In Management courses where case-study discussions form the core of learning, it is a challenge to ensure the participation of every student. To resolve this, IIM Sambalpur has recently introduced AI as a member of the faculty.
The institute has introduced an AI platform of a U.S.-based company named Breakout Learning in its MBA course, which is designed to moderate and evaluate small group discussions to tackle challenges such as unbalanced participation and limited professor visibility. Instead of one large group discussion where only the most articulate dominate, the class was broken up into smaller groups and each group discussion was monitored and assessed by video-enabled AI.
The institute has also signed an MoU with the company to develop India-specific AI-enabled case studies that can be taught worldwide. “The objective was to implement AI-facilitated case-based discussions as part of existing teaching practices at management schools such as IIMs”, said Prof. Mahadeo Jaiswal, Director, IIM Sambalpur.
What is the initiative?
At IIM Sambalpur, a pilot study was undertaken on five courses, which engaged 304 students from the first and second years. These trial cases included ‘Digital Transformation of Supply Chain: Toyota – A Waste-Free Way to Work’, ‘Entrepreneurial Orientation: REDBUS – The Next Step for Growth’, and others.
The case study content was given to the students three to four days before the session so they could study in advance. When students came to the classroom for the session, the setting was digital with no faculty member present at the beginning. The students were placed in groups of seven to nine members. Each group was given the responsibility to carry out discussions.
The session started with a brief online quiz to test if the students had read the material. After the quiz, the AI platform enabled guided discussions within each group. The system tracked student engagement, monitored contributions, and assessed individual and group performance. The whole discussion, including student contributions, was recorded and made available to the students and faculty for learning and reflection.
How AI evaluated?
The AI algorithms evaluated each student based on Bloom’s Taxonomy, which teachers use to identify learning stages in students. It rated responses on six levels of cognition from simple recall of facts to the generation of innovative concepts.
Students who just remembered facts were given lower grades, while students who used concepts well or produced new ideas were given higher grades. When students just recalled facts, they were awarded one mark. Those who elaborated on the discussion were awarded two marks, and those who developed a new product or service got six marks. “Students who try to contribute without deep insights are given lower grades, emphasizing the value of reflective analysis”, said Prof. Jaiswal.
How has it helped teachers?
The shift in teaching methodology begins before the classroom session even starts. The AI-enabled discussion gives teachers insights into students’ comprehension levels, areas where they struggle, recurring themes, and debate-worthy viewpoints.
Faculty members then return to the classroom and break down students’ answers. They elaborate on the best ways to improve analytical and critical skills in students. “This complementary intervention made certain that students would not solely use AI-produced responses but also derive benefits from professorial mentorship”, said Prof. Jaiswal.
The classroom of the future is not driven by AI alone but through the synergy of technology and human knowledge. This takes the administrative workload off professors’ shoulders. “It allows them to steer richer intellectual exploration instead of micromanaging discussions. This does not reduce the teacher’s role but elevates it”, said Prof. Jaiswal.
This shift gives teachers additional research and case writing time. Prof. Jaiswal says that the greater the research we do, the greater the number of India-specific case studies we can create, thereby ensuring that MBA students learn through applicable, context-specific business situations.
IIM Sambalpur is working towards creating more India-specific AI-driven case studies that are to be used around the world. These cases will be written by the institute’s faculty. Prof. Jaiswal says that business cases were earlier created by Harvard and then converted into AI versions. “The motive behind this program is based on IIM Sambalpur’s vision towards innovation in learning and transforming age-old learning models”, said Prof. Jaiswal.
Facilitates self learning
In the past, only high-achieving students gained from class discussions since others passively listened. With each student attending a regular 90-minute classroom meeting with 90 students, one-on-one opportunities to speak come down to fewer than one minute. “Now, thanks to AI, all students are engaged, and there can be equal participation”, said Prof. Jaiswal.
The main benefit of AI-facilitated learning is that it gets students to read and discuss before class. It changes the conventional professor-led model to a more student-centered model. Students come to class with a better grasp of the material, which enables better classroom debates. “Professors can then introduce more state-of-the-art topics, sharpen case study methods, and develop new learning opportunities”, said Prof. Jaiswal.
Long-term goals
The AI-based learning pattern is being phased in, with two AI-based case studies per course initially, then four, and finally six in the years to come. The long-term goal is to incorporate AI-facilitated discussions into a minimum of 50% of the course lectures so that students are actively engaged in discussions instead of passively listening to lectures. “The long-term effect is likely to be significant, with students being more effective communicators, critical thinkers, and active learners”, said Prof. Jaiswal.
Challenges
The institute worked to prepare a student feedback report to understand their perspectives on the initiative. Most students rated the experience positively. Only 19.4% of students did not find it useful.
Some students failed to properly prepare the cases before class. They could not meaningfully contribute and were challenged by the AI assessment. Prof. Jaiswal says that a few of the students, especially introverts, did not want to make active contributions in class. AI marks the responses, so those students suffered a reduction in marks for their hesitation. “Consequently, these students thought that case discussion through AI can be done away with in favour of professor-facilitated classes”, said Prof. Jaiswal.
Prof. Jaiswal says these problems were managed by initiating corrective measures like highlighting active participation. “We made efforts towards making students see the relevance and importance of classroom discussions”, he said.
Published – March 07, 2025 03:54 pm IST