Artificial intelligence, changing industry expectations and concerns around student wellbeing have prompted BITS Pilani to rethink its undergraduate curriculum. The revised approach places greater emphasis on hands-on learning, design, experimentation and problem-solving, alongside changes to how students manage their academic workload. The university is also investing INR 50 crore in upgrading undergraduate laboratories across its Pilani, Goa and Hyderabad campuses to strengthen practical learning.In this conversation with ET Education, Prof V Ramgopal Rao, Group Vice Chancellor of BITS Pilani and former Director of IIT Delhi, explains why the university undertook the overhaul, what it wants to change about the undergraduate learning experience, and how the curriculum is expected to prepare students for an AI-driven workplace. Q. What prompted BITS Pilani to overhaul its undergraduate curriculum? How did industry partners and other stakeholders contribute to the revamp?Prof Rao: AI was an important trigger, but we also wanted to take a fresh look at how students spend their years at BITS. Getting information is easy now. Applying it to an unfamiliar problem, or building something that actually works, is much harder. We felt students needed more room for that kind of learning. We also wanted the curriculum to take their physical and mental wellbeing seriously. Credit for this exercise goes to approximately 250 faculty colleagues who contributed across departments and campuses. They looked at the content of courses, how we teach them and the time students need to learn properly. BITS has the advantage of a close relationship with industry through Practice School, research and our alumni. We get to see how expectations at the workplace are changing. Alumni working in leading AI companies have also been helping us teach these subjects. Alongside these inputs, student feedback helps us understand workload and the choices students want to make. The academic decisions have to bring these perspectives together while preserving the depth of a BITS education. Q. How does the revised curriculum differ from the traditional engineering and science education model, and what impact will it have on student learning and placements? Prof Rao: BITS has offered academic flexibility and industry exposure for decades. With this revision, we are giving students more opportunities to design, experiment and build during their coursework. Engineering Design and Prototyping, for example, gives them an opportunity to turn an idea into something they can test. There will be more problem solving in class and more project work, with fewer conventional quizzes and written tests. Another change is that credit hours now include self study and reflection. A timetable tells only part of the story of a student’s workload. If we want students to spend time on a serious project, that effort must be recognised when we plan their courses. We have also included about 60 hours of structured activities covering fitness, creativity, wellbeing, social conduct and community engagement. These experiences deserve a place in university education. On the academic side, we have spent INR 50 crore this year upgrading undergraduate laboratories at Pilani, Goa and Hyderabad. Students need access to equipment that reflects what is happening in their fields.I would expect the benefit in placements to come from students being better prepared to take on real work. Through Practice School, they already get substantial industry exposure. They should now be able to bring more practical experience to those assignments. Of course, we will have to see the outcomes as these batches graduate. My concern is also how well they do five or ten years into their careers. Q. As AI reshapes entry-level jobs, how will the new curriculum prepare students for the evolving job market? How is the faculty being trained to deliver it effectively?Prof Rao: A student joining us today will graduate into a job market that is difficult to predict. Some routine tasks that graduates used to begin their careers with are already being done with AI assistance. This makes it even more necessary for students to understand their subject well. If an AI tool gives an incorrect answer, they should know enough to question it.I look at AI education through three As: Adoption, Absorption and Application. Students first learn to use the tools, then understand how they work and where they fall short, and finally apply them to problems that matter. We need to take them through that entire process. The ability to ask a good question and decide whether a solution will work is going to remain valuable even as the tools change.For faculty, our Teaching Learning Centres are supporting the changes through workshops on teaching and learning. We have also brought alumni from companies such as OpenAI, NVIDIA, Microsoft and Google into AI teaching. But a workshop by itself is only a beginning. The real work is for a faculty member to go back to a course and rethink the assignments, classroom activities and examinations. Faculty need opportunities to try these approaches and learn from one another. This has to continue as the technology evolves.Q. How will AI education benefit students across disciplines, including sciences and management, and how will it be integrated into non-engineering programmes?Prof Rao: AI will be useful wherever people work with data, make decisions or look for patterns. A chemistry student could use it to study molecular properties. A biology student could use it to analyse experimental results. In management, it can help with demand forecasting, supply chains or understanding customers. The questions will be different in each discipline, and the teaching should reflect that.Our revised undergraduate curriculum provides a foundation in computational thinking and programming. Students can then take courses such as Foundations of Data Science and AI in Chemistry, with more AI and machine learning electives being developed. This gives them a way to connect AI with the subject they have chosen to study. The examples, projects and level of mathematics need to suit each programme.At BITSoM, data and AI are already part of how students learn to exercise managerial judgement. A manager has to understand the assumptions behind a recommendation and what acting on it could mean for the business or its customers. Similar questions arise in the sciences. How good is the data? Does the result make sense? Can it be tested? These are questions we want students to get used to asking. Privacy, bias and responsible use become much easier to understand when taught in that context.Q. How will UROP, Advanced UROP and Super UROP expand students’ access to research opportunities, faculty mentorship and funding?Prof Rao: We want students to get a taste of research early enough to discover whether it interests them. The Undergraduate Research Opportunities Programme, or UROP, gives them a starting point with a basic research project. Advanced UROP and Super UROP allow them to take on more substantial work as they gain experience. The three carry 9, 18 and 27 credit hours respectively, so the growing effort is recognised within the degree.The time spent working with a faculty member is particularly valuable. A student learns how to narrow down a question, read what others have done and decide how to investigate it. Often, the first approach does not work. Learning why it failed, and what to try next, is part of becoming a researcher. As students progress, they should be able to take more responsibility for these decisions.Resources matter here. Alongside these research opportunities, we already fund over 100 student projects addressing societal problems and encouraging entrepreneurship. Students can develop and test their ideas with financial support, laboratory access and guidance from faculty. Practice School mentorship and entrepreneurship pathways can help take promising work further, including towards a venture where that makes sense.Some students will discover that they want to pursue research. Others will carry the experience into industry. Either way, there is considerable value in having worked on a problem without a ready answer and stayed with it long enough to produce something useful.
