Inferential topics used:
●
●
●
●
Estimation of a single proportion
Test concerning single mean
Test concerning the difference between two means
Regression and correlation
Contributions
Jacques Te
-
Introduction, Methods, Data analysis, Conclusion, Excel
Tatiana Pua
- Methods, Results, Conclusions
Gem Hervera
- Introduction, method
Aaron Po
- Introduction, method
An Analysis of Academic Performance in Relation to Studying
Before or After Midnight
Gem Lyzza Marithe D. Hervera1, Aaron Vincent G. Po 2, Tatiana Tricia P. Pua3,
Jacques Benzly L. Te4*
gem_hervera@dlsu.edu.ph, aaron_po@dlsu.edu.ph, tatiana_pua@dlsu.edu.ph,
jacques_te@dlsu.edu.ph*
ABSTRACT
Several studies have been conducted on the academic performance of students in
relation to the quantity of their study sessions, and on what the most effective study
time is in the day; however in depth analyses of students’ academic performance in
relation to studying before or after midnight has yet to be accomplished. This study
analyzes the relationship between academic performance and the time of day studied
specifically before and after midnight, among senior high school students of De La Salle
University (DLSU) Manila Integrated School. This research mainly analyzes
quantitative variables using statistical inference; in particular, the research used
estimation of proportion, test concerning single mean, test concerning difference
between two means, and linear regression and correlation. The results of the study
inferred that generally, approximately 12.17% to 35.83% of students study after
midnight, as well as the average time spent studying by students who study after
midnight is less than the sample. The study also concluded that there is no significant
difference between studying before midnight and after midnight with respect to an
individual's GPA. Lastly, the research also found that there is an indirect relationship
between hours of study and GPA among students who study before midnight, but has a
more indirect relationship among students who study after midnight. Overall, the study
concludes that time spent studying and GPA does not have a significant relationship.
Keywords: Academic Performance, Before Midnight, After Midnight, Time spent Studying
INTRODUCTION
Background
Students nowadays, the so-called
millennials,
have
rather
different
practices in studying. Study habits
significantly
affect
the
academic
performance of students. This includes, to
name a few, the location or space at which
the student feels most comfortable, the
amount of time spent studying, and the
time of the day in which they feel the
most alert and focused. Moreover, each of
these are valuable factors to consider in
terms of their academic performance. The
best time to be more receptive and to have
a more effective brain function to be
better able to focus on what is being
learned and absorb information more
effectively will be determined in the study.
According to oxfordlearning.com
(2017), students’ brains tend to be the
sharpest in the morning, after a
refreshing night’s sleep and a nutritious
breakfast; but considering the fact that an
online
setup
is
currently
being
implemented, students tend to be more
emotionally and mentally drained, and
therefore opt to study during the night
time. In addition, in a blog written by the
Singapore's Productivity and Standards
Board (2020), some researchers have
interestingly suggested that studying at
the time an individual is the most tired
during can actually help our brains retain
a higher level of concentration. However,
one should not forget that it is still the
student’s personal choice on what for
them is the most convenient time to study.
As early as a student begins their
schooling, they already begin to develop a
certain study habit or learning style
which may be different from the rest.
Something that they find more effective
than what others may have put into
practice. This may be accounted to the
mindset that a person has established to
better cope up with the demands of the
current educational challenges. Thereby,
establishing a study routine that is for
them the most effective and efficient.
Statement of the problem
Before
midnight
and
after
midnight studying is vital to one’s
progress in their studying for each study
time has its own advantages and
disadvantages. This problem affects all
students, though mostly in high school to
college students. There have been various
researches and studies done regarding
which time would be the best time to
study during. The success of the study
would prove beneficial to not only DLSU
students, but also other students, for it
can help them find the best time to study
and would therefore help them improve
academically. The target of this study is to
investigate which certain time stamp is
the best time to spend time studying to
increase one’s academic performance.
Research Questions
1. What proportion of DLSU SHS
Grade 11 students study after
midnight?
2. Is the average time spent studying
by the DLSU SHS grade 11
students who study after midnight
less than sample mean?
3. Is there a significant difference in
the average term GPA of DLSU
SHS grade 11 students who study
before midnight to after midnight ?
4. For DLSU SHS grade 11 students,
is there a significant linear
relationship between the time
spent studying before and after
midnight, to their corresponding
GPA of term 1 and term 2?
Objective of the study
The objective of this study is to
evaluate the difference of studying before
midnight to after midnight in its effect on
the academic performance of individuals,
specifically students.
More specifically in evaluating this, the
researchers aim to first, determine the
proportion of students that study after
midnight as well as before midnight,
second is to identify weather the average
time spent studying of students studying
after midnight is greater than the average
time of the whole sample, third is
compare the significance in the difference
between the academic performance of
student who study before midnight to
after midnight. Lastly, the researchers
aim to assess the linear relationship of
academic performance to the hours of
study on both students who study before
midnight and after midnight.
Hypothesis
In
general,
the
researchers
hypothesize that studying after midnight
is more effective and efficient than
studying before midnight in terms of its
benefits on academic performance. In
contrast, the researchers believe that the
proportion of students studying before
midnight is greater than students
studying after midnight.
Moreover, the researchers suspect that
the average time spent studying after
midnight is less than the average of the
time spent studying by the whole sample.
Furthermore, the researchers speculate
that there is no significant difference
between the academic performance of
students who study before midnight to
students who study after midnight.
Additionally, the researchers expect a
moderate linear relationship between the
time spent studying and academic
performance of a student for both
proportion who study before midnight and
after midnight.
MATERIALS AND METHODS
Scope and Limitations
This study focuses on the impact of
studying before or after midnight to the
academic performance of an individual,
this includes the daily time an individual
spends studying in hours, and the
academic performance of an individual
measured by their general point average
in term 1 and term 2. In this study, before
midnight is defined as 6:00 am to 11:59
pm, and after midnight is defined as 12:00
am to 5:59 am. This study also focuses
mostly on the quantitative aspect of the
topic. However, some limitations that may
affect this study is that the sample is
limited to the students of De La Salle
University Integrated School, which may
not
represent
the
whole
general
population. Another limitation is that this
study only focuses on the relationship of
the time spent studying and grade point
average. Other factors not stated in the
scope of this study will not be included.
Data Collection
The researchers collected data
through the usage of a survey with Google
Forms as the platform. 100 participants
were chosen by implementing a simple
random sampling within the population
sample of De La Salle University
Integrated School’s Grade 11 students,
but only 50 respondents are necessary to
complete the data gathering. The
researchers picked respondents from
Grade 11 students from De La Salle
University Integrated School because the
chosen participants are relevant to the
paper that will analyze the academic
performance of students in relation to
studying before or after midnight. Student
respondents were tasked to first answer
questions in relation to basic personal
information such as their name, gender,
age, and section in De La Salle University
Integrated
School.
No
specific
requirements are necessary for the
respondents to be accepted to answer the
survey as long as they are students of De
La Salle University Integrated School.
Afterwards, comprehensive questions
were asked about the time that they spent
studying such as factors that affect their
study time and the quantity of their daily
study time in hours during either before
or after midnight, and about their grade
point average during term 1 and term 2.
The data gathered from the Google Forms
will be analyzed, summarized, and
recorded in a Microsoft Excel spreadsheet
to be further completed through statistical
analysis.
Data Analysis
This study mainly uses statistical
analysis to analyze and interpret the
collected quantitative data, specifically
inferential statistics. The study utilizes
four statistical methods, with the first
being the estimation of a single
proportion. Additionally, this research will
be using a confidence level of 𝞪 = 95% for
all statistical inference. This is used for
the proportion of respondents studying
before midnight or after midnight. This is
done to determine the margin of error of
the proportion for students studying after
midnight, and to construct a confidence
interval to infer a general estimation of
proportion for the whole population. This
is implemented by estimating a standard
error (e) using the equation below; with z
being ( z 𝞪/2 = 1.96) and computing a point
estimate (p) being the number of students
who study after midnight divided by the
sample (50). The (q) is the proportion of
students who study before midnight.
e = z 𝞪/2
𝑝𝑞
𝑛
Equation for standard error
(p-e, p+e)
Confidence interval
The second is a test concerning a single
mean which is used to test the hypothesis
which states that the average time spent
studying after midnight is less than the
average time spent studying by the whole
sample. This is done by forming a decision
rule based on the initial hypothesis and
an alternative hypothesis. The rejection of
the initial hypothesis will be dependent
on the computed z using the equation
below, where 𝑥 is the mean hours of
students studying after midnight, and u is
the sample mean. Lastly, after the
decision, a conclusion is made.
Z=
𝑥−𝑢
𝑠/ 𝑛
Equation for (Z)
The third is a test concerning two means.
This is used to test the hypothesis which
states that the difference between the
academic performance of students who
study before midnight to students who
study after midnight is not significant.
Before starting the hypothesis test, a
F-test was first conducted to determine
whether the mean is assumed equal
variance or not. The hypothesis test is
done by forming a decision rule based on
the initial hypothesis and an alternative
hypothesis. The rejection of the initial
hypothesis will be made depending on the
computed z using the statistical tool in
Microsoft Excel. Finally, after the
decision, a conclusion is made.
The final statistical methods are linear
regression and correlation analysis. These
are used to analyze the linear relationship
between time spent studying as the
independent variable (X) and general
point average as the dependent variable
(Y) . This is analyzed by observing the
correlation coefficient (r), the r-square
(r2), p-value, and t-stat. The correlation
coefficient tells us where the relationship
is direct or indirect as well as if the
relationship is weak, moderate or strong.
It is weak if it's near 0, moderate when
near 0.50, and strong when near 1,
disregarding whether it's positive or
negative. The r2 states what percent of the
values of Y is accounted for by X, and
lastly the p-value and t-stat determines
whether the prediction equation is viable
or not, this is done by comparing the
values to t𝞪/2. Moreover, evaluating the
effectiveness and efficiency of studying for
both before midnight and after midnight.
This will be done by using the linear
regression equation to predict the possible
grade point average obtained from x hours
of studying. This equation will also reveal
which particular study time will be more
effective based on the data; by inputting 1
hour of study in each equation obtained
from after midnight regression and before
midnight regression, and which equation
will give the higher grade point average.
The researchers will be using Microsoft
Excel as the statistical software to
compute the collected quantitative data
for all methods stated.
RESULTS AND DISCUSSION
Data Gathered
After analyzing the data conducted
from the survey; from the 50 respondents,
29 respondents or 58% of the respondents
were female, 19 respondents or 38% of the
respondents are male, and 2 respondents
or 4% of the respondents prefer not to
specify their genders.
Figure 1. Gender
In terms of the ages of the
respondents, 11 respondents or 22% of the
respondents are 16 years old. 30
respondents or 60% of the respondents are
17 years old, and 9 respondents or 18% of
the respondents are 18 years old.
Figure 2. Age of respondents
When respondents were asked
about the time they spent studying daily,
whether they studied more before or after
midnight, 38 or 76% of the respondents
studied more before midnight, while 12 or
24% of the respondents studied more after
midnight.
Figure 3. Time of day spent
studying
The data of the entire sample of 50
respondents was collected along with
their maximum and minimum grade point
averages, mean of the sample, sample
standard deviation and variance. The
maximum value grade point average from
the whole sample of 50 respondents is 98,
while the minimum value grade point
average is 89.15. The mean of the entire
sample is 94.45, the sample standard
deviation is 1.99, and the sample variance
of the whole sample is 3.95.
Whole Sample (GPA)
Mean (x̅)
94.45
Sample
Standard
Deviation
(s)
1.99
Sample
Variance
(s2)
3.95
Maximum
98
Minimum
89.15
Table 1. Summary of Whole sample GPA
With the data collected, in terms of
the mean of the two grade point averages
for term 1 and term 2 of the population
who studies before midnight, the
maximum grade point average from the
38 respondents is 98, whilst the minimum
grade point average is 89.15. The mean
grade point average is approximately
94.33 for respondents who study before
midnight, the standard deviation from
that sample is approximately 2.01, and
the sample variance is 4.05.
Before Midnight (GPA)
Mean (x̅)
94.33
Sample
Standard
Deviation
(s)
2.01
Sample
Variance
(s2)
4.05
Maximum
98
Minimum
89.15
Table 2. Summary of Before Midnight
GPA
With respect to the mean of the
two grade point averages from term 1 and
term 2 of the 12 respondents who study
after midnight, the maximum grade point
average is approximately 97.245, while
the minimum grade point average is
approximately 91.025. The computed
mean grade point average is estimated to
be 94.82, the standard deviation from the
sample of respondents who study after
midnight is approximately 1.94, and the
sample variance is 3.75.
After Midnight (GPA)
Mean (x̅)
94.82
Sample
Standard
Deviation
(s)
1.94
Sample
Variance
(s2)
3.75
Maximum
97.245
Minimum
91.025
Table 3. Summary of After Midnight GPA
The other variable that is being
analyzed is the hours of study of each
respondent with the datas of the
maximum value, minimum value, mean,
sample standard deviation, and variance
for both studying before midnight and
after midnight. For the 50 respondents,
the maximum amount of hours studied is
15 hours, and the minimum amount of
hours is 0.5 hours. The mean of the daily
time spent studying in hours of the whole
sample is approximately 3.815 hours, the
standard deviation of the whole sample is
2.91, and the sample variance is 3.75.
Whole Sample (Daily Time Spend
Studying in Hours)
Mean (x̅)
3.815
Sample
Standard
Deviation
(s)
2.91
Sample
Variance
(s2)
8.47
Maximum
15
Minimum
0.5
Table 4. Summary of the Whole sample
time spent studying
For the 38 respondents who study
before midnight, the maximum amount of
hours studied is 15 hours, and the
minimum amount of hours is 0.5 hours.
The mean of the daily time spent studying
in hours of the 38 respondents who study
before midnight is approximately 4.10
hours, the standard deviation of the
sample is calculated to be 3.24, and the
sample variance is 8.47.
Before Midnight (Daily Time Spend
Studying in Hours)
Mean (x̅)
4.10
Sample
Standard
Deviation
(s)
3.24
Sample
Variance
(s2)
10.48
Maximum
15
Minimum
0.5
Table 5. Summary of Before Midnight
time spent studying
For the 12 respondents who study
after midnight, the maximum amount of
hours studied is 4 hours, while the
minimum amount of hours studied is 1
hour. The mean of the time spent studying
in hours of the 12 respondents who study
after midnight is approximately 2.92
hours, the standard deviation of the
sample of these respondents is 1.14, and
the sample variance is 10.48.
After Midnight (Daily Time Spend
Studying in Hours)
Mean (x̅)
2.92
Sample
Standard
Deviation
(s)
1.14
Sample
Variance
(s2)
1.31
Maximum
4
Minimum
1
Table 6. Summary of After Midnight time
spent studying
All 50 respondents were also asked
whether the time of day that they study
more often, whether before or after
midnight, directly affects the quality of
their study time. 40 respondents or 80% of
the respondents answered that the time of
the day that they study directly affects
the quality of their study time, while 10
respondents or 20% of the total
respondents said that the time they study
does not affect the quality of their study
time. For the 40 respondents who agreed
that the time that an individual studies
affects the quality of their study time, the
reasons were that if an individual
manages to study at an earlier time in the
day, they would be more likely to have a
lengthier and more productive study
session. Other reasons are that their
minds get more tired and are not able to
concentrate at optimum levels on certain
times of the day, their focus, energy, and
motivation levels are higher on certain
times of the day, their environment and
its ambience can heavily affect their focus,
the amount of sleep that they get is
crucial to the quality of their study time,
and that not having their preferred study
session as the time for studying can also
affect the quality of their study time. As
for the 10 respondents who disagreed that
the time that an individual studies affects
the quality of their study time, their
reasons were that the content that enters
the brain is the same no matter the time
of day that they study during, and that
the quality of their study mainly relied on
motivation.
With many people having their
own personal preferences, decisional
factors, and reasons as to why they study
in a particular time of day such as before
midnight or after midnight, the 50
respondents were also asked about the
factors that supported their decision in
whether to study before or after midnight.
In terms of the 38 respondents who
consistently study before midnight, these
factors consisted of alert levels, energy
levels, and personal preferences. For 27
respondents or 71.10% of the respondents
who study before midnight, the factor that
resulted into their studying before
midnight is personal preferences. For 26
respondents or 68.40% of the respondents
who study before midnight, the factor that
resulted into their studying before
midnight is their energy levels, and for 21
respondents or 55.30% of the respondents
who study before midnight, the factor that
resulted into their studying before
midnight is their alert levels. These
factors also overlap with each other as
many respondents who study before
midnight include all these as factors,
while some respondents only include one
or two as factors.
Estimation of Proportion
Figure
Midnight
4.
Factors
for
Before
In terms of the 12 respondents who
normally study more after midnight, the
factors consist of no external disturbances
such as household members and noise,
mental clarity, personal preference, lack of
time during the day, and no motivation
during the day. All 12 or 100% of the
respondents who study after midnight
had the main factor as having no external
disturbances during after midnight. 10 or
83.30% of the respondents also had
mental clarity and personal preference as
a factor for studying after midnight.
While 7 or 53.30% of the respondents said
that the lack of time during the day was a
factor as to why they studied after
midnight, and 1 respondent or 8.33% of
the respondents said that it was due to
the lack of motivation during the day.
Using the data collected on the
proportion of students who study before
midnight and after midnight, an
estimation can be inferred for the general
population, specifically a 95% confidence
estimation for students studying after
midnight is made. The point estimate for
this inference is the percentage of
students who study after midnight which
is (p̂ = 0.24), while the q̂ value is the
proportion of students not studying after
midnight (q̂ = 0.76). Given the collected
data, a margin of error (e) is calculated to
be 0.1183. Using the point estimate and
margin of error, a confidence interval
(C.I.) is constructed by getting the upper
and lower margin (0.1217, 0.3583). Thus
it can be concluded that based on the data
collected, with 95% confidence it can be
implied for the general population that
the proportion of students who study after
midnight is between 12.17% to 35.83%.
p̂
0.24
p̂
0.76
z0.05/2
1.96
n
50
e
0.1183
C.I.
(0.1217, 0.3583)
Table 6. Summary of variables for
proportion
Figure 5. Factors for After Midnight
A possible explanation for this is based on
the survey conducted among the
respondents who study before midnight.
When asked if the time they study affects
the overall quality of studying, about 10 of
the respondents who answered yes had
reasonings related to sleepiness concerns,
concentration
deprivation.
issues,
and
energy
Test Concerning Single Mean
In the previous section, it was
hypothesized that the mean hours of the
time spent by students studying after
midnight is less than the sample mean. To
test whether the hypothesis is statistically
correct, a seven step hypothesis is
conducted. The first step is stating the
null hypothesis, which states that the
mean hours of students studying after
midnight is greater than or equal to
3.815. The second step is stating the
alternative hypothesis, which states that
the mean hours of students studying after
midnight is less than 3.815 (the sample
mean). The third step is finding the
significance level, which is 0.05 or 5%.
Next, based on the hypothesis, a
decision rule is made; and if the
computed z value is less than -1.6449,
then the null hypothesis will be
rejected. The computed z value based
on the data collected is z = -2.182446
(refer to equation in methodology) , so
the decision to reject the null
hypothesis is made. In conclusion, the
hypothesis is correct, and it can be
said that there is enough evidence to
conclude that the average time of
students studying after midnight is
less than the sample mean.
STEP
Hypothesis Test
1
H0: u ≥ 3.815
2
Ha: u < 3.815
3
α = 0.05
4
Reject H0 if z < -1.6449
5
z = -2.18244614
6
Reject H0
7
There is enough evidence to
conclude that the average
time of students studying
after midnight is less than
the sample mean.
Table 7. Hypothesis test procedure for
test concerning single mean
Test Concerning the Difference
Between Two Means
The researchers speculated that
there is no significant difference between
the academic performance of students
who study before midnight to students
who study after midnight. To test if the
hypothesis is statistically correct , a seven
step hypothesis test is done. Before the
first step the F-test conducted shows that
the variances are assumed equal. The
first step is stating the null hypothesis,
which states that there is no significant
difference between the mean GPA of
students who study before midnight in
comparison to those who study after
midnight. On the other hand, the
alternative hypothesis states that there is
a significant difference between the mean
GPA of students who study before
midnight to students who study after
midnight. The third step is to determine
the significance level, which is 0.05 or 5%.
The next step is forming a rejection rule.
Based on the alternative hypothesis, the
rejection rule is to reject if the computed z
value is either less than -1.96, or greater
than 1.96. Based on the data collected, the
z value computed is 0.4539. Thus, a
decision to not reject the null hypothesis
is made. In conclusion, the test implies
that there is no significant difference
between the mean GPA of students who
study before midnight to after midnight.
STEP
Hypothesis Test
1
H0: u1 = u2
2
Ha: u1 ≠ u2
3
α = 0.05
4
Reject H0 if z < -1.96 or z >
1.96
5
z = 0.453898898
6
Do not Reject H0
7
There is no significant
difference between the mean
GPA of students who study
before midnight to after
midnight.
Table 8. Hypothesis test procedure for
test concerning two means
Linear Regression and
Correlation Analysis
In
this section, the linear
regression and correlation analysis is
done from the data retrieved from
students who study before midnight and
after midnight. This is done to have a
clear comparison between the two.
Based on the analysis made on the
data related to students studying before
midnight, the following statistical output
is calculated on Table 9., as well as the
graph shown on Figure 6.
Figure 6. Scatter plot for Before Midnight
r
-0.01178
r2
0.00014
𝝰
0.05
α
94.34
b
-0.0073
ŷ
94.34 + -0.0073x
𝘱
0.9440
t
-0.07073
Table 9. Summary of results for
regression and correlation (Before
Midnight)
The
calculated
correlation
coefficient (r), since it is near zero and it is
negative, states that there is a weak
indirect relationship between the amount
of hours studied and the grade point
average of students who study before
midnight. Furthermore, the value of
r-squared (r2) implies that 0.01% of the
total variation in the values of the grade
point average can be explained by the
linear relationship with the values of
hours spent studying. Finally, the 𝘱-value
and t-stat concludes that there is no
significant linear relationship between
the time spent studying and grade point
average for students who study before
midnight.
On the other hand, another
analysis is made for students studying
after midnight. The following statistical
output and graph are shown below.
Figure 7. Scatter plot for After Midnight
r
-0.32836
r2
0.10782
𝝰
0.05
α
96.44
b
-0.5555
ŷ
ŷ = 96.44 + -0.5555x
𝘱
0.29739
t
-1.09931
Table 10. Summary of results for
regression and correlation (After
Midnight)
The
calculated
correlation
coefficient (r), explained by its closeness to
0.5 tells us that there is a moderate
indirect linear relationship between the
amount of hours spent studying and grade
point average of students who study after
midnight. Additionally, the computed
value of r-squared (r2) states that 10.78%
of the total variation in the values of the
grade point average can be explained by
the linear relationship with the values of
hours spent studying. Lastly, the 𝘱-value
and t-stat concludes that there is no
significant linear relationship between
the time spent studying and grade point
average for students who study after
midnight. A possible explanation as to
why the trendline of the graph has a
negative slope, or an indirect X and Y
relationship is because the greater
amount of hours spent studying before
midnight implies that most individuals
will have less sleep, thus playing a factor
in academic performance.
In comparison, the regression and
correlation of both before midnight and
after midnight graphs have a negative
correlation coefficient, or an indirect X
and Y relationship, although the after
midnight graph has a higher negative
correlation.
When
comparing
the
prediction equation for both before and
after midnight, 1 hour of studying will be
more effective for studying after midnight;
but as the hours of studying increase, the
lesser the effectiveness of studying after
midnight becomes and the greater
effectiveness of studying before midnight
becomes.
CONCLUSION
Conclusion of Findings
With many students not being able
to review and study during the day, their
sleep is compromised as they continue to
do academic work after midnight.
Sleeping late is very prevalent among
students because of the lack of time
during the day. This research aims to
determine whether there is a significant
difference in academic performance for
individuals who study after midnight as
compared to those who study before
midnight. The study provided multiple
results and findings on the relationship of
the time spent studying daily to a person’s
academic performance. These findings are
summarized into four major statistical
analyses: estimation of proportion, test
concerning single mean, test concerning
difference of two means, and linear
regression and correlation analysis.
For the first statistical analysis,
namely the estimation of proportion, with
the data that was collected and
calculated, the proportion of students who
study after midnight to the entire
population of students was determined.
The test of estimating the proportion
stated with 95% confidence that 12.17% to
35.83% of the overall general population
of students study after midnight. This
estimated result means that more
students are more drawn to studying
before midnight as compared to studying
after midnight. An explanation to this
data is because more students prefer to
study before midnight, and have higher
alert and energy levels before midnight.
Studying after midnight causes many
students to feel lethargic, and it also
causes them to have an insufficient
amount of sleep.
The data collected, analyzed, and
calculated from the test concerning a
single mean concludes that the average
time students spend studying after
midnight is less than the sample mean.
The explanation for this result is because
the time interval during after midnight is
shorter than the interval in comparison to
before midnight. Students can take longer
and spend more time studying before
midnight than after midnight because
studying after midnight is closer to a
student’s sleeping time, resulting in a
study session being shortened due to
sleep.
The test comparing the GPA of
students who study before midnight and
after midnight concludes that there is no
significant difference that sets the GPA of
students who study before midnight to be
higher or lower than the GPA of students
studying after midnight. An explanation
for this is because studying after midnight
has its own benefits and downsides, same
as with studying before midnight.
Moreover, based on the analysis on linear
regression and correlation, both studying
before and after midnight concludes that
an increase in hours of study decreases
GPA, although based on the results, it
states that only a small percent of hours
spent studying can account for a change
in the GPA. Overall, when it comes to the
relationship between hours of study and
GPA, considering the time of day a
student spends studying, the results tell
us that a big factor that dictates the
relationship between this is more on
qualitative data, like personal preference,
stress factors, energy and focus levels.
Limitations
Some limitations that may have
affected the results of the study is the
current online setup due to the pandemic,
the said online setup could have affected
the normal time spent studying and
academic performance, due to stress,
differed time schedules, and other factors.
Another limitation could be the small
sample size (50). Moreover, the survey
was conducted within De La Salle
University only. A wider sample size could
bring more variety and accuracy to the
data collected.
Recommendations for Future Study
The
researchers
recommend
considering other factors that affect time
spent studying and academic performance
such as disturbances, sleep deprivation,
and other factors that heavily influence
the quality of an individual’s study time.
Furthermore, other types of regression
analyses like lasso and exponential
regression are also recommended for
better prediction equations. Another
recommendation is to use judgement
sampling or quota sampling to specifically
target a certain number of students who
study before midnight and after midnight.
This study can also be further used to
research
the
relationship
between
academic performance and the time of the
day spent studying.
REFERENCES
The Best Time Of The Day To Study: Day
or Night? Oxford Learning. (2017,
November 30).
https://www.oxfordlearning.com/be
st-time-day-to-study/.
When is the Best Time to Study: Morning,
Noon or Night?: PSB Academy.
(2020, January 17).
https://www.psb-academy.edu.sg/bl
og/best-time-to-study.