciplinary approach when seeking resolution. Autonomous agency theory is adopted capable of structuring cross-disciplinary inquiry processes and formulating a hybrid inquiry paradigm. The paper sets up a narrative agency approachable of delivering a structure that results in a general theory of hybrid inquiry.

The paradigm, which traditionally defines a field of study conceptualises and regulates approaches that enable inquiry into behavioural systems. Mono-disciplinary, they are not suitable for the resolution of issues that arise from cross-disciplinary wicked problems. To resolve this, a relational paradigm has been defined within which sits a cross-disciplinary hybrid inquiry system. A general theory of hybrid inquiry has been offered. It is shown that agency theory can successfully embrace a relational paradigm.

To determine the limitations of this theory there is a need to provide exemplars, which is currently premature. Another outcome is to centre on modes of practice in hybrid inquiry, but there is insufficient space for this here.

This paper makes an original contribution by formulating a structured approach on the creation of a relational paradigm capable of supporting hybrid inquiry. It also adopts cross-disciplinary theory to make its case for a relational paradigm, recognising that wicked problems are cross-disciplinary. As part of the regulatory process, it connects Rittel’s IBIS schema intended to resolve wicked problems issues and the Johari Window and explains how they would relate. A means is suggested for determining the degree of undecidability of wicked problems issues, and hence, that of the models that inquiry produces. This uses formative characteristics that define a modelling space. The paper also adopts Husserl’s concept or lifeworld, which acts as a channel for complex narrative theory through which regulative processes are enabled.

In this study, the authors unpack the micro-level processes of knowledge accumulation (experiential learning) and knowledge application (problem solving) to examine how task allocation structures influence organizational learning. The authors draw on untapped potential of the classical garbage can model (GCM), and extend it to analyze how restrictions on project participation influence differentiation and integration of organizational members’ knowledge and consequently organizational efficiency in solving the diverse, changing problems from an uncertain task environment. To isolate the effects of problem or knowledge diversity and experiential learning, the authors designed three simulation experiments to identify the most efficient task allocation structure in conditions of (1) knowledge homogeneity, (2) knowledge heterogeneity, and (3) experiential learning. The authors find that free project participation is superior when the members’ knowledge and the problems they solve are homogenous. When problems and knowledge are heterogeneous, the design requirement is on matching specialists to problem types. Finally, the authors found that experiential learning creates a dynamic problem where the double duty of adapting the members’ specialization and matching the specialists to problem types is best solved by a hierarchic structure (if problems are challenging). Underlying the efficiency of the hierarchical structure is an adaptive role of specialized members in organizational learning and problem solving: their narrow but deep knowledge helps the organization to adapt the knowledge of its members while efficiently dealing with the problems at hand. This happens because highly specialized members reduce the necessary scope of knowledge and learning for other members during a certain period of time. And this makes it easier for the generalists and for the organization as a whole, to adapt to unforeseen shifts in knowledge demand because they need to learn less. From this nuanced perspective, differentiation and integration may have a complementary, rather than contradictory, relation under environmental uncertainty and problem diversity.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.

The primary objective of this research is to investigate the impact of task complexity on users’ performance in the context of using computer‐based technologies with auditing tasks. A laboratory experiment was performed with 121 undergraduate auditing students. The task complexity is defined in form of structured and unstructured tasks. The dependent variables were accuracy in solving problem and certainty of the correctness of solution. The results suggested that the effect of task complexity on accuracy in solving problems was significant for structured tasks. In addition, the significant effect was also found on certainty of the correctness of solution for structured tasks. The findings suggest the strategy for improving user performance in solving problem and certainty of the correctness of solutions toward a given task by giving users a structured task to perform. In addition, the findings also suggest the need for research on how to benefit from using computer‐based technologies in the context of solving structured task.