Teachers’ Ontological Perspectives of Computational Thinking and Assessment: A Text Mining Approach

Abstract

As a dynamic and multifaceted construct, computational thinking (CT) has proven to be challenging to conceptualize and assess, which impedes the development of a workable ontology framework. To address this issue, the current article describes a novel approach towards understanding the ontological aspects of CT by using text mining and graph-theoretic techniques to elucidate teachers’ perspectives collected in an online survey (N = 105). In particular, a hierarchical cluster analysis, a knowledge representation method, was applied to identify sub-groups in CT conceptualization and assessment amongst teachers. Five clusters in conceptualization and two clusters in assessment were identified; several relevant and distinct themes were also extracted. The results suggested that teachers attributed CT as a competence domain, relevant in the problem- solving context, as well as applicable and transferrable to various disciplines. The results also shed light on the importance of using multiple approaches to assess the diversity of CT. Overall, the findings collectively contributed to a comprehensive and multi-perspective representation of CT that refine both theory and practice. The methodology employed in this article has suggested a minor but significant step towards addressing the quintessential questions of “what is CT?” and “how is it evidenced?”.