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 Kölling (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 Kölling, 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.

In light of this brief review of the current status of knowledge, I would like to follow Mayer (2015), who discussed the strong need for research evidence on game-based learning, and propose that research on the transfer effects of computer programming needs to move beyond untested claims and the mere description of programming tools, their feasibility, and students' interest or enjoyment thereof Fessakis et al. (2013) raised similar concerns: “Instead of focussing on the cognitive effects of programming, more recent studies concern the development of new programming environments for children […]” (p. 89) Along these lines, educational research needs to focus more on the cognitive consequences of learning to program by designing experimental studies that systematically evaluate the transfer effects, making use of the well-developed programming tools such as Scratch® (Resnick et al., 2009). I believe that the outstanding number of feasibility studies on these tools create a fruitful ground for experimental comparisons. Such comparisons, however, need an appropriate research design, which fulfills at least three criteria (Mayer, 2015): (1) Appropriate outcome measures of academic learning or other skills that go beyond students' self-reports, enjoyment, or interest; (2) Experimental control—pretest-posttest designs with a treatment group (i.e., the group that learns to program) and a control group; (3) Random assignment of students to treatment and control groups. Despite the very few studies during the last 20 years, which adhered to these criteria (e.g., Pardamean et al., 2015), my observation is that research on the transfer effects of computer programming is in need of methodologically sound, experimental studies.

From a conceptual perspective, the claims that learning computer programming may translate into the development of other, cognate skills such as problem solving or creative thinking, do have their standing, particularly because a considerable conceptual overlap between these skills exists. From an empirical perspective though, it seems as if the conceptual claims have been supplemented with evidence from experimental studies to a very limited extent. My observation is that most of the empirical research on the transfer effects dates back to the 1980s and 1990s; yet, too few studies have looked into these effects in the twenty-first century. This observation is somehow unexpected, particularly because Pea and Kurland (1984) pointed to the strong need for evidence on the transfer effects of computer programming that takes into account the development of digital technologies more than 20 years ago. Although this plea has been followed by a wave of experimental studies (Liao and Bright, 1991; Clements, 1995), educational research has not systematically followed up on examining the transfer effects. On the basis of the limited research on the transfer effects of computer programming skills on other cognitive skills on the one hand, and the conceptual claims that these transfer effects exist on the other hand, I would like to encourage researchers to fill this gap by learning from the past and reviving this research area in the twenty-first century.

RS has conducted the literature review, drafted the manuscript, and performed revisions.