For students today, coding is not merely a technical skill to be used in isolation. It has now become part of a larger and vibrant digital culture, helping to shape learning, trends, and culture, all made possible through memes, augmented by artificial intelligence, and supported by an endless array of connected applications. In the past, coding was often taught in textbooks or formally, and in a classroom. In contrast, Gen Z (or whatever comes after it) is embedding programming into viral experiences, humor, and mobile and connected tools.

Memes as a Pedagogical Practice

While often considered trivial, memes have become a means of learning and a way of expressing for Gen Z. Memes populate the internet with coding-related content that compresses complicated programming concepts into humorous, relatable images. A meme illustrating recursion with mirrors facing each other, for example, communicates abstractness through visualization

Educational research related to digital pedagogy indicates that humor and visual association can greatly enhance retention while lowering the resistance associated with difficult subjects. Surveys with computer science students show that the use of informal content (e.g., memes, short videos, jokes about coding) as entry points to new topics (a marker of digital culture) is increasing. Perhaps the most important thing to recognize in these changes is this: learning now transcends formal communication modes like texts or lectures; it is embedded in the cultural tradition of everyday digital communication.

The Rise of AI Companions in Coding

The second significant shift involves the emergence of various AI tools. These AI assistants are not enhancements to Generation Z’s learning style. In the survey data from developers, the majority of students and early-career programmers now utilize AI assistants for bug checking, generating snippets, or brainstorming for solutions.

Both opportunities and challenges arise from this situation. AI is clearly lowering the barriers to entry for coding. The AI assistants and tools make coding more accessible to novices.

In their initial attempts and approaches to coding, students have immediate access to explanations, alternatives to purported rules, and examples, thus shortening the cognitive gap in the learning process. There is also, however, a risk of superficial thinking if learners and students casually copy AI-generated solutions without engaging in a critical exercise of considering whether a solution is right for the particular context.

For students, the real skill is not “memorizing all the syntaxes” but learning to direct, interpret, and validate the output of AI. So in a way, coding is less about memorization today and more about framing a problem, analysis, and validation.

Apps are another storyline for Gen Z on their coding journey. The other generations used either documents printed on paper or integrated development environments (IDEs), while those using coding have more access today to a variety of coding apps and platforms.

Mobile coding environments, gamified environments like Grasshopper or Mimo, or collaborative spaces like Replit have changed our thinking of where coding can occur — when and where.

In survey results, many respondents said they do “micro-learning” while traveling on a commute, during breaks, or while hanging out with friends. This hybrid learning is now more aligned with the trend of learning-on-demand. Hence, this is also a generation of relatively flexible, self-directed learners who have a habit of learning in pieces frequently.

Implications for the future

1. Coding as Culture: Learners in social and cultural spaces, with memes, learning becomes more integrated within those cultural modes. More democratized programming knowledge should lend itself to becoming a bit more informal. How will academics change to embrace these modes of cultural engagement while maintaining academic rigor?

2. AI as Co-Coder: The next generation of programmers will not be competing against AI, but rather with it. Developers of the future will need to have expertise in system-level thinking, testing, and security, while continuing to consider AI as an accelerant rather than a replacement.

3. The Empowering and Everywhere Learning Experience: For the learner, the experience of coding is no longer going to be on a desktop or in a computer lab. Students will experience both learning and project making on mobile devices and through the cloud and collaborative tools. How can formal education systems support nimble app-centric formal curricula with curricula focused on self-directed, multi-modal, and self-paced learning without being less thorough?

Generation Z are coding differently, situated in an era where memes are cultural shorthand, AI assistants are common place, and apps are the natural learning media for solving problems.

All of these are not trends or fads; they are systemic shifts in how people will experience programming in context.

The opportunity for students is to leverage these different contemporary learning and performing modes in programming, but to do so critically. Memes offer a way to present learning in a more approachable manner, but cannot actually replace the context of rigour and depth study; AI offers speed to everyday development, but AI is not a replacement for human trust and verification; while Apps could democratize coding and make it accessible, ubiquitous and portable, they still require rigour, practice, and reflection to utilize effectively.

Coding’s journey into the future will not be defined by voiding the fundamentals; it will be act of engaging the fundamentals, or revisiting and meaningfully using those fundamentals, and all the experiences, in these new contexts culturally and technologically. The students (or anyone engaged with coding) who do succeed will be those who traverse the boundary between creativity and rigor, fluency with cultural and curiosity along with deep understanding of the technical.