# When is the best time to learn? -- Evidence from an introductory statistics course

## TL;DR

This study investigates how the time of day students engage with an introductory statistics course affects their success, revealing that daytime learning correlates with better outcomes and providing insights into student behavior and study patterns.

## Contribution

The paper introduces statistical models analyzing the impact of learning time on success and characterizes student study behaviors based on time of day and effort.

## Key findings

- Daytime learning predicts higher success in final exams.
- Good students tend to study in the afternoon, while some unsuccessful students study at night.
- Students who took the exam spent more time on exercises than dropouts.

## Abstract

We analyze learning data of an e-assessment platform for an introductory mathematical statistics course, more specifically the time of the day when students learn. We propose statistical models to predict students' success and to describe their behavior with a special focus on the following aspects. First, we find that learning during daytime and not at nighttime is a relevant variable for predicting success in final exams. Second, we observe that good and very good students tend to learn in the afternoon, while some students who failed our course were more likely to study at night but not successfully so. Third, we discuss the average time spent on exercises. Regarding this, students who participated in an exam spent more time doing exercises than students who dropped the course before.