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FOREIGN TRADE UNIVERSITYHO CHI MINH CITY CAMPUS---------***--------MIDTERM ESSAYECONOMETRICS – GROUP 5ANALYZING THE IMPACT OF SLEEP AND CAFFEINEON FTU2 STUDENT'S LEARNING ACHIEVEMENTStudent: Chu Hải Dương 1911115095 Văn Bội Hân 1911115133 Phu Minh Khang 1911115200 Lê Kim Khánh 1911115207 Vũ Uyển Nhi...

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FOREIGN TRADE UNIVERSITY HO CHI MINH CITY CAMPUS ---------***--------

MIDTERM ESSAY ECONOMETRICS – GROUP 5

ANALYZING THE IMPACT OF SLEEP AND CAFFEINE ON FTU2 STUDENT'S LEARNING ACHIEVEMENT Student:

Class:

Chu Hải Dương

1911115095

Văn Bội Hân

1911115133

Phu Minh Khang

1911115200

Lê Kim Khánh

1911115207

Vũ Uyển Nhi

1911115364

K58CLC3

Ho Chi Minh City, June 2021

CONTENT ABSTRACT ....................................................................................................................... 1 1. Introduction ............................................................................................................. 2 2. Literature review ..................................................................................................... 3 2.1

Domestic research ............................................................................................... 3

2.2

International research ......................................................................................... 6

3. Methodology and data............................................................................................. 8 3.1

Model specification ............................................................................................ 8

3.2

Data source ....................................................................................................... 10

4. Result ...................................................................................................................... 10 4.1

Statistical Significance ..................................................................................... 11

4.2

Diagnosing model problem testing ................................................................... 11

4.2.1

Multicollinearity testing ............................................................................. 12

4.2.2

Heteroscedasticity testing .......................................................................... 12

a.

Park testing ................................................................................................... 13

b. Glejser testing ................................................................................................ 13 c. 4.3

White testing ................................................................................................. 14 Economic Significance ..................................................................................... 15

CONCLUSION ................................................................................................................ 17 REFERENCE................................................................................................................... 18

ABSTRACT Background Sleep deprivation is prevalent among college students, even though it is a basic need. However, the elements that induce sleep deprivation and how they impair students' capacity to study are yet uncertain. The goal of this study is to find out how common drowsiness and sleep deprivation are among Foreign Trade University students, as well as what variables contribute to inadequate sleep and how sleep affects academic performance. Materials and methods This is cross-sectional research done at random among students in Foreign Trade University Ho Chi Minh. Each was asked to fill out a self-administered questionnaire regarding their lifestyle, sleeping patterns, and academic performance (GPA) throughout the previous three months of education. The PSQI (Pittsburgh Sleep Quality Index) was developed to assess the quality and consistency of sleep. Results From a total of 100 respondents, 74% of study participants may be suffering from sleep deprivation (obtained less than 7-8 hours recommendation of sleep). Students whose GPAs are higher, however, reported experiencing a sufficient sleep duration (more than 7 hours). Conclusion Sleep deprivation is common at the Foreign Trade University in Ho Chi Minh City, Vietnam, and has been linked to poor academic performance. In this group, interruptions in sleep length are also associated with an increased risk of sleep difficulties

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1. Introduction Sleep could be a reversible state of reduced response to external stimuli, amid complex and predictable physiological changes. These changes include coordination, spontaneous and internally generated brain activity, as well as fluctuations in hormone levels and relaxation of muscle tissue. (1) Sleep appears necessary for our nervous systems to function properly. Yet, many college students don't reach these recommendations and get plenty of sleep but 6 hours per night. Consequently, lack of sleep leaves us drowsy and unable to concentrate the following day. It also ends up in impaired memory and physical performance and reduced ability to hold out math calculations. Caffeine can effectively control our mental state. Although it is beneficial to restore lower wakefulness levels and offset cognitive task performance decline caused by sleep deprivation, caffeine will adversely affect future sleep. This requires careful consideration of the risks associated with sleep deprivation and caffeine intake, especially among students. On average, a sufficient 7-8 hours of sleep would be considered enough for many people and has been related to good academic performance (2, 3, 4, 5). Academic performance refers to the short- or long-term educational achievements of college students. These goals are expressed in terms of your Cumulative Grade Point Average (GPA) and your classroom learning outcomes. The Cumulative Grade Point Average is calculated by dividing the total average of credits earned by the total number of hours attempted. Existing research shows that high-dose caffeine has the ability to reverse the alertness and mood changes caused by lack of sleep and there is a correlation between sleep time and academic performance: those who sleep a lot (more than 8 hours) have a higher GPA than students with shorter sleep times (less than 5 hours) (6, 7). In this cross-sectional study, the current hypothesis is whether your academic performance is affected by lack of sleep and caffeine. Many different factors can interfere with a student's sleep. However, the factors that lead to insufficient sleep that we must consider are: the regularity of the sleep, the interruption of sleep at night, the average duration of sleep per day and the intake of caffeinated beverages. 2

Therefore, the purpose of current research is to investigate the impact of sleep deprivation and caffeine intake on academic performance among HCMC Foreign Trade University students. (1)

https://www.britannica.com/science/sleep

(2)

https://www.education.ninds.nih.gov/brochures/Brain-Basics-Sleep-6-10-

08-pdf-508.pdf (page 4) https://www.researchgate.net/profile/Ljubomir_Jacic2/post/How_much_sle

(3)

ep_we_we_really_need/attachment/59d61dd879197b807797aba6/AS%3A273674467250 193%401442260485704/download/Ferrara+%26+De+Gennaro%2C+2001How+much+do+we+sleep.PDF (4)

https://www.hindawi.com/journals/sd/2013/910104/

(5)

https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.692.3996&rep=

rep1&type=pdf (6)

https://link.springer.com/article/10.1007/BF02244933

(7)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3959895/

2. Literature review 2.1 Domestic research A thorough analysis of past published research is essential prior to conducting the regression model and its variables. Our group gains unbiased insight into the repertoire of available literature thanks to a thorough analyzing process. In terms of domestic research, there are a few publications that go into detail into the various elements that influence student’s academic performance. Our group has found the following research publications on the topic:

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Vo Thi Tam (2010) investigated the overall level of performance of nearly 4000 students at the University of Economics in Ho Chi Minh City. Learning motivation, learning persistence, competition, impression of the institution, and learning methods, according to her, account for almost half of the changes in academic achievements. Three of them have a positive relationship with educational outcomes. Learning approaches (β=.511), learning perseverance (β=.119), and university impression (β=.116) are listed in descending order. The other two factors, learning motivation and competitiveness, have no discernible impact on learning outcomes. https://drive.google.com/file/d/1BQhEhZWTa8lI3l8srduU19Ct0DvH3Tij/view (page 80-83)

Dung, Oanh and Hai (2017) using multiple regression models identified four key characteristics that influence learning outcomes of Business Administration majors at Vietnam National University of Forestry. Similarly, the study reveals that learning methods are the most important factors, with those who devote extra time to self-study using computers, the Internet, and other resources being more likely to succeed academically. http://vnuf.edu.vn/documents/4400543/5703735/17.Nguyen.Thuy.Dung.pdf (page 140)

Nguyen Thi Nga (2013) correlates academic achievements to top-of-the-class performance in high school, learning interest, self-study length, learning methods, and teaching methods, utilizing qualitative and quantitative methodologies. Nearly 40% of the ultimate result is determined by these factors. Surprisingly, while self-study hours are less likely to be a deciding factor, others demonstrate a clear positive link with students' academic performance. https://drive.google.com/file/d/1aV6PUW4BKPyILe01r5N6FCLm5Gwy3SS4/view (page 89-92) 4

Van Viet and Thu Phuong (2017) carried out 7 factors that affect the learning outcomes of students at the University of Information Technology in Ho Chi Minh City including: study interest, social pressure, infrastructure, intellectual capacity, peer pressure, scholarship and family motivation. Specifically, the strongest impact on students' learning results is the study interest (β = 0.216); the second factor is infrastructure (β = 0.198); the third factor is social pressure (β=0.177); the fourth factor is peer pressure (β = 0.174); the fifth is Intellectual capacity (β = 0.162); the sixth is the scholarship (β = 0.142) and the last is parent motivation (β = 0.131). https://drive.google.com/file/d/1KJkTlu6ZVEI1oVjd8yl6DSFzJCSJpgmS/view (page 29 – 33)

Cong Toan, Minh Tri, Van Hau, Cam Hong and Van Quan (2015) analyzed 10 main characteristics affecting the learning outcomes of university students majoring in Rural Development in Can Tho University. Surprisingly, factors of gender, time of self-study, number of absences from school and the source of materials provided by lecturers have an influence on the economic performance of students majoring in rural development with a significance level of 10%. Other factors such as part-time work, extra-curricular activities, group study, learning about the content and objectives of the course or the amount of allowance from the student's family have an unknown influence on the student's performance. https://drive.google.com/file/d/1oztxVehZIknYSMhEBeD7lknszRTE9w2T/view (page 76 – 80)

Hoang Hung and Thanh Tam (2020) researched the overall level of performance among more than surveys of 500 students of different majors and courses of Hanoi University of Industry. According to them, factors including Learning motivation and

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Motivation for learning. However, the result shows that there is no difference in academic performance in terms of gender and permanent residence. https://drive.google.com/file/d/1WWB9rEgM3yrKblVXw2JSLjEKZ6FgVfr_/view (page 127 – 130)

2.2 International research Many college students are sleep deprived these days because they go to bed late and wake up for school or work before getting enough sleep. Sleepiness and irregular sleeping patterns have a variety of unexpected repercussions, one of which is a reduction in learning ability, memory, performance, and GPA. The exact details of the association between sleep and GPA are still being worked out. However, many international researchers have found a link between sleep deprivation and GPA.

According to A. Souza and S. Traslavia's (2013) study, 994 undergraduate students from four universities in Chile's Magallanes Region investigated the links between different types of stimulant beverages and poor sleep quality. Short sleep may also contribute to the frequent use of drugs and alcohol as sleep aids and stimulants to boost daytime alertness, according to researchers. Stimulants (coffee, caffeine shots, and energy drinks) have become more popular in recent years. Participants who reported drinking energy drinks (including Red Bull, Dark Dog, Battery, Red Devil, Shark, and Turbo Energy) had the highest prevalence of poor sleep quality. Participants who drank coffee, yerba mate, or cola had lower prevalence estimates. Although this link did not achieve statistical significance, those who reported drinking three or more stimulant beverages per week had a higher prevalence of poor sleep quality (data not shown). Around 18.5 percent of participants said they drank energy drinks as a result of sleep loss, while another 27.3 percent said they drank energy drinks to meet a general need for energy and another 29.5

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percent said they used energy drinks to study. Approximately 11.3 percent of those polled said they mixed energy drinks with alcohol at parties. https://www.hindawi.com/journals/sd/2013/910104/ (page 3 – 8)

Insaf Altun of Kocaeli University's High School of Health's Department of Fundamentals in Nursing (2012) conducted a study on the elements that contribute to university students' poor sleep experiences. A descriptive survey of 256 university students in Turkey was undertaken at random. Following their research, they came to the conclusion that the most common self-reported cause of bad sleep experiences amongst university students were exposure psychological problems (67.2%), stress (64.8%), exposure to tobacco smoke in the sleeping room (63,7%), pain (62,9%), having family problems (62,5%), being patient (55,1%), air quality of the room (55,1%), strenuous physical activity (53,9%), fatigue (53,5%), sadness (53,1%), noise that caused by other people in the room (52.0%), room scents (sweat, perfume, humidity, naphthalene, etc.) (53.1%), depression (51, 6 %), anxiety, and tension (51, 1%). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3634295/#

Erwiza*, Sri Kartiko, Gimin (2019) explored the factors that influence concentration and critical thinking on student learning achievement that have both direct and indirect impact on economic subjects in Madrasah Aliyah Negeri 1 Pekanbaru (MAN 1 Pekanbaru). They focused on 95 students and considering the results,

the non-physical school

environment had an effect on learning achievement directly by 24.2% and indirectly had an effect of 12%. Learning interest influences students's performance directly by 27.1% and indirectly by 8.8%. Learning concentration directly affects learning achievement by 19.5%. Critical thinking directly influences learning outcomes by 27.3%. https://drive.google.com/file/d/1OLXmoTh9FF9j9xvpILqvFelV0S9AeL4i/view (page 208 – 214) 7

Alya Atieah Al Ghamdi (2013) did research about the relationship between the sleep deprivation and academic performance of students in college of nursing at King Saud University. A descriptive survey was conducted randomly on 114 university students. After investigating and researching, they come to conclude that the association between insufficient sleep duration lifestyle and lower university grades are understandable because students who score B sleep less than usual, they spend more time than intermediate students who score A level on research or final exams. https://drive.google.com/file/d/1s6_irgw1v96TZak0KhFEBntwFqtvJbtX/view (page 156 – 165)

3. Methodology and data 3.1 Model specification We narrowed down the most relevant elements affecting students' academic performance, including sleep regularity, sleep disruptions, sleep length, and caffeinated beverage intake, based on prior studies, most notably a 2001 study by Medeiros, Mendes, Lima, and Araujo. The model we employ to estimate sleep-related factors of Foreign Trade University students' GPA in HCMC is as follows: ln(GPA) = β0 + β1SLPOS + β2SLPINTRPT + β3SLPLENGTH + β4CAFFEINE + u* Description of variables: GPA: GPA of students in Foreign Trade University in HCMC SLPOS: Sleep regularity SLPINTRPT: Existence of interruptions during sleep over SLPLENGTH: Average length of sleep CAFFEINE: Consumption of caffeinated beverage 2 hours before sleep 8

u*: the error term denotes omitted variables that collectively affect GPA From the effects of the independent variables in the model on GPA, we expect the coefficient of sleep regularity ( β1 ) to be positive. Since this binary variable helps determine sleeping habits, the expectation is based on the result of “The Relationships between SleepWake Cycle and Academic Performance in Medical Students” study, stating that considerable variations in bedtime leads to decrease in academic outcomes. β3 , the coefficient of average sleep length, also bears the same positive sign. Sleep deprivation has a major impact on students' capacity to perform effectively in class, according to a 2001 study by William E Kelly, Kathryn E Kelly, and Robert C Clanton. As a result, it's reasonable to predict an increase in GPA percentage in proportion to the number of daily hours students sleep, and vice versa. In contrast, the binary variable SLPINTRPT should have negative coefficient ( β2). According to the National Sleep Foundation, those who have disturbed sleep are at risk of having their attention span, reaction speed, and memory diminished, all of which are crucial to a learner's success. Caffeine suppresses sleep-inducing hormones, causing insomnia and disrupted sleep, according to Henry Ford Health System experts in "Caffeine Effects on Sleep Taken 0, 3, or 6 Hours Before Going to Bed." As a result, it is reasonable to assume that the sign of this indirect cause of learning ability impairment is negative. Table of Parameters’ expectation: Independent Variable

Measurement

Parameters’ expectation

SLPOS

Sleep regularity

+

SLPINTRPT

Existence of sleep interruptions

-

SLPLENGTH

Sleep length

+

Caffeine

Caffeine in drinks before sleep

-

9

3.2 Data source 100 participants were 18 and 19-year-old students from Foreign Trade University of Ho Chi Minh City (sophomore and junior, respectively). They were asked to fill out a questionnaire anonymously, with no personal information recorded. Questions about students' sleeping quality and their GPA in the last three months of schooling were developed based on empirical research and the Pittsburgh Sleep Quality Index (PSQI), a reputable instrument for quantifying sleep quality in the previous months. Only self-reported questions are included in the scoring, which focuses on three specific areas: sleep length, sleep disruptions, sleep start regularity, and caffeine intake. Data was analyzed using Stata 15. Various testing methods aiming at multicollinearity and heteroscedasticity detection were done and their descriptions will be elaborated in the result section.

4. Result Having analyzed our model using Stata, we came into these following results:

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4.1 Statistical ...