Exploring Patterns of Online Instruction Usage for K–5 Students Using K-Means Clustering

• In Event: AERA Poster Session 10
  In Poster Session: Division D Section 1 Poster Session 3

Abstract

Data mining techniques have emerged as valuable tools for gleaning insights from the veritable ocean of data made available through online instruction and assessment. However, research on online instruction usage patterns using time-series variables have primarily focused on secondary education students. This study uses k-means clustering to identify patterns in weekly usage amongst younger students. Follow-up analyses investigated the relationship between cluster membership and measures of student success.

Author

• Elizabeth Adele Patton, Curriculum Associates