Artificial Intelligence Can’t Wait: Why Students Must Be Involved in Shaping the Curriculum That Shapes Their Future

Students of computer science continue to learn from syllabi that have not changed significantly in the past ten years. The fundamentals of machine learning are taught through rote memorization, algorithms are analyzed on paper, and coding exercises revolve around contrived scenarios. In the meantime, the world is changing due to advancements like GPT-4, autonomous systems, and AI-empowered diagnostics.

This mismatch is no longer just an inconvenience; it’s an educational crisis.

Our teaching methodologies and the expectations we set for students are not aligned with the realities of the world in which these students are intended to become leaders. In the era of AI, blockchain, and quantum computing, the rate of change requires an equally radical response an on-demand evolving curriculum that adapts to the emerging technology, and not the other way around, and students not only turn out as learners, but as co-creators of their learning pathways.
It is a call to action, not an academic criticism. Education aims to equip learners with knowledge and skills for the world beyond the classroom learning; therefore, it invites students to have a say in what and how they are learning.

The Disconnect Among Academia and Industry

Universities are falling behind with the growing AI-driven industry. In addition to programming languages, software engineers now they need to knowledge cloud computing, machine learning frameworks, Docker containerization, ethical algorithmic decision-making, etc. However, the subjects are unfamiliar to many graduates.
Let's take a different approach to this issue. How many undergraduate students have experience designing AI models, let alone fine-tuning them, while implementing AI in their marketing, customer service, and other verticals? How many can describe the societal repercussions of AI bias and have experience working with live datasets and creating GitHub portfolios?

There are not many who fit this description. The explanation for this is quite straightforward: education is built around a stagnant and irrelevant framework with no connection to the world outside the classroom.

AI-Readiness Needs More Than Just a single Course:

Being "AI-ready" does not mean merely enrolling in an elective course on artificial intelligence or machine learning during the concluding semester. Rather, it signifies an encompassing mindset that requires a cross-disciplinary foundation and a comprehensive set of skills. These should be cultivated from the outset of a computer science curriculum.

A graduate who is prepared for AI should:

• Comprehend both the theory and practical applications of machine learning and deep learning.
• Solve practical real-world problems by working with datasets.
• Work together across fields (e.g., AI in law, AI in medicine).
• Recognize the ethical, societal, and legal issues surrounding AI.
• Use projects, publications, or portfolios to showcase abilities beyond exams.

The fact that most of our curricula fall short of even two of these indicators is troubling. More than ever, universities must embed AI not just as a subject, but as a foundation shaping culture woven into programming, design, ethics, and application.

Curriculum 2.0: Co-Designed, Co-Own, Innovate

So, what strategies can we employ to build a curriculum that accommodates evolving shifts in circumstances? There is a remarkable and straightforward answer to this problem: students need to be part of the solution.

Curriculum design has historically been a top-down process, resulting in significant delays in the revision of syllabi after their initial creation and subsequent approval by committees. This approach mirrors the problematic practice of consistently delivering outdated software in fast-paced fields such as computer science.

We must establish what I call “A Curriculum 2.0,” which contains the following characteristics:

• Agile: Must undergo annual or bi-yearly evaluations.
• Student informed: Shaped and moulded based on actual, solicited feedback from students.
• Flexible: Offers multiple options to create customized pathways
• Industry aligned: Guided feedback from respected tech industry leaders, emerging enterprises, and alumni.
• Experimental: Encourages swift project-based learning and fosters the foresight to “fail” in the process.

When students become a part of curriculum review boards, academic councils, or innovation panels, they are immediately immersed in the world of academic learning and “real life” because of the current work they do. Many are eager to be a part of expanding the world of AI through open source initiatives and are part of the workforce through ventures like hackathons and their own startups.

This leads to a question: Are their ideas significant and noteworthy? Absolutely. Their insights are not just valuable, they’re crucial.

Why Students Need to Raise Their Voice on Curriculum

Students are innovators, adventurers, and tomorrow's leaders in our community, rather than simply being passive recipients and absorbing information. However, we frequently leave them out of choices about what and how they should be taught. This is a lost chance.

Involving students in curriculum development will benefit everyone:

• Students are the first to notice new trends and technologies.
• Taking charge of one's education boosts drive and output.
• They encourage the system to tackle practical problems and come up with original solutions.
• A range of student perspectives contributes to the creation of accessible, inclusive content.

Forward-thinking organizations are already undertaking this approach all over the world. The advisory board for Stanford University's computer science curriculum includes students. Curriculum hackathons are regularly held by EPFL in Switzerland. Credit transfer, modular certifications, and blended learning models are gradually being made available by Indian institutions under NEP 2020. These indicate a shift.

The Role of Computer Science Departments

As a computer science professor, I think this shift needs to be spearheaded by our departments. Since computer science is at the core of technological innovation, its curriculum needs to be equally agile.

• Departments of computer science can now do the following:
• Establish student curriculum councils as ongoing advisory groups.
• Implement feedback loops to enable continuous improvement after each course.
• First-year courses should be redesigned to cover AI literacy in addition to programming.
• social impact, AI in agriculture, or ethics in algorithms.
• Promote student research that can be published and open-source contributions.

We must also engage in self-examination. Educators should remain current with the latest technological advancements and be open to exploring innovative teaching strategies, such as project-based learning, micro-courses, and flipped classrooms.

Student university selection processes must adapt alongside. Instead of relying solely on rankings or reputations alone, students should consider:

How frequently are the curriculum revisions done?

• Are there labs or cells for AI startups?
• Is there offered electives from multiple fields of study?
• Is there a focus on results such as portfolios, internships, and publications?

India at a Turning Point

Having the greatest youth populace in the world, it puts India on the threshold of being a global technology settler. We have the figures, now what is needed is the preparedness.
To truly harness our demographic dividend, universities alone cannot supply graduates. These must become visionary technologist, ethical innovators, and adaptable problem- solvers.
Space technology, climate change, and AI as well as quantum computation are far from being remote fantasies. These are prospects available today, yet they demand a world-changing curriculum and students capable of active involvement in the designing process.

Outdated methods of viewing the curriculum as a fixed entity must be abandoned. In this context, students should be seen as catalysts for change, and classrooms should function as laboratories, actively participating in the reimagining of education.

The job market is evolving at the speed of technology. So why hesitate?

Let us have confidence in our students regarding both their learning outcomes and the design of their educational experiences. Empowering students through trust enables them to take the essential steps toward a promising future.

We’re racing into an AI-powered future. Let’s make sure our students aren’t just passengers, but drivers of the journey

(This article is written by Dr. Yasir Afaq, Assistant Professor, Department of Computer Science and Engineering, SRM University – AP- Amaravati. This is an opinionated article; EPN has nothing to do with this editorial.)