Think Quantumly About Computing

Davor Pavuna

Raquel Coelho, Raja Krishnaswamy, Ibrahim Oluwajoba Adisa +1 more

Computational Thinking (CT) frameworks have expanded over the past two decades to address technological advances and sociotechnical concerns, yet they remain grounded in classical, deterministic computational logic.Quantum information science introduces fundamentally different principles for representing and processing information, requiring learners to engage with non-intuitive, probabilistic, and relational forms of reasoning that depart from classical computational models.Drawing on frameworks by Brennan and Resnick and Kafai et al., we explore what Quantum Computational Thinking (QCT) might entail and open a dialogue about how the learning sciences community might prepare learners for a quantummediated world, with attention to access, democratic participation, and the challenges of developing new intuitions. Computational thinkingNearly two decades ago, Wing (2006) introduced Computational Thinking (CT) as "a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use" (p.33).Early work by Papert (1980/2020) framed CT primarily in terms of procedural thinking and programming.Subsequent scholars broadened its scope: Grover and Pea (2013) identified transferable competencies such as abstraction, decomposition, and debugging; Brennan and Resnick (2012) reframed CT as the interplay of concepts, practices, and perspectives, shifting attention toward epistemic and identity dimensions; and Kafai (2016) proposed computational participation to foreground the social, cultural, and ethical aspects of computing.Yet across these perspectives, CT remains grounded in classical, deterministic, binary logic.When these frameworks were established, quantum technologies were largely theoretical (Nielsen & Chuang, 2010).Today, quantum information science (QIS) is rapidly transitioning from theory to application, promising transformative impacts.The question is no longer whether quantum technologies will redefine the computational landscape, but how soon and for whom.This shift calls for re-examining what it means to think computationally.Quantum Computational Thinking (QCT) does not replace classical CT, but extends it to address a distinct class of problems that quantum computation is uniquely suited to tackle.In the next section, we explore what QCT entails and how quantum concepts, practices, and perspectives can deepen and extend CT for the emerging quantum era.

Matthias Ziegler, Tim Leonhardt

Caiseal Beardow, Pieter Jan Stappers

In recent years, the quantum computing industry has seen significant investment and growth. However, this burgeoning industry faces a persistent labour gap: individuals with computing expertise, an understanding of quantum principles, and the ability to apply these principles to computing practices, are in increasing demand, but finding such individuals is proving challenging. We frame this problem as one of education, arguing that a computing-centred approach to learning about quantum computing is needed, and that the notion of computational thinking can help to define appropriate learning goals and outcomes in this context. We propose that metaphors can be an effective pedagogical tool in supporting the development of 'quantum computational thinking'. In this paper, we present our efforts to gather and assess a collection of metaphors that are currently used to teach quantum computing concepts. We describe a series of interviews with quantum computing experts in which we aimed to elicit such metaphors, and document our process of metaphor identification and metaphorical model synthesis. We subsequently assess these metaphors and models using both numerical rating data from experts and our own qualitative analysis. Informed by our findings, we suggest ways of developing metaphors that better support quantum computational thinking: emphasising target concepts' computational roles, acknowledging connections between concepts, and balancing procedural narratives with embodied, tangible imagery.

Christian Gamrat

Although no one can yet forecast if or when it will become an operational technology, quantum computing R&D efforts will nevertheless have a profound impact on the future of computing as it is boosting research in important topics such as hybrid architectures, and algorithmic and computational complexity. It also forces us to re-think the very nature of information processing.

Vicente Moret‐Bonillo