Subject: Summary - 03/23
From: Smeet Poladia <[email-masked]>
To: Brian Junker <[email-masked]>
Cc: Zhuyi Xu <[email-masked]>, Zhou Lu CMU MSP <[email-masked]>
Date: Tue, 23 Mar 2021 17:35:18 -0400

Summary:

Using metric (success rate for initial opportunities, coefficients of AFM model for each student, assistance score, ranked average, number of opportunities) other than the proportion of correct responses in the first attempt.
Understanding the literal meaning (in a mathematical sense) of KCs.
Create a heat-map of responses to understand the distribution of NA values better.
For MATHia dataset (500 students, Grade 7), consider pairwise correlations and then finding the closest positive definite matrix.
For MATHia dataset (500 students, Grade 7), pick a group of KCs and examine them.
Make logit transformations for success rate.

On a side note:
These are the the screenshots of this cluster from the GGM plot. Although the KCs are named differently, they should probably be considered one (or two) math concepts based on literal mathematical meaning.

Thanks and have a great day!

Regards,
Elaine, Smeet & Zhou

Regards,
Smeet Poladia