Application of expert systems in project management decision aiding

The feasibility of developing an expert systems-based project management decision aid to enhance the performance of NASA project managers was assessed. The research effort included extensive literature reviews in the areas of project management, project management decision aiding, expert systems technology, and human-computer interface engineering. Literature reviews were augmented by focused interviews with NASA managers. Time estimation for project scheduling was identified as the target activity for decision augmentation, and a design was developed for an Integrated NASA System for Intelligent Time Estimation (INSITE). The proposed INSITE design was judged feasible with a low level of risk. A partial proof-of-concept experiment was performed and was successful. Specific conclusions drawn from the research and analyses are included. The INSITE concept is potentially applicable in any management sphere, commercial or government, where time estimation is required for project scheduling. As project scheduling is a nearly universal management activity, the range of possibilities is considerable. The INSITE concept also holds potential for enhancing other management tasks, especially in areas such as cost estimation, where estimation-by-analogy is already a proven method

Using features for automated problem solving

We motivate and present an architecture for problem solving where an abstraction layer of "features" plays the key role in determining methods to apply. The system is presented in the context of theorem proving with Isabelle, and we demonstrate how this approach to encoding control knowledge is expressively different to other common techniques. We look closely at two areas where the feature layer may offer benefits to theorem proving — semi-automation and learning — and find strong evidence that in these particular domains, the approach shows compelling promise. The system includes a graphical theorem-proving user interface for Eclipse ProofGeneral and is available from the project web page, http://feasch.heneveld.org

Problem solving from textbook examples

There has been a great deal of research into students' use of examples when solving problems in textbooks. Much of this work has been within the framework of analogical problem solving (APS). Indeed many researchers believe they can build adequate models of how students learn and solve exercise problems by analogy to worked examples. In the first part of this thesis I argue that this view of problem solving from examples is inappropriate and often misleading. Most students learning a subject for the first time tend to imitate examples. Imitative Problem Solving UPS)is a weak form of analogical problem solving. APS accounts assume that a solver has a representation of an earlier problem in memory. The difficulties involved are accessing that source problem and adapting it to solve the current one. WS does not assume t at the source is represented in memory, and even when the source example is available( as in textbook examples), the student may not understand it well enough to be able to adapt it to new situations.The second part of the thesis presents an interpretation theory for analysing both texts and the behaviour of solvers using those texts to solve exercise problems.The third part applies the interpretation theory to the solution explanation of a simple algebra word problem. Where an example problem fails to map directly onto an exercise problem, or where inferences have to be made to understand it, the solver win be unable to imitate the example and hence will have difficulties in proportion to the mapping inequalities between the two problems. That is, the interpretation theory allows us to predict precisely where solvers will have difficulty using an example to solve an exercise problem of the same type.The final part presents experimental tests of these predictions. The results confirm that the interpretation theory analysis can correctly identify possible areas of difficulty for the student due to a) the way an example problem is structured, and b) the nature of the transfer task

A study of novice programmer performance and programming pedagogy.

Identifying and mitigating the difficulties experienced by novice programmers is an active area of research that has embraced a number of research areas. The aim of this research was to perform a holistic study into the causes of poor performance in novice programmers and to develop teaching approaches to mitigate them. A grounded action methodology was adopted to enable the primary concepts of programming cognitive psychology and their relationships to be established, in a systematic and formal manner. To further investigate novice programmer behaviour, two sub-studies were conducted into programming performance and ability. The first sub-study was a novel application of the FP-Tree algorithm to determine if novice programmers demonstrated predictable patterns of behaviour. This was the first study to data mine programming behavioural characteristics rather than the learner’s background information such as age and gender. Using the algorithm, patterns of behaviour were generated and associated with the students’ ability. No patterns of behaviour were identified and it was not possible to predict student results using this method. This suggests that novice programmers demonstrate no set patterns of programming behaviour that can be used determine their ability, although problem solving was found to be an important characteristic. Therefore, there was no evidence that performance could be improved by adopting pedagogies to promote simple changes in programming behaviour beyond the provision of specific problem solving instruction. A second sub-study was conducted using Raven’s Matrices which determined that cognitive psychology, specifically working memory, played an important role in novice programmer ability. The implication was that programming pedagogies must take into consideration the cognitive psychology of programming and the cognitive load imposed on learners. Abstracted Construct Instruction was developed based on these findings and forms a new pedagogy for teaching programming that promotes the recall of abstract patterns while reducing the cognitive demands associated with developing code. Cognitive load is determined by the student’s ability to ignore irrelevant surface features of the written problem and to cross-reference between the problem domain and their mental program model. The former is dealt with by producing tersely written exercises to eliminate distractors, while for the latter the teaching of problem solving should be delayed until the student’s program model is formed. While this does delay the development of problem solving skills, the problem solving abilities of students taught using this pedagogy were found to be comparable with students taught using a more traditional approach. Furthermore, monitoring students’ understanding of these patterns enabled micromanagement of the learning process, and hence explanations were provided for novice behaviour such as difficulties using arrays, inert knowledge and “code thrashing”. For teaching more complex problem solving, scaffolding of practice was investigated through a program framework that could be developed in stages by the students. However, personalising the level of scaffolding required was complicated and found to be difficult to achieve in practice. In both cases, these new teaching approaches evolved as part of a grounded theory study and a clear progression of teaching practice was demonstrated with appropriate evaluation at each stage in accordance with action researc

Hypothesis Generation and Pursuit in Scientific Reasoning

This thesis draws a distinction between (i) reasoning about which scientific hypothesis to accept, (ii) reasoning concerned with generating new hypotheses and (iii) reasoning about which hypothesis to pursue. I argue that (ii) and (iii) should be evaluated according to the same normative standard, namely whether the hypotheses generated/selected are pursuit worthy. A consequentialist account of pursuit worthiness is defended, based on C. S. Peirce’s notion of ‘abduction’ and the ‘economy of research’, and developed as a family of formal, decision-theoretic models. This account is then deployed to discuss four more specific topics concerning scientific reasoning. First, I defend an account according to which explanatory reasoning (including the ‘inference to the best explanation’) mainly provides reasons for pursuing hypotheses, and criticise empirical arguments for the view that it also provides reasons for acceptance. Second, I discuss a number of pursuit worthiness accounts of analogical reasoning in science, arguing that, in some cases, analogies allow scientists to transfer an already well-understood modelling framework to a new domain. Third, I discuss the use of analogies within archaeological theorising, arguing that the distinction between using analogies for acceptance, generation and pursuit is implicit in methodological discussions in archaeology. A philosophical analysis of these uses is presented. Fourth, diagnostic reasoning in medicine is analysed from the perspective of Peircean abduction, where the conception of abduction as strategic reasoning is shown to be particularly important

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

Building expert systems: cognitive emulation.

Chapter 1 briefly introduces the concept of cognitive emulation, and outlines its current status. Chapter 2 reviews psychological research on human expert thinking. First, the study of expert thinking is placed in the context of modern cognitive psychology. Next, the principal methods and techniques employed by psychologists examining expert cognition are examined. The remainder of the chapter is given over to a review of the published literature on the nature and development of human expertise. Chapter 3 reviews the main arguments for and against cognitive emulation in expert system design. The tentative conclusion reached is that a significant degree of emulation is inevitable, but that a pure, unselective strategy of emulation is neither realistic nor desirable. Chapter 4 examines the prospects for cognitive emulation from a more pragmatic angle. Several factors are identified that represent constraints on the usefulness of a cognitive approach. However, a second set of factors is identified which should facilitate an emulation strategy - especially in the longer term. Some guidance is given on when to seriously consider adopting an emulation strategy. Chapter 5 presents a critical survey of expert system research that has already addressed the emulation issue. Six basic approaches to cognitive emulation are distinguished and evaluated. This helps draw out in more detail the implications of an emulation strategy for knowledge acquisition, knowledge representation and system architecture. The chapter concludes by discussing the issues that arise when different approaches to emulation are combined. Some guidance is offered on how this might be achieved. Chapter 6 summarizes the main themes and issues to have emerged, the design advice contained in the thesis, and the original contributions made by the thesis