Contextualizing industry job requirements for PhDs: a mixed method investigation

Abstract

The PhD has historically served as a pathway to an academic career, but the increasing number of PhD graduates surpasses the limited opportunities within the traditional academic job market. This is a global issue, particularly pronounced in Australia. Consequently, there have been calls to revamp the PhD program to enhance graduates' employability in non-academic sectors. However, most initiatives focus on generic skill training without considering the diverse expectations and work cultures across industries. To effectively prepare PhD students for non-academic roles, further research is needed to develop contextually sensitive employability skills training. Current Australian educational policy assumes that PhD graduates should expand their skill sets, a notion that can be traced back to the Australian government's 1999 Discussion Paper on Research Training (Kemp, 1999). Despite substantial efforts to improve PhD employability training since then, industry employers continue to express concerns about the lack of specific skills, such as communication and time management, in PhD graduates. These skills have long been taught in Australian universities' research training and career development programs, suggesting either ineffective training or the presence of additional factors contributing to employers' dissatisfaction. As a result, this thesis adopts a cultural capital perspective on employability, acknowledging the interconnectedness between social structure and employers' skill demands. The analysis in this study is guided by a sociological view of employability. This thesis examines the perspective of employers on desirable skills for researchers outside academia by analyzing 1,800 job ads in high-research-skills-intensive roles within the healthcare and computing industries. To comprehensively analyze the skills mentioned in job ads, this study applies the 'Move-Step analysis' framework, derived from applied linguistics, which considers the influence of professional field habitus on ad composition. Additionally, the study employs a novel approach combining machine learning and natural language processing (ML-NLP) to automate qualitative analyses of skills in job ads, enabling a more systematic examination of skills while incorporating cultural factors. This study found that different industries interpret and value the same skills but want them deployed in different ways, which has implications for the development of any new PhD curriculum. Specifically, the results show how industry-specific values, beliefs, legislations, goals, and environmental settings presented in job ads work together to construct the meanings of skills sought by one industry field but not necessarily by another. Also, the quantitative analysis of professional skills presented in job ads revealed how different industry fields valued the same skills to varying extents. In addition, the thesis demonstrated that ML-NLP is a promising approach to understanding skills demand in different cultural/work worlds that PhD graduates may enter. The findings of this thesis trouble the idea that PhD skill development can be established on a decontextualized or generic basis. Perhaps a little more pedagogical intervention in PhD curriculum might be desired to emphasize the important role of culture and 'field habitus' in the meaningful construction of skilled practice, even for PhD graduates. As many PhD graduates nowadays need to seek jobs outside of academia, helping them transition smoothly from academic culture to industry culture is essential. The best approach is perhaps a skill development mode that clarifies not only 'what the skills are', but also 'how the skills are interpreted, and 'where such interpretation of skills is relevant'. Show more