Hiệu quả sử dụng smartphone về kết quả của học sinh tại trường đại học ngoại thương chi nhánh II( ANOVA )

Hiệu quả sử dụng smartphone về kết quả của học sinh tại trường đại học ngoại thương chi nhánh II( ANOVA )

FOREIGN TRADE UNIVERSITY Faculty of Economics and International Business

- -DISSERTATION

THE EFFECT OF USING SMARTPHONE ON THE RESULT OF THE STUDENT IN FOREIGN TRADE UNIVERSITY BRANCH II (ANOVA)

TABLE OF CONTENTS

ABSTRACT

2.2 Methods of data collection and model estimation technique 6

THE EFFECT OF USING SMARTPHONE ON THE RESULT OF THE STUDENT IN FOREIGN TRADE UNIVERSITY BRANCH II (ANOVA)ABSTRACT

In this digitization world, media is constantly improved day by day From thelaptop to the cell phone, especially smart phone Using modern technology to serve forthe purpose of learning is really a powerful tool However, beside the good side, it stillhas some downsides surround the use of phone Almost the students use smart phonemore than 2 hours each day Spending too much time using phone may be the reasonmakes students’score feel lack of concentration, lacking of sleeping or even though itcan make student live in digital world and live far away from people around them Sohow about student of Foreign Trade University II? Using smart phone too much makeeffect on learning outcomes? Isn’t it? Thus, our group researched, reviewed andanalyzed the relationship between the time using smart phone of student at FTU2 in

Ho Chi Minh City and their learning outcomes Purposes of researching isunderstanding clearly the degree of influence of time using smart phone to the result oflearning and review that if spending lots of times on using smart phone, Will theyreally effect to your learning outcomes? If yes, we will show some ways to surmountthis situation Through the using of factor ANOVA variance methods from the directsurvey 238 students, we have a conclusion that using smart phone too much can effect

to student’s results Finally, our group will expose some ways to restrict using smartphone excessively and how to use efficiently to promote the learning outcomes of eachstudent

KEY WORDS: Learning outcome, time of using, analysis of variance, Foreign Trade

University 2, students, one-way ANOVA, Tukey's HSD test

1 Introduction

Nowadays, along with the evolution of Information Technology, telephones arenot only for texting and calling purposes, but they also help us to connect with eachother via social networks, email and other online services These smartphones arebecoming more modern and helpful day after day However, overusing smartphonemay cause many negative effects on everyone especially college students Theseeffects include decline in health, waste of time and decrease in study result Thedecrease in study result is the most serious consequence when smartphones are gettingcommoner among the students

The phenomenon that smartphones are addictive and affect many respects oflife is no new problem It has appeared so many times on the media This is anunsolvable problem for the students as well as a deep concern for the parents.Therefore we decide to carry on the topic “The effect of smartphone on the studyresult of the student in Foreign Trade University branch II” by analyzing One - factorANOVA We find down how the percentage, scale and usage of smartphone of thesecond-year student of Foreign Trade University branch II in HCMC change theirstudy result as well as propose some solution to overcome this worrying problem

2 Theory and research methodology

2.1 Theoretical basis and Analysis framework

While the analysis of variance succeeded in the 20th century, antecedentsextend centuries into the past according to Stigler These include hypothesis testing,the partitioning of sums of squares, experimental techniques and the additive model.Laplace was performing hypothesis testing in the 1770s The development of least-squares methods by Laplace and Gauss circa 1800 provided an improved method of

squares By 1827, Laplace was using least squares methods to address ANOVA

problems regarding measurements of atmospheric tides

The phrase “analysis of variance” was coined by Sir Ronald Aylmer Fisher, astatistician of the twentieth century, who defined it as “the separation of varianceascribable to one group of causes from the variance ascribable to the other groups.Tests hypotheses are made about differences between two or more means If

independent estimates of variance can be obtained from the data, ANOVA compares

the means of different groups by analyzing comparisons of variance estimates There

are two models for ANOVA, the fixed effects model, and the random effects model (in

the latter, the treatments are not fixed)

The purpose of analysis of variance is to see if there is any difference betweengroups on some variable In research, analysis of variance is used as a way to considerthe effect of a cause factor to the results factor

The method contains:

Supposing we have k groups 1, 2, 3 …k (may be different from size) Callingµ1,µ2,µ3….µk

Xij: observation j of group i

…

x 2n2

…

x knk

Find the average each group:): ´x=∑

Step 2 :Find total sum of squares

SSW- Within groups sum of squares:

Step 3: Find variances

MSW (mean square within): MSW=SSW n−k

MSB (mean square between): MSB=k−1 SSB

Step 4:One-way ANOVA Table

Source ofvariation

SS(sum ofsquare)

Df(degrees offreedom)

MS(mean ofsquare)

F ratio

BetweenSamples

SSB k−1

F=

MSB MBW

Samples SSW

n−k

In: k number of populations

N Sum of the sample size from all populations

df Degrees of freedom

HSD (honest significant difference) test

The purpose of the analysis of variance is to test the hypothesis H0 that theoverall average is equal After the analysis and conclusions, there are two cases whichcan occur: H0 hypothesis is accepted or rejected If the hypothesis H0 is accepted,analysis will end If the hypothesis H0 is rejected, the overall average is not equal Sothe next further issue is to analyze and identify that any group is different from othergroups, the average of groups is greater or smaller

There are many methods to calculate when hypothesis H0 is rejected We useTukey method The content of this method is to compare pairs of the average groups at

a significance level α for all possible tested pairs to detect the different groups

Example:

Research byU.S.scientistsatKent State UniversityofOhiofound thatstudents-studentsusingsmart phonetoomuchcan lead toanxietyandlearning outcomedecline Theresearcher surveyed 500 students on daily smartphone usage , lifestyle analysis andacademic scores for the purpose of considering whether smartphones can help improvetheir lives or not

The result shows that using smartphone too much has scores of disadvantage Studentswho use too much have the worst score but they are at the highest level of anxiety.

The teamreportedin the journalComputersinHumanBehaviormajors: "When thefrequency ofmobile phoneuseis toohigh, the degree of successinlearningandinlifefellcomfortable Statistical modelingsuggests thatsuchrelationshipsareclear

Research of Dr Karla Murdock at Washington Lee (USA) University has the sameresult This research shows that students who send a lot of message usually less sleepand more stress than others

Based on that, we decide to use analysis of variance and Tukey's HSD test tosurvey whether using smartphone affects to the study result of the second-year student

of FTU II or not

2.2 Methods of data collection and model estimation technique

The data used in this research is collected from the researchers’ questionnaires.Because of time and resources restriction, the researchers only carry survey on 238people Therefore, the result cannot generalize for the whole set because eachindividual surveyed has their own features and cannot represent for the whole set

We had to choose the one factor ANOVA to analyze Compare the average of

many populations based on the average of models Consider the effect of one factorreason to result factor

3 Results and discussion

H1: The average monthly food cost of them are not equal.

Table 1:Anova: Single Factor by Excel

Groups 136,1692091 234 0,581919697

If F > F crit, we reject the null hypothesis As we can see in the table above:

populations are not all equal At least one of the means is different Therefore, we cansay that the hour for using smart phone does affect how much to the result / averagemark of students.

3.3 HSD (honest significant difference) test

Because the null hypothesis has been rejected, the result / average mark of fourgroups are not equal However, in order to find out how they differ from each other,

we need to do Tukey’s HSD (honest significant difference) test and compare eachcouple of group

t-Test: Two-Sample Assuming Equal Variances

0,354579874

Pooled Variance 0,430531732

Hypothesized Mean

Pooled Variance 0,522143574

Hypothesized Mean

Pooled Variance 0,683793757

0,961922206

Through the analyzing process above, we can say that the result / average mark differssignificantly as the hour for using smart phone change, except the case of From 0h to2h and >2h to 4h, cause the difference in the hour for using smart phone betweenthem is not big enough.

4 Conclusion and Policy Implication

After researching influences of using smartphones on the study results of ForeignTrade University II students, we can know that the time of using smartphones plays animportant role in their study results

Although study results depend on many impacts such as intelligence, working, study method and so on, time for studying is also a very essential one Themore time students spend on using smartphones, the less time they spend on studying.When a student spend more time on learning, his or her study results will be certainbetter and vice versa It is very clear that screen time right before bed is bad for sleep.And using your smartphone late at night also makes you feel depleted in the morning,thereby making you less focused and engaged at studying.

hard-To have a good study result, a student need know how to arrange study time andreasonable entertainment Time for using smartphones should be within a certain limit

It will be better for students’ health as well as study results if they do not usesmartphone after 9 pm Smartphones only brings much benefit and convenience whenstudents know how to use them reasonably