Factors affecting timely completion of a PhD : a complex systems approach

Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be important to students and then quantify the network based on five individual perspectives: the students, a supervisor and a university research students centre manager. The resultant network comprised 37 factors and 40 connections, with an overall probability of timely completion of between 0.6 and 0.8. Across all participants, the four factors that were considered to most directly influence timely completion were personal aspects, the research environment, the research project, and incoming skills. Timely completion of a PhD is an important outcome for the student, the host university and the economy. However, completion of this programme in the required timeframe is dependent on many interacting factors. In this study, we develop a statistical complex systems approach to identify and quantify the important factors and their interactions that are perceived to impact on timely completion of a PhD in Statistics in an Australian university. We define timely completion to be within 3.5 years. We construct a Bayesian Network (BN) to describe these inter-relationships (Pearl, 1985); the construction and interpretation of a BN is described in more detail below. The conceptual model for the BN was developed collectively and then quantified by five candidates: three students, a supervisor and a university research students centre