Negotiating Disciplinary Boundaries In Engineering Problem-Solving Practice

Abstract

The impetus for this research is the well-documented current inability of Higher Education to

facilitate the level of problem solving required in 21st century engineering practice. The

research contends that there is insufficient understanding of the nature of and relationship

between the significantly different forms of disciplinary knowledge underpinning engineering

practice. Situated in the Sociology of Education, and drawing on the social realist concepts of

knowledge structures (Bernstein, 2000) and epistemic relations (Maton, 2014), the research

maps the topology of engineering problem-solving practice in order to illuminate how novice

problem solvers engage in epistemic code shifting in different industrial contexts. The aim in

mapping problem-solving practices from an epistemological perspective is to make an

empirical contribution to rethinking the theory/practice relationship in multidisciplinary

engineering curricula and pedagogy, particularly at the level of technician.

A novel and pragmatic problem-solving model – integrated from a range of disciplines – forms

the organising framework for a methodologically pluralist case-study approach. The research

design draws on a metaphor from the empirical site (modular automation systems) and sees

the analysis of twelve matched cases in three categories. Case-study data consist of

questionnaire texts, re-enactment interviews, expert verification interviews, and industry

literature. The problem-solving model components (problem solver, problem environment,

problem structure and problem-solving process) were analysed using, primarily, the

Legitimation Code Theory concept of epistemic relations. This is a Cartesian plane-based

instrument describing the nature of and relations between a phenomenon (what) and ways of

approaching the phenomenon (how). Data analyses are presented as graphical relational

maps of different practitioner knowledge practices in different contexts across three problemsolving

stages: approach, analysis and synthesis.

Key findings demonstrate a symbiotic, structuring relationship between the ‘what’ and the

‘how’ of the problem in relation to the problem-solving components. Successful problem

solving relies on the recognition of these relationships and the realisation of appropriate

practice code conventions, as held to be legitimate both epistemologically and contextually.

Successful practitioners engage in explicit code-shifting, generally drawing on a priori physics

and mathematics-based knowledge, while acquiring a posteriori context-specific logic-based

knowledge. High-achieving practitioners across these disciplinary domains demonstrate

iterative code-shifting practices and discursive sensitivity. Recommendations for engineering

education include the valuing of disciplinary differences and the acknowledgement of

contextual complexity. It is suggested that the nature of engineering mathematics as currently

taught and the role of mathematical thinking in enabling successful engineering problemsolving

practice be investigated.