David Roney

My name is David Roney and I am a sophomore from Denver, CO. I am a Psychology major and Communication Sciences and Disorders minor. Some of my favorite things to do on campus are play golf (I am on the school team) and buy snacks I don’t need from the C Store. I am especially interested in Educational Psychology because I want to go to grad school for Speech-Language Pathology, and in that profession I will work with a lot of kids in their critical periods of development. I believe that having a strong background in psychology, and especially in education will help me to be more understanding and competent when entering my career.




Article Critique Statement of Interest

  1. Sleep patterns of students and their performance in school
    1. WHO: Preferably high school/college students, as this is when school typically gets more difficult and requires more dedication
    2. WHAT: Sleep patterns, or times that school is in session, and how that interacts with sleep
    3. WHY: I know that school start times vary greatly between grade levels and school districts, and that there has been recent debate about high schools starting too early to foster effective learning. A school district in my state even stopped holding class on Mondays in an effort to create better learning during times when students are in school. So, I would like to look at sleep patterns specifically, and this may include the hours that school is in session.
  2. Academic success and motivation of student athletes vs non-athletes
    1. WHO: Preferably college athletes, for whom athletics plays a bigger role in school life (as opposed to high school athletes)
    2. WHAT: College athletes, whether they play at small or big schools (D1, D2, D3, NAIA, etc.) sacrifice time that could be spent in school or doing schoolwork to practice and play their sport. I want to look at how playing a sport in college affects time away from school as well as academic success and motivation.
    3. WHY: Some schools offer counseling or academic services to athletes that some schools may not, and I am curious as to how much athletics takes away from the academic experience, as well as goals of student athletes professionally (in sports or in their academic field) and their ability to achieve academic goals while playing college sports.

Research Statement

For my research proposal I will investigate the effect of sleep quantity on academic performance among high school students. Understanding the relationship between these two variables could provide insight into the discrepancy between the ideal and realistic sleep patterns of students as well as the proposition of later school start times and time-of-day changes in education.

Annotated Bibliography

Burrus, R. T., & Graham, J. E. (2013). Sleep Deprivation and Introductory Finance Student Performance. Journal of Financial Education, 39(3/4), 31–46.

This study looks at the relationships between demographics, sleep behavior, and academic performance among finance students (business majors) at a mid-sized university. The sample consisted of 398 corporate finance students over five semesters, and the study yielded 384 usable respondents. The school is 83% Caucasian, creating a possible race bias in the sample. The measure used to collect data was a voluntary survey asking about work hours, working at night, hours of sleep, and preferred hours of sleep; it was administered before the final exam. The study found that students who worked more hours or worked at night did worse in the class. Also, it was determined that as students missed hours of sleep, the impact of losing an additional hour became greater.

The results of this study relate to my proposed study as it shows that sleep deprivation affects students at the university level, and that its effects increase as more sleep is lost. Also, academic performance was found to decrease when students spent their nights doing something other than sleeping, often working on assignments. This connects to the proposition that students could benefit from later school start times.

Carrell, S. E., Maghakian, T., & West, J. E. (2011). A’s from Zzzz’s? The Causal Effect of School Start Time on the Academic Achievement of Adolescents. American Economic Journal: Economic Policy, 3(3), 62–81.

This study investigates the causal relationship between school start time and academic achievement at the United States Air Force Academy. The sample consisted of 6,165 first-year students from 2004-2008. The students were evaluated in their achievement in classes when their assigned first period started at 7:00am, 7:30am, or 7:50am. The negative effect (on academic achievement) of having the first period randomly assigned was significant at 7:00am, but insignificant when the time moved to 7:50. It was determined that the achievement difference between the 7:00am and 7:50am students was equivalent to increasing teacher quality by one standard deviation.

This study is relevant as the results show that later start times at the university level do in fact increase academic performance. The USAFA is a specialized, military academy, but the students still attend classes and sports practices as they would at another institution. However, their military commitments remain different than the ordinary college student. The study also brings up the connection of academic achievement to both sleep and teacher quality. If sleep can have as much of an effect on achievement as teacher quality, a factor immediately present in the classroom, its investigation proves worthwhile.

Danner, F. (2008). Adolescent Sleep, School Start Times, and Teen Motor Vehicle Crashes. Journal of Clinical Sleep Medicine, 4(6), 3.

This study looks to assess the connections between delayed high school start times, academic achievement, and motor vehicle crashes. The sample consisted of 9,966 students from sixth to twelfth grade in 1998 and 10,656 in 1999 (one county). The students, who obtained parental permission, filled out a questionnaire asking about their sleep habits on school and non-school nights, as well as their daytime functioning. The questionnaire was given before and after an hour delay in school start time. From before to after the delay, school night sleep increased, and weekend sleep decreased. Motor vehicle crashes among 17-18-year-olds in the county of study decreased 16.5% from before the delay, however in the entire state the rate increased 7.8%. This relationship did not prove to be causal.

This study is relevant to my proposal because it outlines the relationship between my two variables in my population of interest (high school students). The investigation of motor vehicle crashes adds an interesting opportunity for potential future study, however is still outside of my realm of research. The null hypothesis was rejected, so my purpose for investigation remains valid.

Edwards, F. (2012). Early to rise? The effect of daily start times on academic performance. Economics of Education Review, 31(6), 970–983. https://doi.org/10.1016/j.econedurev.2012.07.006

This study uses data from all middle school students in Wake County, NC from 1999-2006 to investigate the effect of school start times on academic performance. This county utilizes a staggered school start schedule due to busing concerns. The study finds that a one-hour delay in school start time produces a three percentile point increase in math and reading scores, decreased absences, less time spent watching TV, and more time spent doing homework.

This study is helpful for my research proposal because it brings to light several effects of later school start times for student. While the data in this study does not directly involve sleep, the literature mentioned in the introduction and discussion states that there is evidence that earlier start times decrease hours of sleep. The discussion of the data from there on assumes that later start times increase sleep, and that sleep is included in the reason why start times affect the variables. Due to the indirect connection to sleep, I may not be able to utilize this study to talk about my variables, but it can be used to contribute to my discussion of school start times.

Eide, E. R., & Showalter, M. H. (2012). Sleep and Student Achievement. Eastern Economic Journal, 38(4), 512–524.

This study looks at the relationship between student sleep and standardized test performance, using a sample from the CDS. The tests included Letter-Word, Passage Comprehension, and Applied Problems. The sleep variable was measured by a survey question that asked about hours of sleep per night of respondents aged above 10 years old. Results showed the optimal hours of sleep per night for different age groups – optimal hours decrease with age through adolescence. Also, there was a significant correlation between hours of sleep and standardized test scores.

This study is useful because it uses a significantly larger sample than the other studies, despite its impersonal nature of a database survey. The questions on the survey were direct, however one question about sleep did not distinguish between weekday and weeknights, decreasing the breadth of understanding provided. This study can be used in my proposal as it represents a large sample, studies my variables, and also provides the possibility that too much sleep may have a negative effect. The more perspectives that can be brought to light such as this one, the more possibilities for future research exist.

Eliasson, A., Eliasson, A., King, J., Gould, B., & Eliasson, A. (2002). Association of Sleep and Academic Performance. Sleep and Breathing, 06(1), 45–48. https://doi.org/10.1055/s-2002-23157

In this study, a sample of suburban Maryland middle and high school students was used to study the relationship between total sleep time and academic performance. A questionnaire was given to participants asking about their total sleep time, academic performance, and their feelings of “sleepiness.” The study has a 50% response rate among high schoolers, and there were 200 seventh grade participants. It was found that nightly sleep time increased an hour when students took naps, and 90% of students felt “groggy” waking up for school. However, the average time students thought they should be sleeping for was 8.43 hours, and 80% believed they did not get enough sleep. The study found no significant correlation between self-reported academic performance and sleep time. The top two predictors of academic performance (GPA) were home work time and gender, respectively.

Overall, this study was performed in a less formal way as students were given a questionnaire and all data was self-reported. However, this is not negative since the students were able to provide information in their own way, contributing to the richness of the data. Also, the fact that no significant correlation was found increases the worthiness of my research; it opens up room for discussion about the possible factors connected to sleep and academic performance and may guide my proposal in a new direction. This can be used to show that not every study yields the same results, increasing my reason for performing such a study related to these variables.

Fallone, G., Seifer, R., Acebo, C., & Carskadon, M. A. (2002). How Well do School-aged Children Comply with Imposed Sleep Schedules at Home? Sleep,25(7), 739–745. https://doi.org/10.1093/sleep/25.7.739

This study aimed to investigate children’s compliance with experimental imposed sleep schedules, using a sample of 78 children from local schools in Rhode Island and Massachusetts. The decreased and optimized sleep schedules were a week long, and children of different ages were given schedules with the goal of increasing daytime sleepiness (which is unethical but interesting for my research). Actigraphy was recorded for all of the conditions. Results showed that children completed about five of seven nights on decreased sleep schedules and six of seven nights on optimized sleep schedules. Also, compliance decreased as age increased.

This study contributes to my research proposal as it looks at one aspect of students’ sleep tendencies, including their ability to comply to an imposed sleep schedule, which at younger ages is imposed by parents. It is realized that older students comply less, which shows that the variables I aim to study are more worthwhile to study in students nearing the end of adolescence. In these students, sleep patterns supposedly have a more significant role in school life.

Gau, S.-F., & Soong, W.-T. (1995). Sleep Problems of Junior High School Students in Taipei. Sleep, 18(8), 667–673. https://doi.org/10.1093/sleep/18.8.667

Gau & Soong’s study looks at the connection between daily sleep time and characteristics of students such as grade level, gender, and academic performance. The sample consisted of a total of 965 students and parents from students at two junior high schools in Taipei. The mean sleep time per night was 441.68 minutes. Girls slept less than boys but did not show an increase in sleepiness and students taking the entrance examination slept more than those taking the final examination. Sleeping less made students feel sleepier in the day and made it harder to arise in the morning.

This study is useful for my research proposal because it shows the results of my variables studied in a non-American culture. This expands my introduction, and shows that the issue is not strictly American, but has been applied to students anywhere. Also, it does not reference the academic performance variable directly, but investigates sleep’s effect on the daily experience in general, which is also important to students’ lives.

Gezgin, D. M. (2018). Relationship among Smartphone Addiction, Age, Lack of Sleep, Fear of Missing Out and Social Networking Sites Use among High School Students. Cypriot Journal of Educational Sciences, 13(2), 166–177.

This study aimed to see the effects of smartphone addiction on “fear of missing out,” social media usage, age, sleep time, and duration of smartphone ownership. The study used a sample of 161 high school students in Turkey, and data was collected using research forms including scales for the variables. Findings showed positive correlations between smartphone usage and age of students, duration of smartphone ownership, and “fear of missing out.” A negative correlation was found between smartphone usage and sleep time.

The results of this study are useful for my proposal since it shows that smartphone usage is yet another factor that affects sleep quantity in students, which may also have an affect on academic performance. This is another opportunity for further research which I also may decide to incorporate in my study. I can explain how the chain of effects stretches longer than simply between sleep and academic performance, as smartphone usage is a factor that affects sleep first, as well as sleep schedule compliance in the Fallone et al. study.

Howell, A. J., Jahrig, J. C., & Powell, R. A. (2004). Sleep Quality, Sleep Propensity and Academic Performance. Perceptual and Motor Skills, 99(2), 525–535. https://doi.org/10.2466/pms.99.2.525-535

The intent of this study was to measure relationships between sleep propensity, sleep quality, and academic performance. Sleep propensity was measured on the Epworth Sleepiness Scale, sleep quality was measured on the Pittsburgh Sleep Quality Index (PSQI), and academic performance was measured using GPA and grades in an introductory psychology class. The sample consisted of 414 college introductory psychology students, with a 64.5% female gender bias. This study’s results showed no correlation between the variables among the total sample, but among those carrying a full course load, poor sleep quality correlated with poor academic performance.

Although this study resulted in an overall acceptance of the null hypothesis, it showed that sleep has more of an effect on students taking a full course load than on those who don’t. As students reach higher education, they take more difficult and specialized classes, thus it can be deducted that sleep becomes more and more important. Considering this, sleep is a worthy variable to study among students as its effect becomes more pronounced as students take on more academic responsibility.

Lepore, S. J., & Kliewer, W. (2013). Violence Exposure, Sleep Disturbance, and Poor Academic Performance in Middle School. Journal of Abnormal Child Psychology, 41(8), 1179–1189. https://doi.org/10.1007/s10802-013-9709-0

This article investigates whether sleep disturbance mediates the connection between academic performance and violence exposure in middle school students. 498 seventh grade students completed a computer-assisted survey interview about exposure to community violence and peer victimization, and another scale measuring sleep problems. It was concluded that community violence exposure correlated directly with lower GPA and indirectly with sleep problems, and peer victimization exposure was connected directly to lower GPA via sleep problems. The researchers say that sleep problems and low academic performance may suggest an exposure to violence.

This study contributes to my research proposal by adding another factor to the list of variables that may affect student sleep, and by association, academic performance. The factors affect differently-aged students differently, so sleep proves to be important for all students. Violence exposure can exist in several forms, so it is important to address its effects on students.

Pagel, J. F., & Kwiatkowski, C. F. (2010). Sleep Complaints Affecting School Performance at Different Educational Levels. Frontiers in Neurology, 1.https://doi.org/10.3389/fneur.2010.00125

This study looks at the effects of sleep disturbance on academic performance, which has been negatively correlated by past research. It uses a broad sample in terms of age, including 98 middle school students, 67 high school students, and 64 college students. Sleep disturbance was measured on a questionnaire, and academic performance was measured using self-reported GPA. In middle school, restless legs and periodic limb movement were associated with lower GPA. Daytime sleepiness negatively affected high school students, and sleep onset and maintenance insomnia affected college students most.

This study is especially useful because the sleep variable goes deeper than simple asking how many hours of sleep students get, but records intricacies such as body movement, sleep onset, and daytime sleepiness. The data is self-reported, which may decrease accuracy since the data has to do with sleep, so future studies could use sleep-tracking technology to measure tendencies. I can use this study to justify sleep research on differently aged students.

PhD, J. F. G. (2010). The Prevalence of Sleep Disorders in College Students: Impact on Academic Performance. Journal of American College Health, 59(2), 91–97. https://doi.org/10.1080/07448481.2010.483708

This study examined the prevalence of risk for sleep disorders among college students and how that affects GPA. It incorporated a sample of 1,845 students at a large southeastern public university. The students were given a sleep disorders questionnaire, and GPAs were obtained from the university’s registrar. Results showed that 27% of students were at risk for one or more sleep disorders, white and Latino students were more vulnerable than African American and Asian students, and those at risk were also more at risk for academic failure.

This study looks at sleep disorders specifically instead of the broader category of sleep quantity. Sleep disorders can be a cause of lack of sleep, which then affects academic performance. This study, along with the study about smartphone addiction, offers an antecedent to the lack of sleep that affects so many students. These items may be able to play a role in what my study investigates.

Randler, C., & Frech, D. (2009). Young People’s Time-of-Day Preferences Affect Their School Performance. Journal of Youth Studies, 12(6), 653–667.

This article studies whether morningness and eveningness affects school performance by grade level. 811 students from 10-17 years of age filled out the Pupil Morningness-Eveningness Questionnaire that asked about daily circumstances with respect to time of day. School performance was measured with self-reported grades, as a standardized test may not capture the essence of the classroom. Results found that students shifted towards eveningness at about 12 years, gender differences were not significant, and that students who preferred the morning did better in school.

This is useful because the study looks at students’ daily experiences being in school, and how they feel throughout their days. The school experience is not always objective; it can be measured by how students feel in terms of tiredness. By using this study, I will be able to show students’ self-reported accounts of tiredness during the school day, which has an effect on academic performance as does the sleep they get the night before.

Singleton, R. A., & Wolfson, A. R. (2009). Alcohol Consumption, Sleep, and Academic Performance Among College Students. Journal of Studies on Alcohol and Drugs,70(3), 355–363. https://doi.org/10.15288/jsad.2009.70.355

This research studies the associations between alcohol consumption, sleep, and academic performance in college students. A sample of 236 liberal arts college students were given personal interview surveys asking about weekday and weekend sleep time, alcohol consumption, academic class, and academic performance. Alcohol consumption was correlated with duration of sleep, timing of sleep, and weekday-weekend sleep duration and timing discrepancies. Gender, alcohol consumption, sleep duration, and daytime sleepiness were the strongest predictors of GPA.

This study shows that alcohol consumption is a factor that can affect both sleep and academic performance. Alcohol consumption was found to affect sleep, and sleep has been found both in this study and several others to correlate with academic performance. Using this study, alcohol consumption can be added to the variables that relate to academic performance in students, specifically college students in this case.

Literature Review Outline

Academic Performance


-Standardized tests.

Student Sleep Quantity

-Sleep routines.

-School start times.

-Personal factors.

High School Student-Athletes

-Time commitments to sport. (In-season vs. out-of-season)

-Time management. (In-season vs. out-of-season)

-Sleep patterns. (In-season vs. out-of-season)

Proposed Study

IS Symposium Reflection

I attended two Symposium posters that I took special interest in: Hunter Coia’s project on predicting NCAA basketball tournament seedings based on statistical factors, and Andrew DeLaat’s project on the effect of natural projects on digestive tissue in mosquitoes. (Time was limited due to golf commitments starting at 12:00pm).

Hunter Coia’s project explored a realm of sports that I had not before considered: the process gone through to create brackets. I had previously never thought about the factors that went into where each team was ranked. There are 18 statistical categories that help to determine this, and it made me think about how subjective the process is, and how in reality, it can’t be made much more objective. People choose the categories, the difference between two adjacent seeds is statistically the same, and at-large bids are determined by factors that are inherently subjective. Thinking about this then made me think about my own sport, and how professional golfers may receive sponsor exemptions into tournaments based solely on the status of their sponsorship, when there may be a better golfer who is left out. This can be applied to the field of psychology by looking at bias and attitudes towards different kinds of people.

Andrew DeLaat’s poster, in a biological science field, looked at the insecticidal properties of natural plant compounds and their effect on female Aedes aegyptimosquitoes, which has relevance on the topic of ways to prevent malaria in countries it affects. This presentation was very different than something I would do in psychology but provided clarity in the larger issue it aimed to contribute to. The intricacies of an IS can be overwhelming to those who are not in the field, but there are always a wide range of larger-world issues that they relate to. A study about children in special education environments can be applied to how special education is approached in different places, with similar situations. This presentation made me look forward to learning about the group of people my own future IS may be able to affect.

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