In recent years, education has put considerable emphasis on the development of twenty-first century skills—a set of skills that can almost universally be applied to a broad range of domains and problems, and that help students to deal with the challenges and demands of complex, real-world problem situations (Pellegrino and Hilton, 2012). Among others, these skills comprise problem solving, creativity, critical thinking, collaboration, adaptability, digital literacy, and computational thinking, and are considered to be critical in our information- and knowledge-rich society (Binkley et al., 2012; Wagner, 2012; Scherer, 2015; Care and Anderson, 2016). Against this background, it has become the designated aim of educators to help students to develop these skills (Kay and Greenhill, 2011). The question of how the development of these skills and the ability to transfer them to different contexts and knowledge domains can be fostered has therefore gained significance (Greiff et al., 2014). Nonetheless, this question is by no means trivial, because the transfer of knowledge and skills does not automatically happen, as Tricot and Sweller (2013) argued. In the pursuit of finding ways to foster twenty-first century skills and their transfer, voices have become loud inspiring education to incorporate computer programming into K-12 curricula (Lye and Koh, 2014). The reactions on these voices have been tremendous; some countries developed an entire curriculum around computer programming (Sturman and Sizmur, 2011; Webb et al., 2016). Behind this development is the belief that fostering programming skills improves students' performance on other critical skills such as creativity and problem solving (Liao and Bright, 1991; Clements, 1995). Mitchel Resnick, the director of MIT's Media Lab and facilitator of the Scratch® programming language, argued that “programming supports “computational thinking,” helping you learn important problem-solving and design strategies […] that carry over to nonprogramming domains” (Resnick et al., 2009, p. 62). Along the same lines, Barr and Stephenson (2011) proposed that computer programming “is a problem solving methodology that can be automated and transferred and applied across subjects” (p. 51). Brown and Kolling (2012) took this argument even further and claimed that the “use of programming skills can allow for a deeper and more direct understanding of the subjects under investigation, using Computing to support learning in the same way that Mathematics supports the learning of subjects such as Physics.” (p. 1) Whereas there has been a great body of research supporting these claims in the 1980s and 1990s (for an overview, please refer to Liao and Bright, 1991), it seems as if there is very little evidence on the transfer effects of computer programming skills in the context of twenty-first century education (Grover and Pea, 2013; Lye and Koh, 2014). Although computer programming and other skills share a number of cognitive and even metacognitive processes (Clements, 1986, 1995; Brown and Kolling, 2012; Lye and Koh, 2014; Rich et al., 2014), therefore supporting potential transfer effects, I argue that educational research lags behind in sharing sufficient evidence for these claims. Against this background, the main position this opinion paper conveys is that—although the conceptual argumentation about the potential transfer effects of computer programming skills on other skills such as problem solving and creativity is reasonable—there is a strong need for empirical evidence supporting this, particularly in the context of the recent advancements of digital technologies.