Covert conversations: disciplined improvisation and meaning-making in the masters (MA) supervisory relationship

This research asks the question: “What are the relational dynamics in Masters (MA) supervision?” It does so by focusing upon the supervisory relationship itself. It does this through dialoguing with the voices of both MA supervisors and supervisees in the Humanities using a Cultural Historical Activity Theory (CHAT) framework. In so doing, this research argues for a re-evaluation of how MA supervision is conceptualised and proposes a new theoretical framework for conceptualising MA supervision as a relational phenomenon. The research design was derived from an Activity Theory-influenced methodology. Data collection procedures included the administration of Activity Theory Logs, individual semi-structured interviews with both supervisors and supervisees and the completion of reflective journals. Grounded Theory was used to analyse the data. The sample for the study consists of three supervisor-supervisee dyads from three disciplines in the Humanities. Data was collected over the course of one academic year, 2010-2011. This research found that both individual and shared relational dynamics play an important role in MA supervision. Individual dynamics, such as supervisors’ iterative negotiation of ambiguity/clarity and supervisees’ boundary work, revealed that both parties attempt to negotiate a separation between their professional-academic identities and personal identities. However, an inherent paradox emerged when the shared relational dynamics of MA supervision were investigated. It was found that the shared space created by the supervisory relationship did not only exist in a physical setting, but was also psychoactive in nature and held strong emotional resonances for both parties involved. This served to undermine the separation between professional-academic and personal identities. As a result, this research argues that the interaction between the individual and shared relational dynamics in MA supervision enables, for both supervisors and supervisees, a disciplined improvisation of academic identity.

Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.