In her influential work, Computational Thinking, Wing posited computational thinking as an essential skill for all students to master alongside the established skills of reading, writing and arithmetic.  Bridging computer sciences and the liberal arts, Wing argued that computational thinking is a “universally applicable attitude and skill set for everyone” [34].  As such, computational thinking is a conceptual process that is inherently humanistic. At its most innovative, it draws upon the ways in which humans think, rather than simply replicating the ways in which machine thinking occurs.  It is based on ideas, rather than artifacts.

Computational thinking cannot be reduced to the software that it may produce. The term is shorthand to express the complexity of “the computational concepts we use to approach and solve problems, manage our daily lives and communication, and interact with other people” [34]. It addresses the whole array of social and natural problems and is “limited only by our own curiosity and creativity” [34]. More concretely, computational thinking pedagogy involves developing in students the “thought processes involved in a way of solving problems, designing systems, and understanding human behavior” [16].  In other words, computational thinking parallels many of the goals and practices of the pedagogical traditions of the liberal arts.

While computational thinking is broad in scope, a pedagogical operationalization of computational thinking is coding, which is “simply the language used by technology to make it work” [28]  Coding builds upon “the basics of thinking and planning in order to make things happen (the whole purpose of coding)” [28]. Engaging students in the practices associated with coding enhances their ability to solve problems by breaking a complex issue or problem into its component parts and reassembling those parts in a systematic and logical manner.  Further, “students learn to problem solve, overcome challenges and persevere. Students develop independence as they troubleshoot their coding errors [and] learn teamwork as they work in groups” []. These skills are relevant beyond the STEM disciplines.

The expansion of coding pedagogy to students beyond STEM may yield intellectual and social benefits [21];[31]. Research suggest at least four positive outcomes. First, a greater range of the diversity of the student population may be reached, including students of color, women, and others [27]. Second, a broader spectrum of issues of social and material life may get addressed by different orientations to problems that envision new types of solutions.  Third, for today’s students living and earning in an information economy, coding may help them achieve proficiency in working with “a set of problem-solving skills to thrive in a digital world full of objects driven by software” [and data] [24]. Finally, coding may empower students to gain agency to move from the relatively passive role of consumer of information and data to the more active role of producer of information, data, and other cultural forms [6].  Given these educational outcomes, the rationale and value of coding across the curriculum is compelling.

However, in the context of higher education, research about coding pedagogy beyond STEM disciplines and the K-12 environment is limited.  Payton et al., in their comprehensive literature review of peer reviewed journal articles from 2000 to 2015 conclude that there were “few studies that focused on the intersection of STEM, the arts, and higher education” [21]. Of the available scholarship, “an overwhelming number of research studies focus on K-12” rather than on college. They suggest that the paucity of research about “STEAM (STEM + the Arts) and the higher education domain [presents] an opportunity to generate new data that may inform future research” [21].

Studies that do focus on higher education and coding pedagogy for students outside of computer science and STEM disciplines suggest that the interconnections between the arts, humanities, and STEM hold powerful pedagogical potential. Steven Tepper, dean of the Herberger Institute for Design and the Arts, states “we know from the learning sciences that the kind of pedagogy that has high impact for student learning is exactly the kind of pedagogy that has been part of an arts curriculum for a long time” [21]. Relationships between the arts, humanities, and STEM can be leveraged to promote creativity and innovation toward learning [19].

In their research on using a problem-based learning approach informed by the arts for teaching and learning about coding, Sochacka et al. found that the strategy afforded opportunities for students to explore the connections between their learning and possible solutions to real-world problems. Others [21]; [33] cite the benefits of including co-curricular activities that promote student engagement and self-efficacy with coding instruction. Greenberg et al. recommend the development of specially tailored coding courses for non-STEM majors that address student perceptions of coding as “tedious, antisocial, and irrelevant” [10]. Such approaches may contribute positively toward student persistence and success and inform liberal arts coding pedagogy.

Instructors design specially tailored coding classes around key pedagogical strategies. These include the identification of a relevant programming context, an appropriate choice of coding language, and intentional efforts to establish a supportive, inclusive, and engaging classroom culture with active learning opportunities.  Examples of tailored courses include media computation, robots, games, and animation [10]. Forte and Guzdial’s seminal study at the Georgia Institute of Technology found several positive outcomes to this approach. “More non-majors succeeded (completed and passed) the tailored courses than the traditional course; students expressed fewer negative reactions to the course content, and many reported that they would be interested in taking another tailored CS course” [7].  Importantly, the tailored classes also fostered greater inclusion of women and underrepresented groups compared to the standard CS classes.

Beyond carefully tailored courses, innovative pedagogical strategies for coding instruction in the liberal arts have extended the emphasis on the design and development of new contexts for teaching coding.  This pedagogical strategy seeks to “present computing as a medium of creativity” in order to make coding relevant to a diverse array of disciplines [10].  The approach draws upon the pioneering work of Professor John Maeda from the MIT Media Lab who re-envisioned computing pedagogy for the arts. Trained in both fine arts and computer science, Maeda “re-contextualized computer code from an applied math notation to a creative medium on par with charcoal, paint, and clay” [10].  Maeda’s pedagogical research culminated with the development of the Processing language which has been used in liberal arts areas, including Art and Design, Architecture, Information Science, and Data Visualization. Greenberg et al. furthered this pedagogy by opening up new instructional contexts in which students “used generative art and creative coding [to] create a portfolio of aesthetic visual designs” that employ the coding structures typically taught in introductory computing classes [10].

Similarly, Freeman and Magerko advanced creative coding pedagogy to iterative music composition and articulate “a role for live coding—without live performance—in educational contexts” [8]. Live coding involves “the simultaneous modification and execution of code in a live performance setting where a performer shares the [programming] screen with the audience” [8]. Using the learning platform EarSketch, students of music technology and music composition “write Python or JavaScript code to algorithmically generate loop-based music within a digital audio workstation (DAW) workflow” [8]. This approach establishes an innovative, real-time educational context for students to learn and practice coding regardless of whether they are actually in a staged setting. The concept and practice of this pedagogical strategy focuses on producing discipline-relevant contexts for coding instruction and is able to be transferred across the disciplines of the liberal arts.

In addition to the focus on the development of specific educational contexts for coding, many humanities and social science disciplines have identified the basic building blocks of the web—HTML, CSS, and JavaScript—along with data computational skills, as key literacies for pedagogical practice to address.  In these instances, coding pedagogy emphasizes instruction in the use of HTML for web page design, PHP and MySQL for content management systems, Java, JavaScript, or Swift for app and mobile development, as well as coding programs for data scraping, UI design, data visualization, computational data analysis, and social media analytics.

While gaining fluency in coding is considered an important literacy, some faculty point out that it may be unrealistic to expect that university departments of computer science can or will be equipped to teach coding skills in ways that are deeply meaningful to the distinctive areas of foci within particular liberal arts disciplines.  They maintain that CS faculty may not be accustomed to employing pedagogical approaches that fit the traditions, practices, questions, and habits of mind inherent in the various liberal arts disciplines. Journalism professor Cindy Royal recommends that the faculty of academic departments take on the task of teaching coding to the students in their programs.  She contends that in the age of digital media, journalists need to have coding skills as well as journalistic skills, and that this is the case across the liberal arts. She states, “coders won't be hired to support journalism, storytelling, art, or science. They will be the journalists, storytellers, artists, or scientists" [25].

Some institutions of higher education have begun to work in this direction by taking a more comprehensive approach that combines coding pedagogy with the liberal arts to form new dual degree programs.  For example, the “CS + X” degrees at the University of Illinois combine computer science with non-STEM fields. These dual degrees continue to be created and thus far pair computer science with anthropology, linguistics, music, advertising, economics, and philosophy, as well as STEM fields of chemistry, astronomy, and crop sciences.  The dual degree programs are structured such that “students get a strong foundation in computer science [and] as computer science students move on to upper-level electives in different specialties, "CS +" students take advanced courses in their "X" field” [35].

Similarly, Purdue University has commenced the Integrative Data Science Initiative (IDSI) to infuse “data science education as a part of every student’s learning experience on campus, no matter the field” [26].  Purdue is also considering the creation of several data-science focused physical spaces on campus to foster computational skills and research. These locations would range from student residences and learning communities to faculty and industry collaboration spaces.

Parallel initiatives include programs at Yale, Stanford, Carnegie Mellon University, MIT, the University of California-Berkeley, Bates College, and the University of Washington among others. The Division of Data Science and Information at UC-Berkeley articulates a broad goal to “enable students and researchers to take not just the scientific challenges opened up by pervasive data, but the societal, economic, and environmental impacts as well” [15]. The Division “emphasizes interdisciplinary training among scientists, engineers, social scientists, and humanists [to] integrate data sciences into its academic offerings” [15].

The Digital and Computational Studies (DCS) program at Bates College is also an interdisciplinary approach that seeks to “bring computational thinking, practices, and theory to the full breadth of the liberal arts curriculum” [14]. Currently under construction, the core curriculum of DCS includes courses in software design and development (introductory through advanced), design thinking, and opportunities for “placing students’ learning in a broad societal context” [14]. Its inaugural course in 2018 focused on the integration of dance, electronic music, and computing. Digital and Computational Studies Chair, Matthew Jadud, describes the program as “a model for computing that is deeply inclusive and integrative.” He articulates connections between coding and pedagogical practices nested within larger social structures, stating that the program fosters “critical interrogation of practices in and out of the classroom. . . [and asking] meaningful questions about what computing education should look like as part of a liberal arts education” [14].

Pedagogical efforts such as these are at the vanguard.  While coding may foster creativity and problem-solving, especially through innovative pedagogical approaches that connect non-STEM fields, this is an embryonic trend for most liberal arts departments.  Although the concept of coding across the curriculum has been “celebrated and acknowledged in theoretical research, there has been a lack of practical projects” that use coding in non-STEM fields [5].  In addition, there are myriad practical challenges associated with teaching and learning coding that are just starting to be identified and would need to be addressed before coding across the curriculum becomes a widespread norm in the liberal arts.

Goldstone’s account of teaching literary data analysis offers an illustrative example of some of these challenges. His experience of introducing students to the R programming language was rife with pedagogical and epistemological obstacles.  He writes, “my argument, in brief, is that teaching this material is really, really hard, for reasons that are more than technical or technological” [9].  Some of the difficulty is located in the problem that “available strategies for teaching literary analysis under the “DH” (digital humanities) rubric [are] inadequate” [9]. The DH field—and likely other disciplines in the liberal arts—have yet to establish fully epistemological and methodological practices that guide the ways in which interpretation is to be done, and that, in turn, enable the determination of what the data produced through coding mean.

While Goldstone’s students gained proficiency in coding, he notes that “programming competence is not competence in analytical methods . . .  A programming curriculum can bring students only up to the threshold of method and not over it.” [9]. His students wrangled with data, but possessed a dearth of methodological knowledge about how to analyze the data.  “Though data-wrangling is indeed a crucial research skill, it should not come before the question of how to analyze data . . . otherwise, why wrangle?” [9].

The pedagogical problem that Goldstone and his class experienced was deeper than simply the issue of balancing coding instruction with analytical method.  Rather, the problem was the inchoate disciplinary issue of how to address “the problems of quantitative methodology as problems rather than passing them by, or, worse, imagining they have been solved because students are learning to code” [9]. This practical and epistemological predicament may be experienced by other liberal arts disciplines as they increasingly engage in the coding pedagogy of data science languages such as R, Python, and JavaScript.  As liberal arts disciplines take on various forms of coding, it may be that old as well as new forms of epistemology and methodology need to be examined.

This all leads to a core epistemological and practical implication for the pedagogy of coding in the liberal arts, and one that may re-center the liberal arts in higher education.  To the extent that coding pedagogies contribute to the increased generation of data, there is a recursive necessity that must be addressed. Data-driven forms of empiricism have been, until recently, created by disciplines that are not necessarily rooted in the traditions, methods, and analytics of the liberal arts.  Coding, and its associated practices, generate new forms of data that may call for new methodological, epistemological, and analytical approaches by which to make sense of them. This is true even for those disciplines that traditionally employ empiricist methodologies, e.g., experimental social sciences. Given the data created through digital coding—potentially vast amounts—older methods may not be up to the interpretive task.  How are coding pedagogy and practice not only to be taken up, but also to be understood by the liberal arts?

There are at least two implications regarding the present state of coding pedagogy in the liberal arts that suggest answers to this question.  First, as Kitchin presaged, “the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences, propose radically different ways to make sense of culture, history, economy, and society” [17].  The liberal arts may import coding from computer science, but the liberal arts disciplines, particularly those in the humanities and social sciences that possess rich traditions of critical and qualitative inquiry, are well-positioned to make valuable contributions to coding pedagogy in ways that imprint its own forms of meaning on the practices and outcomes of coding. Second, a further effect may be that, while interdisciplinarity has long been talked about and aspired to in higher education, in many instances, disciplines remain siloed. It is possible that, given the need to develop and use new methods associated with coding pedagogy, there may be a reinvigorated movement toward increased interdisciplinarity and institutional cross fertilization. Kitchin observes the effects of coding when he writes that “big data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted” [17].  We could revise this statement to also include the reality that “big data and new data analytics are disruptive innovations which are reconfiguring in many instances how research [and pedagogy are] (emphasis added) conducted” [17]. It may be that within this new context, the liberal arts are well positioned to move to the pedagogical and analytical center of this paradigm shift.

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