Metaphors are deeply embedded in the language of computing, from ‘stacks’ and ‘queues’ to ‘trees’ and ‘handshaking’. Such metaphorical expressions not only shape but also fundamentally reflect our understanding and conceptualization of computing concepts. Students’ descriptions of computing concepts have also been shown to be richly metaphor-laden, often framing abstract notions in more tangible or accessible ways. The rich metaphorical conceptualizations set the stage for a natural application of Conceptual Metaphor Theory (CMT) in computing education research. At its core, CMT posits that metaphors are not just linguistic expressions but fundamental structures of understanding, influencing how we perceive and think about the world.

This work highlights the inherent congruence of traditional CMT analysis methods with computing education research contexts. We demonstrate this applicability via a case study that brings CMT into action, focusing on student-generated analogies from a CS1 course using a tailored CMT framework. The tailored approach employs analogical decomposition, to analyze both the target and source domain descriptions. While the case study presents a tailored CMT framework for analogies, this work retains broad relevance for understanding student conceptions using natural language data in which students describe computing concepts.