Sentence examples for clustering students from inspiring English sources

Clustering students into groups based on their interaction.

Cerezo et al. (2016) have researched clustering students based on their patterns of interaction with LMS.

By clustering students according to their performance, we identified three distinct student types, common to both years: Achievers, Disheartened, and Underachievers.

Several studies have been done to process these logs to elicit the following: Students' learning and interaction Variables for predicting learning outcomes Clustering students into groups based on their interaction.

To investigate the impact of clustering students by instructor in the student analysis (i.e., including instructor random effects) and clustering by institution in the instructor analysis (i.e., including institution random effects), we performed sensitivity analyses fitting the logistic regression models without the respective random effects.

In this paper, we present the applicability of variable precision rough set model for clustering student suffering studies anxiety.

The groupings cluster students of similar skills, as determined by another practice the new leadership introduced: continual assessment.

The methodology clustered students based on video tool access.

In other words, we cluster students by instructor to control for potential additional unmeasured characteristics of the instructor that are related to student perception of OTL.

Including a random effect for instructor makes the logistic regression model a hierarchical model as it clusters students together that shared an instructor.

A variety of data have been collected and processed for clustering the students.