Introduction:

 

The education system in America is largely based on examinations which leads adolescents to sacrifice sleep in favor of studying. The lack of sleep led students to have more academic problems as they advanced in their education (Gillen-O’Neel, Huynh & Fuligni, 2013; Estes, 1985). Many studies have found that sleep does have an effect on academic performance. It was found that better sleep quality led to the achievement of an individual’s scholarly goals (Flueckiger, Lieb, Meyer, & Mata, 2014). In our study, we aim to investigate the relationship between study habits of City College students and their grades. Based on the studies we have examined, we have able to deduce that good study and sleep habits yield positive academic outcomes (Kerdijk, Cohen, Mulder, Muntinghe, & Tio, 2015). The study habits that we are examining are the Spacing Effect and “cramming.” Many students tend to pull all-nighters or study a significant amount of the course material the night before the exam, which is known as cramming, while others choose to study the same material over a spaced out period of time (the spacing effect) (Thacher, 2008). This study aims to discover whether or not there is a relationship between study habits that affect sleep levels and the resulting examination scores.

 

References

Estes, Thomas H., and Herbert C. Richards. “Habits of Study and Test Performance.” Journal of Reading Behavior, vol. 17, no. 1, 1985, pp. 1–13., doi:10.1080/10862968509547527.

Flueckiger, L., Lieb, R., Meyer, A. H., & Mata, J. (2014). How Health Behaviors Relate to Academic Performance via Affect: An Intensive Longitudinal Study. Plos ONE, 9(10), 1-10. doi:10.1371/journal.pone.0111080

Gillen-O’Neel, C., Huynh, V. W. and Fuligni, A. J. (2013), To Study or to Sleep? The Academic Costs of Extra Studying at the Expense of Sleep. Child Development, 84: 133–142. doi:10.1111/j.1467-8624.2012.01834.x\

Kerdijk, W., Cohen-Schotanus, J., Mulder, B. F., Muntinghe, F. H., & Tio, R. A. (2015). Cumulative versus end-of-course assessment: effects on self-study time and test performance. Medical Education, 49(7), 709-716

Thacher, P. V. (2008). University Students and the “All Nighter”: Correlates and Patterns of Students’ Engagement in a Single Night of Total Sleep Deprivation. Behavioral Sleep Medicine, 6(1), 16-31. doi:10.1080/15402000701796114

 

Research Question:

 

Do study habits that affect sleep levels influence test scores of City College students?

 

Methods:

 

To gather substantial data, we are conducting surveys of 60 students in various locations across the City College campus (NAC Building/Courtyard, Shepard Hall, Compton-Goethals Hall, Marshak Cafe). We plan on gathering data after midterms so our subjects will have exam scores fresh in their minds. Our survey consists of the following questions:  

  • What year are you in? (List years)
  • What is your major? (Short Answer)
  • What midterms are you taking this semester? (Short Answer)
  • How many classes are you taking? (Multiple Choice)
  • Rank what order you prioritize your classes for studying. (Subject)
  • How many hours did you study? (Intervals in hours)
  • Did you space out your studying or did you study the night before? (2 Options)
  • How much sleep did you get the night before the examination? (Intervals in hours)
  • How many hours of sleep do you get on an average night? (Intervals in hours)
  • What were your examination Scores ? (Letter Grades or did not take)

We have created a Google Form (https://goo.gl/forms/jMQW6MZFx4L8Rg0l1) that we plan on distributing the second week of November (November 6 – November 10).

We plan on examining the correlation (if any) within the following variable sets :

  • Year vs. Hours of studying (Bar Graph)
  • Year vs. Hours of Sleep (Bar Graph)
  • Hours of Sleep vs. Test scores (Linear Regression)
  • Cramming vs. Average Test Score, Spaced out studying vs. Average Test Score (Bar Graph, T-test)

To examine our data, we are going to create bar graphs for our ordinal data. For our ratio data, we are going to create a scatterplot and then perform a Linear Regression test to examine the correlation between Hours of Sleep and Test Scores. Finally, we are going to create a bar graph that analyzes the average test score received when students practiced the study method of cramming the night before and the average test score when the students practiced the study method of spacing. Using this data, we will perform a t-test to determine whether there is a significant difference between study methods and the average test score received.