---
date: "2025-10-02T00:00:00Z"
categories:
  - linkedin
  - llms
description: I updated my Tools in Data Science course and used LLMs to analyze student feedback from IIT Madras. I found that students actually value "desirable difficulty" and rigor, suggesting that high-pressure assessments can increase perceived educational value.
keywords: [data science education, llm analysis, student feedback, desirable difficulty, iit madras, course design]
---

Tools in Data Science Sep 2025 edition is live: https://tds.s-anand.net/. Major update: a new AI-Coding section and fresh projects.

I teach TDS at the Indian Institute of Technology, Madras as part of the BS in Data Science. Anyone can audit. The course is public. You can read the content and practice assessments.

I fed the May 2025 term student feedback into The Sales Mind and asked:

- _What are the top non_-_intuitive_ / _surprising inferences_?
- _What are interesting observations_?
- _What are high impact actions_?

Full analysis: https://lnkd.in/gVWVqaxN: summary, outliers, and action ideas.

Most students find the course tough (or at least time-consuming), especially the Remote Online Exam (ROE).

**Surprise**: students who mentioned ROE time limits rated it 2.61 vs 2.33 (+12%!). Those who felt time pressure also saw more value -- suggesting "desirable difficulty," rather than frustration.

A minority even asked for _tougher projects_.

The main actions are faster feedback loops, automated pre-checks, mock ROEs, clear rubrics, etc.

But my two takeaways are:

- Students value rigor and challenge, even if it makes the course harder.
- Using LLMs to analyze student feedback is a force multiplier for instructors.

[LinkedIn](https://www.linkedin.com/posts/sanand0_mimicking-developer-styles-with-coding-agents-activity-7378303257724706816-ydlR)