Suppose you are teaching “Introduction to Business Analytics” to a professional audience (e.g., MBAs or EMBAs). The diverse set of student background often make it hard to deliver personalized learning experiences to each student. As one example, students from a tech-savvy background would likely embrace technical content but may need more support in managerial insights, whereas students from a more managerial-oriented background may not know how to code at all but still would like to learn data-driven decision-making. A traditional design of the course often needs to spend a few weeks just to teach students the basics of programming (which make some bored and others overwhelmed). In this blog, we will show you how Mentorica AI allows you to easily build a business analytics course that “meets each student where they are”.
If you haven’t already, please register for a free instructor account on our instructor portal.
Step 1: Create a Course
The first step is to create your course in the instructor portal, which will become the one-stop location for you to configure AI agents, manage students, monitor activities, etc. Creating a course is easy, simply go to “My Classes” on the top right navigation, click on “Add New Class”, and the fill in your basic course information.
If you are not yet ready to launch an actual course, the “DEMO101” course available to you upon account creation is a good place to try things out (and it’s free).
Step 2: Pick the AI Activities
It is often more effective to teach business analytics topics not as abstract concepts and algorithms but as concrete business problems rooted in practice. This is why Mentorica has curated a comprehensive set of AI-powered activities for you to choose from. Each activity covers an important topic in business analytics and consists of (1) description of a concrete business problem, (2) the associated dataset, and (3) an AI agent specifically built to provide learning support for this problem. The AI agent has access to the problem description file as well as the dataset, and can answer questions about the business problem, write and execute code to carry out various analyses, and assist students in other tasks related to the focal problem (e.g., brainstorm managerial recommendations after running some analyses). Depending on your pedagogical design, you can assign these activities as in-class practices, case discussions, or homework assignments. As an instructor, you will also get a teaching note with learning objectives, prompt template, and recommended discussion questions.
After adding one or more AI activities to your course, you can further configure them (e.g., start / end dates and visibility options) and assign them to individual students or student teams. Please see this tutorial for more details on AI activity configurations.
We also support building custom AI activities with your own teaching materials. Contact us and we will work with you to build and deploy your custom AI activities.
Step 3: Align your Teaching Strategies with Selected Activities
From our own experiences teaching with Mentorica, AI agent-based learning activities are most effective when they are aligned with your overall teaching strategies. For instance,
- If you prefer in-class engagement and discussions, you can briefly demo the AI agents and then have students interact with them during class (e.g., a 30-min working session on customer segmentation with our Global Bank case). Students can ask questions and discuss with each other while they explore.
- If you would like students to work on the AI activities in their own time and pace, you can use the activities as homework assignments. We recommend setting clearly specified deliverables that encourage use of the AI agents — e.g., a written report of customer spending analyses and insights for the Catalog Co. case; or a presentation of marketing campaign strategy for the Universal Bank case.
Regardless of your pedagogical choice, Mentorica supports you in your classrooms. Our early adopters have used Mentorica to innovate the ways they teach business analytics. See below for a few testimonials.
Indranil Bardhan (UT-Austin): I used two of the Mentorica cases along with their RAG AI agent for in-class exercises with my MBA students at the McCombs School of Business. The students loved the use of the conversational (text) chatbot to do a deeper dive into analytics problems related to market segmentation and prediction. They were not only able to understand how to utilize the agent to run different algorithms but were able to test the robustness of the RAG to extract relevant business insights from the underlying data sets. Overall, it received very positive feedback as a way to provide experiential learning to managers and working professional MBA students.
Zhuoxin "Allen" Li (University of Wisconsin-Madison): I’ve had the opportunity to integrate dab.bot into my case-based teaching, and the experience has been nothing short of transformative. While AI tools are often praised for their ability to summarize cases or answer conceptual questions, dab.bot truly stands out in its quantitative capabilities—data visualization, customer segmentation, programming support, and more. My Professional MBA students were impressed by how seamlessly the tool handled complex analyses that would typically require significant time and effort. Interestingly, its strong analytical performance also pushed me to rethink my teaching approach. In the past, I might have designed a case discussion around discovering insights through guided questions. Now, with students able to extract insights from the bot almost instantly, I find myself focusing more on how to interpret, challenge, and extend those insights in meaningful ways. This shift enhances the depth of our discussions rather than diminishes them.
For instructors who may be hesitant, I’d suggest that dab.bot is not a threat to the case method—it’s a complement. In fact, the service opens the door to pedagogical innovation: simulating agent-based negotiations, supporting role-based debates, and enabling students to explore multiple strategic perspectives with real-time feedback. These capabilities enrich rather than replace what we already do in the classroom. One classroom experiment I found effective was to have students attempt a data task (e.g., customer segmentation) without the AI assistant first, and then again with dab.bot. The comparison sparked lively discussions about delegation, collaboration, and the quality of AI-generated insights—skills highly relevant to today’s managerial context.
Overall, dab.bot is not just a useful tool—it’s a pedagogical catalyst. It supports both faculty and students in elevating their learning experience and adapting to the future of work and education. I strongly recommend it to anyone teaching with cases, especially those looking to integrate more analytical rigor and AI literacy into their courses.
Wen Wen (UT-Austin): I’ve found Mentorica to be an incredibly effective tool for helping students in my professional MBA course to engage with analytics without the need to code. Its ChatGPT-like interface allows them to focus on using data to generate actionable business insights while also learning how to write effective prompts to interact with Gen AI. Students love how intuitive and powerful it is, and it’s been a great way to build both their data analytics skills and AI skills.