Meurig Beynon

A new paradigm for computer-based decision support

We identify and address a fundamental general problem which we regard as crucial for the widespread, effective use of decision support systems (DSS) in the future: how can we substantially improve the quality of interaction, and the degree of flexible engagement, between humans and computers? Rather than seeking an answer in additional technical functionality, we propose a new paradigm for computing that is human-centered and that adopts a novel, observation-oriented approach to data modelling. We report a recent practical work (a timetabling instrument) showing an unusual degree of openness for interaction, and we give evidence that our approach can encompass conventional tools such as expert systems.

Cognitive Technology: Instruments of Mind

Cognitive Technology is the study of the impact of technology on human cognition, the externalization of technology from the human mind, and the pragmatics of tools. It promotes the view that human beings should develop methods to predict, analyse, and optimize aspects of human-tool relationship in a manner that respects human wholeness. In particular the development of new tools such as virtual environments, new computer devices and software tools has been too little concerned with the impacts these technologies will have on human cognitive and social capacities. Our tools change what we are and how we relate to the world around us. They need to be developed in a manner that both extends human capabilities while ensuring an appropriate cognitive fit between organism and instrument. The principal theme of the CT2001 conference and volume is declared in its title: Instruments of Mind. Cognitive Technology is concerned with the interaction between two worlds: that of the mind and that of the machine. In science and engineering, this interaction is often explored by posing the question: how can technology be best tailored to human cognition? But as the history of technological developments has consistently shown, cognition is also fashioned by technology. Technologies as diverse as writing, electricity generation and the silicon chip all illustrate the profound and dynamic impact of technology upon ourselves and our conceptions of the world. The instruments afforded by these technologies continue to evolve and to shape the minds that first conceived them. The technologies of the third millennium promise mind-machine interactions of unprecedented intimacy and subtlety. These interactions embrace radically new kinds of experience that force us to re-examine fundamental concepts of embodiment and consciousness which frame our understanding of the relationship between minds and machines. The implications of these interactions will hinge on the ways in which humans make meanings out of these new experiences. The conference and these proceedings address this issue using the diverse perspectives afforded by a wide range of disciplines, and evidence drawn from both contemporary developments and the history of technology. Its aim is to deepen our insight into the potential influence of current and future technologies over people and society.

Lifelong Learning, Empirical Modelling and the Promises of Constructivism

Educational technology is seen as key for lifelong learning, but it has yet to live up to expectation. We argue that current learning environments are typically oriented too much towards structured learning to meet the needs of the lifelong learner. Environments for lifelong learning demand a higher degree of autonomy for the learner, must be open to eclectic sources, support soft informal learning activity, and accommodate evolution both in the experience of the learner and in the context in which this occurs. We propose sense-making through the construction of suitable interactive artefacts as a core activity for lifelong learning, and discuss and illustrate how this can be supported using Empirical Modelling. The merits of Empirical Modelling as a constructivist approach are assessed with reference to a criterion recently proposed by Bruno Latour, namely, the extent to which it strengthens five guarantees, taken together.

Computer support for constructionism in context

The benefits of constructionism as a learning paradigm are widely recognised. Though the constructionist philosophy can be seen as applying to activities that are not necessarily computer-based (such as bricolage and concept mapping), its modern application in educational technology has been closely linked with computer use. In particular, Paperts work on LOGO programming in schools has both informed the original concept of constructionism and been a major influence over subsequent computer-based constructionist developments. This paper questions whether - despite these precedents - traditional computer programming is well-suited for the constructionist educational agenda. It argues that other approaches to computer model-building, such as those based on spreadsheet principles, are in fact much better aligned to the objectives of constructionism. Building on this basis, it proposes that more effective computer support for the constructionist perspective is offered by empirical modelling (EM) within a conceptual experiential framework for learning (the EFL).

Experimenting with computing

We distinguish two kinds of experimental activity: post-theory and exploratory. Post-theory experiment enjoys computer support that is well-aligned to the classical theory of computation. Exploratory experiment, in contrast, arguably demands a broader conception of computing. Empirical Modelling (EM) is proposed as a more appropriate conceptual framework in which to provide computational support for exploratory experiment. In the process, it promises to provide integrated computational support for both exploratory and post-theory experiment. We first sketch the motivation for EM and illustrate its potential for supporting experimentation, then briefly highlight the semantic challenge it poses and the philosophical implications.

Modelling with Experience: Construal and Construction for Software

Software development presents exceptionally demanding conceptual challenges for model-building. It has such diverse phases, may touch so many disciplines, may address personal and public applications, can involve collaboration of experts from many fields, user participation, and an essential need for ongoing revision. Software modellers must see and think like designers, logicians, engineers, programmers, business analysts, artists, sociologists. This chapter reviews thinking about software development with particular reference to: the limitations of adopting the formal representations that classical computer science commends; different approaches to rationalising the use of models in software development; and the problems of conceptualising software development as theory-building. It concludes by sketching an embryonic approach to software development based on ‘Empirical Modelling (EM)’ that draws on William James’s pluralist philosophy of ’radical empiricism’, the historian of science David Gooding’s account of the role of ’construals’ in experimental science, and the sociologist Bruno Latour’s vexing notion of ’construction’. The products of EM development are interactive artefacts whose potential meanings are mediated by the patterns of observables, dependencies and agencies that they embody, as elicited by the actions of the participants in the model-building.

Computing for construal: an exploratory study of desert ant navigation

Abstract The study of ant navigation is a rich source of empirical data and speculative theories that has been well-documented in the scientific literature. We describe and illustrate how an approach to computer-based modelling (“Empirical Modelling”) can be used to devise construals to support the exploratory experimental activities that inform an understanding of desert ant navigation.

CONSTRUCTIVIST COMPUTER SCIENCE EDUCATION RECONSTRUCTED

Abstract The merits of Empirical Modelling (EM) principles and tools as a constructivist approach to computer science education are illustrated with reference to ways in which they have been used in teaching topics related to the standard computer science curriculum. The products of EM are interactive models — construals - that serve a sense-making role. Model-building proceeds in an incremental fashion through the construction of networks of definitions that reflect the observables, dependencies and agents associated with a current situation. The three principal case studies discussed (teaching bubblesort, solving Sudoku puzzles, and recognising groups from their abstract multiplication tables) highlight respects in which EM accounts for aspects of computing that cannot be effectively addressed by thinking primarily in terms of abstractions, procedures and mechanisms. The discussion of EM as a constructivist approach to computer science education is set in the context of an analysis of constructivism in computer science published by Ben-Ari in 2001. Reconciling EM’s constructivist epistemology with this analysis involves recognising its pretensions to a broader view of computer science.

Empirical modelling in support of constructionist learning: a case study from relational database theory

Conventional programming paradigms have limitations where support for constructionist learning is concerned. This paper illustrates the merits of an alternative approach to giving support for constructionist learning, based on the principles of empirical modelling (EM), with reference to an algorithm from database theory. Effective model-building for constructionist learning has to support activities relating to three roles: that of student, teacher and developer. This paper aims to show that EM brings far greater conceptual unity to interactions in these roles than is typically found in conventional approaches to educational software development.

Replaceability and computational equivalence for monotone Boolean functions

SummaryReplacement rules have played an important role in the study of monotone boolean function complexity. In this paper, notions of replaceability and computational equivalence are formulated in an abstract algebraic setting, and examined in detail for finite distributive lattices — the appropriate algebraic context for monotone boolean functions. It is shown that when computing an element f of a finite distributive lattice D, the elements of D partition into classes of computationally equivalent elements, and define a quotient of D in which all intervals of the form [t ∧ f, t ∨ f] are boolean. This quotient is an abstract simplicial complex with respect to ordering by replaceability. Other results include generalisations and extensions of known theorems concerning replacement rules for monotone boolean networks. Possible applications of computational equivalence in developing upper and lower bounds on monotone boolean function complexity are indicated, and new directions of research both abstract mathematical and computational, are suggested.