ISYE 6501
Introduction to Analytic Model
Homework 2 Latest Updated
Georgia Institute of Technology.
, ISYE6501_homework2
2024-05-30
Question 4
Q4.1
Traditional grading systems often fail to capture the nuanced differences in students’ knowledge and skills. As
a former part-time tutor, I observed firsthand that each student possesses unique strengths and weaknesses.
To address this, I propose categorizing students by their skill levels using clustering algorithms, which can
help tailor educational strategies more effectively.
To accurately assess and categorize students, we will use the following five predictors:
Speed and Accuracy of Task Completion: Evaluates how quickly and correctly a student completes assigned
tasks.
Problem-Solving Skills: Measures a student’s ability to understand problems, devise solutions, and execute
them efficiently.
Conceptual Understanding: Assesses the depth of a student’s grasp of fundamental concepts in various
subjects.
Practical Application: Evaluates how well a student can apply theoretical knowledge to practical, real-world
scenarios.
Q4.2
I first filtered the data by selecting the numerical values from the data set and then I scaled it. Afterwards,
I used the library factoextra which provides the optimal number of clusters using the total within sum of
squares. I set the range of K to be from 1-10 and the optimal value using the elbow method is k = 3. Based
on the cluster plot, 95.9% of the data was captured
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