A mixed-method study of stem qualified professionals’ persistence intentions within the Australian agriculture sector
Masters Thesis
Title | A mixed-method study of stem qualified professionals’ persistence intentions within the Australian agriculture sector |
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Type | Masters Thesis |
Authors | |
Author | Lovric, Kristen A. |
Supervisor | McIlveen, Peter |
Beccaria, Gavin | |
McDonald, Nicole | |
Institution of Origin | University of Southern Queensland |
Qualification Name | Master of Psychology (Clinical Psychology) |
Number of Pages | 251 |
Year | 2020 |
Digital Object Identifier (DOI) | https://doi.org/10.26192/435r-r936 |
Abstract | There is currently a demand for Science, Technology, Engineering or Mathematics (STEM) trained personnel within the Australian agriculture industry driven by the precision agriculture revolution and subsequent digitisation of many work tasks. This research explored the utility of Social Cognitive Career Theory (SCCT) as a framework for explaining career persistence intentions among STEM trained professionals working in the Australian agriculture sector. SCCT has previously been found to be generalisable in a variety of educational and career contexts. While STEM academic and career choice, and persistence have been extensively explored within the SCCT literature, few studies have focused on the application of STEM skills within an Agricultural workforce context. This thesis addresses the gap in the literature and aims to contextualise the operationalisation of SCCT constructs to the Australian STEM of agriculture workforce. The SCCT choice and persistence literature is reviewed to understand the direct and indirect effects of hypothesised pathways within STEM and agricultural populations. Prior operationalisation of SCCT constructs are discussed and used to inform the current studies instrumentation. An adapted model of career persistence was developed to test SCCT (a) self-efficacy expectations, (b) outcome expectations, (c) goal directed activity, (d) environmental supports, and (e) personality trait propositions. A sequential mixed-methods design was utilised, in which an initial qualitative study was undertaken, and semi-structured interviews conducted to conceptualise SCCT variants within a STEM and agriculture context relevant to the Australian workforce. Face validity of prospective measures was assessed using theory-driven thematic analysis. A STEM task-specific self-efficacy measure was developed as a result of qualitative analysis. In addition, interpretation of interviewee responses led to the inclusion of variety seeking, an expression of the openness to experience personality trait in the second quantitative study. The follow-up quantitative study tested the predictive utility of SCCT using online survey data. Hierarchical regression analysis was used to test the predictive utility of independent variables on persistence intentions. Mediation analysis was then utilised to test indirect relationships among variables. Testing of the SCCT Model of STEM Professionals Persistence within Australian Agriculture revealed that perceived organisational support and work engagement were direct predictors of persistence intentions. The inclusion of work engagement as a mediator also demonstrated that the path from perceived organisational support to persistence intentions was mediated by work engagement. Therefore, to contribute to persistence within the field organisations should provide adequate support, and individuals whom seek career counselling may benefit from interventions that clarify their goals and broaden their coping strategies. |
Keywords | Social Cognitive Career Theory, mixed methods, STEM, agriculture, career persistence |
ANZSRC Field of Research 2020 | 520104. Industrial and organisational psychology (incl. human factors) |
Byline Affiliations | School of Psychology and Counselling |
https://research.usq.edu.au/item/q6060/a-mixed-method-study-of-stem-qualified-professionals-persistence-intentions-within-the-australian-agriculture-sector
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Updated Full Thesis November 30th 2020_Lovric_Track Changes Accepted .pdf | ||
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