Using Data Visualization Techniques to Assess Perception of Professionalism, Professional Identity and Development: A Case Study on Closed-Type Questionnaires

Abstract

Introduction. Professional identity, professionalism, and professional development are concepts that attract research interest over the years. The concepts are complex, multi-faceted, evolving over time, and varying depending on the pre-primary teachers’ (i.e., preschool educators’) and primary school teachers’ context. The conceptualization by teachers themselves is of particular interest. Goal. Explore the use of artificial intelligence techniques and specifically dimensionality reduction methods, in analyzing in-service teachers’ perceptions of the three concepts as captured in closed-type questions with Likert-scale responses. Methods of the Research. Model Likert-scale responses of closed-type questionnaire as multi-dimensional question space. Apply dimensionality reduction techniques to visualize responses in two dimensions. Translate back question distances into theoretical concepts and identify unexplored topics. Results. The dimensionality reduction disclosed novel correlations between the concepts and their components, not previously reported in published literature, where classical statistical analysis was employed. Conclusions. We confirm the applicability and usefulness of the dimensionality reduction method for the analysis of human responses in closed-type questionnaires. Further, we identify through dimensionality reduction two novel research questions that should be further studied in the future.