Our study is set in an educational context: to better teach and assess twenty-first century skills, such as computational thinking or creative problem solving, we propose to formalize a specific activity that involves these competencies. This activity, referred to as #CreaCube, is presented as an open-ended problem which consists of assembling a set of robotic cubes into an autonomous vehicle. We not only anchor our formalization in classical learning science frameworks but we also propose to draw on neuro-cognitive models to describe the observed behaviors of learners engaged in this activity. The chosen formalism is symbolic and is aligned on upper ontologies to ensure that the vocabulary is well specified. This allows for a better communication between the summoned research fields, namely learning science, cognitive neuroscience and computational modeling. Beyond this specification purpose, we suggest performing inferences using available reasoners to better guide the analysis of the observables collected during the experiments. This operationalization of a creative problem-solving activity is part of an exploratory research action. In addition, an effective proof of concept is described in this study.