An Empirical Study of Transformative Learning Resulting Due to Profession Change
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A career choice may emerge or be adopted due to personal interest or to balance a range of factors like familial influences, educational qualifications and economic considerations. Once a choice has been made, some follow the ‘one life, one career’ paradigm and settle soon. In contrast, the career trajectories of some others may involve journeying through multiple professions. Since stories of such journeys often evoke curiosity and reflection, scholarly inquiries into this phenomenon are common in the domain of career theory. However, somewhat underrepresented is the transformative influence of profession change. In this work, we used the Transformative Learning theory of Jack Mezirow to study the personal transformation of profession changers. For this, we reviewed select literature from five domains: ‘Education’, ‘Adult Education’, ‘Philosophies and Theories of Adult Education and Learning’, ‘Transformative Learning’ and ‘Profession Change and Transformative Learning’. This led to the realisation of multiple open areas in the existing scholarship. Subsequently, the following four objectives were framed to address some of the identified gaps: 1. To create a conceptual framework to describe the transformative journey of profession change. 2. To operationalise Mezirow’s conception of six types of ‘Habits of Mind’ so that extent of transformation of a profession changer could be measured. 3. To establish a measure for comparing previous and current professions of a profession changer. 4. To predict the likelihood of observing Transformative Learning amongst profession changers using information related to personal history and current and previous professions. Methodologically, our approach to every objective was primarily decided by three considerations: insights from extant literature, empirical data, and the direction provided by the objective. The data was obtained from 319 profession changers from India using a structured questionnaire. For analyses, we used suitable techniques and computational tools. Inferences and recommendations have been made. To address the problem posed by the first objective, we synthesised a new framework to explain the transformative journey of profession changers. This framework draws insights from the domains of career theory, adult learning, and Transformative Learning. It identifies important stakeholders and provides insights for career planning and management. In contrast, the second objective was conceived considering the scarcity of ways to measure the extent of personal transformation. While addressing this gap, Mezirow’s work on six types of ‘Habits of Mind’ was extended beyond the original conceptualisation by identifying constituent latent factors through the Exploratory Factor Analysis (EFA) technique. The statistical reliability and validity of these factors have been established, and a factor-based scale approach is recommended for application. Further, the pursuit for the third objective involved the examination and operationalisation of the concept of ‘Profession Formality’ using the Partial Least Squares – Structured Equation Modeling (PLS-SEM) methodology. This resulted in the construction of a new index with five dimensions: ‘systematic theory’, ‘ethical codes’, ‘professional culture’, ‘professional authority’, and ‘community sanction’. The final objective explored the possibility of whether the likelihood of observing Transformative Learning may be predicted using information related to personal history and current and previous professions. For this, the outputs of the second and the third objectives were combined and examined using a machine learning method – the Random Forest algorithm. It was observed that the following five variables play an important role in prediction: ‘Overall Formality (Previous Profession)’, ‘Community Sanction (Previous Profession)’, ‘Professional Authority (Current Profession)’, 'Bridge Course', and 'Gender'. This study is important for four groups: (a) profession changers, (b) employers, (c) support organisations, (d) academic community. Profession changers could use the information generated by this study for meaning-making and career planning and management. This information may also be used by those who employ or support profession changers for improving or augmenting their Human Resource Management practices and assistance programmes. In contrast, the academic community could utilise the information for educational and research purposes since this study provides a new framework, two new tools, and an empirically backed rationale.