The AI Era: When Learning Spaces Must Transform into Workspaces
Artificial intelligence (AI) is transforming almost every sector, including higher education. Previously, the primary challenge for universities was how to transfer knowledge to students; now, the issue has shifted.
Knowledge is becoming increasingly easy to obtain through AI, digital platforms, and open learning resources. What is becoming more important is how students are able to use that knowledge to solve real-world problems.
This change demands that universities undergo a transformation. Learning spaces can no longer be defined merely as lecture halls where lecturers deliver theory. Students need to experience firsthand how knowledge is applied in professional work, so that the learning process occurs alongside the working process.
Therefore, project-based learning, studios, simulations, field visits, and the involvement of industry practitioners are becoming increasingly relevant. Students must not only understand concepts but also learn to read technical documents, understand project schedules, recognise cost, quality, and time risks, and practice decision-making in situations that closely mimic real-world conditions.
One approach being implemented is the concept of ‘Workplace Credit Units’ (SKS Ruang Kerja), which is a learning model that places students in professional work environments as part of the curriculum. The essence is not merely an internship, but rather turning the workspace into a learning space.
The experience of the Landscape Architecture Study Programme at ISTN provides an illustration of this approach. Through the ‘Workplace Credit Unit’ programme spanning two years, students begin entering professional work environments from their third semester.
They learn alongside lecturers, practitioners, and partner companies in activities that are inherently part of the landscape architect profession. Interestingly, students are not placed as administrative staff or general interns.
They are introduced directly to tasks that align with their programme’s competencies, such as project management, the preparation and interpretation of S-Curves, understanding hardscape technical specifications (RKS), simulations of pedestrian bridge projects, and site visits. Such material is certainly not easy for early-semester students.
However, exposure to the complexity of work from an early stage helps them understand the professional standards they will face after graduation. Feedback from partner companies indicates that this approach provides significant benefits.
Students who are accustomed to reviewing technical documents, understanding project workflows, discussing with consultants, and following the rhythm of professional work tend to adapt more quickly when entering the workforce.
Ultimately, industry does not only require graduates who master theory, but also prospective professionals who can work in teams, understand processes, ask the right questions, and learn from field experience.
It is in this context that AI finds its role. AI can assist students in understanding difficult concepts, summarising technical documents, creating simulations, drafting reports, and acting as a 24/-hour learning companion.
However, AI cannot replace the experience of facing real projects, interacting with clients, resolving conflicts on-site, or bearing professional responsibility. Such experiences must still be gained through direct practice.
Naturally, questions arise regarding scale. With millions of students in Indonesia, must they all be placed within companies? The answer is not necessarily.
A ‘workplace’ can be defined more broadly. Companies, laboratories managed to industry standards, teaching factories, research centres, government agencies, startups, or collaborative digital projects with practitioners can all serve as both workspaces and learning spaces.
The most important factor is that students perform work relevant to their field of study and receive adequate guidance. This transformation requires closer partnerships between universities, industry, government, and professional organisations.
However, such an investment will produce graduates who are better prepared to face the increasingly rapid changes in the world of work. In the AI era, the advantage of a graduate is no longer determined solely by their GPA or the number of courses completed.
What becomes increasingly decisive is the experience of solving real problems, the ability to use AI responsibly, project portfolios, and the readiness to contribute from the very first day of work.
It is time for campus learning spaces to evolve into educational workspaces, ensuring that higher education produces not just scholars who know many things, but young professionals who are ready to make an impact.