Problematic Problems: A Historically Critical Examination of the Concept of the Problem in Computer Science

Objectives Computer science has profoundly shaped contemporary life, not only through technological artifacts but also through the ways it frames questions, problems, and solutions. One prominent example is computational thinking, which is often presented as a general problem-solving competence for the digital age. This paper examines what kinds of problems such framings imply and whether they are adequate when designing technological interventions that affect social and political contexts. More specifically, it investigates how the concept of problem is understood within computer science education research (CSER) and seeks to explain why certain understandings have become dominant. Study Method We first develop a conceptual framework by outlining historical and theoretical perspectives on the concept of problem , informed by conceptual history, philosophy of science, Critical Theory, planning theory, and computational thinking. Building on this framework, we conduct a systematic scoping review of how problems and problem solving are discussed in CSER literature, using a corpus of 85 articles from ICER, Koli Calling, ITiCSE, and TOCE. Findings Our analysis suggests that CSER tends to emphasize structured, solution-oriented, and comparatively tame problems, while more open-ended, contested, and wicked problems remain marginal. We also find that contextualization and real-world framing are often used primarily to motivate or legitimize tasks, rather than to foster critical reflection on how problems are framed and what assumptions underlie them. Conclusions We argue that the dominant problem framing in CSER is historically situated rather than natural or neutral. It is closely connected to broader social and economic commitments to formalization, optimization, and efficiency, including the logic of capitalist production. This has important implications for how computing research and education understand legitimacy, solvability, and intervention, and it points to the need for greater reflection on what counts as a problem and where the limits of computing-centered problem solving lie.