IUST ATTENDANCE SUMMARY
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last update
Subject breakdown #
Monthly attendance detail #
AI Summary #
using model: llama-3.2-3b-instruct
Visualizations #
Attendance radar
What is this?

Compares attendance percentages across all active subjects against a dashed 75% target baseline.

Any data points falling inside the central dashed polygon indicate subjects trailing behind the required threshold.

Effort map
What is this?

Maps classes held (X-axis) against attended classes (Y-axis). Bubble size indicates attendance volume.

Red bubbles furthest to the right require immediate attention—they represent high-frequency classes missing a large absolute number of lectures.

About this project #

This is a live page for the academic attendance of Mohammad Azeem Wani from iust.ac.in.

It was built out of sheer necessity. Going to the IUST portal, hoping your session hasn't expired, navigating to the attendance section, manually marking the checkboxes for every single month, and then fetching the attendance for each subject one by agonizing one... it was incredibly tedious.

Psychological research—famously encapsulated by Miller's Law—shows that the human brain can only hold about 7 items (plus or minus two) in its working memory at any given time. This is the exact reason why we struggle to hold a new 7-digit phone number in our head before writing it down—our mental scratchpad simply fills up. By the time I've clicked through all those portal dropdowns and menus, my working memory is completely maxed out. Add the mental math required to figure out exactly how many classes I need to attend to escape the "risk zone" for multiple subjects? It's pure cognitive overload. This dashboard automates the heavy lifting, so I can actually understand my standing at a glance without frying my brain.

Feel free to contact me if you want to know more at me@mohammadazeem.in.