Predictive Model Dataset for Mathematics Anxiety using Sleep Hours and Working Memory Factors

Published: 1 September 2025| Version 1 | DOI: 10.17632/twt5jjbpct.1
Contributor:
NISHA MAHAUR

Description

This dataset, " Predictive Model Dataset for Mathematics Anxiety using Sleep Hours and Working Memory Factors," is designed to facilitate research into the relationship between cognitive factors, sleep patterns, and mathematics anxiety. The dataset is provided in a single .csv file. The key variables in the dataset are: • Sleeping Hours: A numerical variable representing the average number of hours of sleep per night. • VWM (Verbal Working Memory): A score representing a participant's verbal working memory capacity. • VSWM (Visuospatial Working Memory): A score representing a participant's visuospatial working memory capacity. • Mathematics Anxiety: The target variable, representing a score on a validated scale measuring the level of mathematics anxiety.

Files

Institutions

  • Dayalbagh Educational Institute Faculty of Science
  • Dayalbagh Educational Institute Faculty of Education

Categories

Cognitive Psychology, Education, Anxiety, Machine Learning, Sleep, Working Memory

Licence