Abstract

The curriculum for modern design disciplines, specifically Interactive Design and Technology (IDT), increasingly incorporates computer programming as a fundamental requirement. This integration challenges the traditional separation between visual aesthetics and technical implementation. This article examines the pedagogical and professional justifications for teaching coding to design students. It analyzes the concept of “computational thinking,” a cognitive process that allows designers to understand the constraints and possibilities of the digital medium. Research from the Association for Computing Machinery (ACM) indicates that designers with programming literacy produce higher fidelity prototypes and engage in more effective problem-solving. Furthermore, studies published in The Design Journal demonstrate that coding knowledge bridges the communication gap between designers and software engineers, reducing production errors. Data from the World Economic Forum identifies technological literacy as a critical skill for future employability, distinguishing hybrid designers from traditional graphic artists. The text argues that the objective of this education is not to convert designers into full-stack engineers, but to create “T-shaped” professionals who possess deep visual expertise and broad technical understanding. This cross-disciplinary approach ensures that graduates can navigate the complex ecosystems of user experience (UX) and creative technology.

Keywords: Computational thinking, design education, creative coding, interactive design, technical literacy.

Coding for designers: why are IDT BINUS students taught programming basics?

High school students entering university design programs often expect a curriculum focused exclusively on drawing, typography, and color theory. However, the Interactive Design and Technology (IDT) program at BINUS University mandates that students acquire a working knowledge of programming languages. This requirement reflects a structural shift in the global design industry. The separation of visual conception from technical execution is disappearing.

The logic of computational thinking

The primary objective of teaching code to designers is the development of computational thinking. This term refers to a method of problem-solving that involves expressing solutions in ways that a computer can execute. Wing (2006) defined computational thinking as a fundamental skill for everyone, not just computer scientists, involving abstraction and decomposition.

For a designer, understanding variables, loops, and conditional statements changes how they approach a layout. They stop seeing a design as a static picture and start seeing it as a dynamic system. A study published in The Design Journal by Taylor & Francis noted that students who engaged with material-based programming developed a deeper understanding of the “grain” of the digital medium (Giaccardi & Karana, 2015). Just as a sculptor must understand the properties of clay, a digital designer must understand the properties of code to push the medium to its limits.

Bridging the gap with engineering

A persistent friction point in the technology industry is the “hand-off” between design and engineering. Designers often create complex visual interfaces in static tools like Figma or Adobe XD that are difficult or impossible to implement in actual code. This leads to production delays and compromised user experiences.

Research from the ACM Digital Library highlights that shared knowledge bases facilitate better collaboration. When designers understand the basics of HTML, CSS, or JavaScript, they create designs that account for technical constraints. They speak the same language as the developers. This shared vocabulary reduces misinterpretation during the development cycle. Looking at industry workflows, Vorvoreanu et al. (2017) found that UX professionals with technical competence were rated as more effective team members because they could empathize with the implementation challenges faced by their engineering counterparts.

Prototyping fidelity and interactivity

Static images cannot fully convey the feel of an interaction. A designer might draw a button, but a drawing cannot demonstrate how that button behaves when pressed, hovered over, or disabled. To test an interaction properly, a designer must build a prototype.

Modern interface design relies on high-fidelity prototyping. Tools like Processing or p5.js allow designers to write code to generate visuals and interactions that react to user input in real-time. A paper in the MDPI journal Multimodal Technologies and Interaction discussed how algorithmic design tools enable creators to explore complex patterns and behaviors that manual drafting cannot achieve (Berni & Borgianni, 2020). By writing code, IDT students can create functional prototypes that prove their concepts work before a dedicated engineering team begins full-scale development.

Employability in the digital economy

The economic reality of the 2020s demands hybrid skill sets. Purely aesthetic skills are increasingly commoditized or automated. The World Economic Forum (2023) listed “technological literacy” and “analytical thinking” among the top skills in the Future of Jobs Report 2023.

Employers in the technology sector prioritize candidates who can span multiple domains. A designer who can tweak a front-end script is more valuable than one who requires an engineer to make minor visual adjustments. This versatility aligns with the concept of the “T-shaped” professional, who has deep expertise in design (the vertical bar) and a broad understanding of related technical fields (the horizontal bar). The IDT curriculum prepares students for this reality by ensuring they are not helpless when faced with a terminal window or a script file.

References

Berni, A., & Borgianni, Y. (2020). Applications of generative design for the creation of consumer products: A review. Multimodal Technologies and Interaction, 4(4), 79. https://doi.org/10.3390/mti4040079

Giaccardi, E., & Karana, E. (2015). Foundations of materials experience: An approach for HCI. The Design Journal, 18(3), 447-464. https://doi.org/10.1080/14606925.2015.1059396

Vorvoreanu, M., Gray, C. M., Parsons, P., & Rasche, N. (2017). Advancing UX education: A study of the subject matter UX professionals value most. Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, 713-722. https://doi.org/10.1145/3027063.3053335

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215

World Economic Forum. (2023). The future of jobs report 2023. World Economic Forum. https://www.weforum.org/publications/the-future-of-jobs-report-2023/