THE INFLUENCE OF THE SOCIAL MEDIA APPLICATION ON UNIVERSITY STUDENTS RESULTS IN HO CHI MINH CITY

2.3.2.2A factor effect on Engagement EN: Active Collaborative Learning ACL 15 2.3.2.3 The relationship between Perceived ease of use PEOU and Perceived usefulness PU as well as the effec

TON DUC THANG UNIVERSITY FACULTY OF BUSINESS ADMINISTRATION

INTERNATIONAL BUSINESS

ùøùøùø

REPORT BUSINESS RESEARCH METHODS THE INFLUENCE OF THE SOCIAL MEDIA

APPLICATION ON UNIVERSITY STUDENTS RESULTS

IN HO CHI MINH CITY

Lecturer: Tran Thi Van Trang Group: Infinity IQ – Shift: 4 (Monday) and 2 (Wednesday)

Ho Chi Minh City, 30 May 2021

LIST OF GROUP MEMBERS

Full name Student

ID

Synthesis report

4 Truong Minh Thi 719D0173 Chapter 1

(1.4)

Chapter 3 (3.4) Chapter 4

(5.2)

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ACKNOWLEDGEMENT

First of all, our team would like to give their sincere thankfulness and deep gratitude to Ms Tran Thi Van Trang Ms Trang was the one who gave us endless support and conscientious guidance during the course of our research and finished our survey on the subject: <The influence of the social media application on

university students results in Ho Chi Minh City= Base on precious expertise and research experience, she was a passionate help and provided specific guidance on the direction of development, the direction of the study of the subject, while also providing guidance on the appropriate approach, presentation of content, to go in and analysis of the research laid out That is the reason why we can get our survey

as well as the research in the best possible way Secondly, our team would like to thank the Department of Business administration at Ton Duc Thang University for allowing us a chance and good condition to explore and study the subject

Nevertheless, because of limited time conditions, along with the fact that lack of practical experience, he was inevitably flawed, eager to receive comments from teachers and friends Thank you so much

Research Team

Key words: social media applications (SMU); students’ academic performance;

sustainability for education; structural equation modelling (SEM); TAM

TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION 1

1.1 Background 1

1.2 Problem statement 5

1.3 Object and scope of the study 6

1.3.1 Research object 6

1.3.2 Scope of the study 6

1.4 Objectives of the study 6

1.5 Research questions 6

1.6 Significant of research 7

1.7 Structure of the research paper 7

CHAPTER 2: LITERATURE REVIEW 8

2.1 Concepts and theories 8

2.1.1 INP and INL 8

2.1.2 ACL 8

2.1.3 PEOU and PU 8

2.1.4 EN 9

2.1.5 SMU 9

2.1.6 SS 9

2.1.7 SAP 9

2.2 Previous studies 9

2.2.1 Key paper: The research by Mahdi M Alamri, Mohammed Amin Almaiah, and Waleed Mugahed Al-Rahmi 3 (2020) 9

2.2.2 Support paper: The research conducted by Nasser Alalwan, Waleed Mugahed Al-Rahmi, Osama Alfarraj, Ahmed Alzahrani, Noraffandy Yahaya, and Ali Mugahed Al-Rahmi (2019) 11

2.2.3 Support paper: The research articles performed by Jaffar Aman, Mohammad Nurunnabi, and Shaher Bano (2019) 12

2.3 Research Model and Hypothesis 13

2.3.1 Research Model 13

2.3.2 Hypothesis 14

2.3.2.1 Factors effect on Engagement (EN): Interactivity with Peers (INP) and Interactivity with Lecturers (INL) 14

2.3.2.2A factor effect on Engagement (EN): Active Collaborative Learning (ACL) 15 2.3.2.3 The relationship between Perceived ease of use (PEOU) and Perceived

usefulness (PU) as well as the effect of each factor on Engagement (EN) and Social

media application use (SMU) 15

2.3.2.4 Students' Engagement (EN) is a factor effect on Social media application use (SMU), Student’s Satisfaction (SS) and Student’s Academic Performance (SAP) 16 2.3.2.5 A factor effect on Student’s Satisfaction (SS) and Student’s Academic Performance (SAP): Social media application use (SMU) 17

2.3.2.6 The relationship between Student’s Satisfaction (SS) and Student’s Academic Performance (SAP) 17

CHAPTER 3: RESEARCH METHODOLOGY 18

3.1 Research design 18

3.2 Pilot test 18

3.3 Questionaires design 18

3.4 Measurement scales 19

3.5 Sample 24

3.6 Collection method 25

3.7 Data analysis 25

CHAPTER 4: DATA ANALYSIS 28

4.1 Descriptive statistics 28

4.2 Scale measurement/model 30

4.2.1 Reliability testing 30

4.2.1.1 Indicator Reliability 30

4.2.1.2 Internal Consistency Reliability 33

4.2.2 Assessing the accuracy of the model 33

4.2.2.1 Convergent validity 33

4.2.2.2.Discriminant validity 34

4.3 Structural models 35

4.3.1 The overall coefficient defines R Square 35

4.3.2 Path coefficient 36

4.4 Variance analysis of an One Way-ANOVA factor 41

4.4.1 Method variance analysis of an One Way-ANOVA factor 41

4.4.1.1 Examining variances between value groups 41

4.4.1.2 Test the average difference 41

4.4.2 ANOVA test 42

4.4.2.1 Independent Sample T-test for Gender 42

4.4.2.2 Independent Sample T-test for Status 42

4.4.2.3 ANOVA test for Age 43

4.4.2.4 ANOVA test for Degree 44

4.4.2.5 Independent Sample T-test for Job 45

4.4.2.6 ANOVA test for Income 46

4.4.2.7 ANOVA test for SMU 47

4.5 Results of verifying research hypotheses 48

CHAPTER 5: CONCLUSION, AND RECOMMENDATIONS/ LIMITATIONS 51

5.1 Research summary 51

5.2 Recommendations 52

5.2.1 ACL -> SAP 53

5.2.2 INL -> SAP 54

5.2.3 INP -> SAP 55

5.2.4 PEOU -> SAP 56

5.2.5 PU → SAP 57

5.3 Limitations and directions for future research 58

CONCLUSION 59

APPENDIX 60

REFERENCES 61

LIST OF ABBREVIATIONS AND ACRONYMS

SPSS Statistical Product and Services Solutions

Abbreviations of variables

LIST OF FIGURES

Figure 1 The World's most-used social platforms in 2021 by Authors Synthesized

(Source: Datareportal.com) 1

Figure 2 Time per day spent using the internet in the world in 2020 by Authors Synthesized (Source: Datareportal.com) 2

Figure 3 Social media in Vietnam in 2021 by Authors Synthesized

(Source: Datareportal.com) 3

Figure 4 Social media behaviors in Vietnam in 2021 by Authors Synthesized

(Source: Datareportal.com) 3

Figure 5 Most-used social media platforms in Vietnam in 2021 by Authors Synthesized (Source: Datareportal.com) 4

Figure 6 Research model of the relationship between social media application and student’ academic performance (2020) by Authors Synthesized 10

Figure 7 The research model illustrates the factors Affecting Students' Academic Performance in Higher Education by Authors Synthesized 11

Figure 8 Research model about the relationship between positive media factors (PMF), negative media factors (NMF), and Students(2019) by Authors Synthesized 13

Figure 9 Research Model by Authors Synthesized 14

Figure 10 Model analysis Results 50

LIST OF TABLE

Table 3.1 Measurement scales 19

Table 3.2 Criteria for measuring SEM in Smart PLS 26

Table 3.3 Indicators of Cronbach's Alpha in Smart PLS 26

Table 4.1 Demographic characteristics based on 310 samples 29

Table 4.2 Conformity results of factors 31

Table 4.3 Conformity results of factors 32

Table 4.4 Discriminant value of factors according to Fornell & Larcker 34

Table 4.5 Coefficient value R Square and R Square Adjusted 35

Table 4.6 Numerical values of T-statistics, P-values and F square 37

Table 4.7 T Statistics values, path coefficients, and standard deviation of variables 40

Table 4.8 Result of T-test for Gender 42

Table 4.9 Result of ANOVA for Gender 42

Table 4.10 Result of T-test for Status 42

Table 4.11 Result of ANOVA for Status 43

Table 4.12 Result of T-test for Status 43

Table 4.13 Result of ANOVA test for Age 44

Table 4.14 Result of T-test for Degree 44

Table 4.15 Result of ANOVA test for Degree 45

Table 4.16 Result of T-test for Job 45

Table 4.17 Result of ANOVA test for Job 46

Table 4.18 Result of T-test for Income 46

Table 4.19 Result of ANOVA for Income 47

Table 4.20 Result of T-test for SMU 47

Table 4.21 Result of ANOVA for SMU 48

Table 4.22 Results of verifying research hypotheses 49

CHAPTER 1: INTRODUCTION

1.1 Background

Nowadays, our world is continually changing Every passing day we can hear and know new things in the world through the Internet and social media applications People often said that "The Internet is always followed by social networks", this is a true

judgment because if you compare the early days of social networking on the Internet with the present, it has changed very much Specifically, in the past, people could only send emails or search for information, today we can do everything through social networks such as entertainment, connecting with people around the world, and even use it as a tool for learning and research

From a macro perspective, according to statistics from Simon Kemp's

<DataReportal= website, figure 1 shows the most used social media platforms across all countries up to April 2021 Based on this report, we can see that Facebook is the most used platform with 2.97 billion users and the lowest is a social network called Quora with

300 million users A follow-up data in figure 2 shows the average daily human time spent

on social media around the world as of January 2020, according to this report, it

estimated that we humans spend time on social network time for 7 hours per day (account for about a quarter of the total 24 hours per day)

(Source: Datareportal.com)

Figure 2 Time per day spent using the internet in the world in 2020 by A uthors

Based on other statistical data from DataReportal by Simon Kemp, but from a micro perspective, specifically the current situation of using social networks in Vietnam, the data are recorded as follows, see figure 3 In our country with nearly 100 million people, 72 million people have used social networks through a variety of devices and use purposes are extremely diverse from entertainment, for study, and in work Based on these statistics in 2021, Simon Kemp and his associates have shown that on average, Vietnamese spend more than two hours per day on social media, not only that, each person still uses social media every day using a lot of different platforms and currently, there are nearly 10 platforms per user However, unlike the majority of users worldwide, Vietnamese people use Youtube the most and the least is Snapchat See figures 3, 4, and

5

Figure 3 Social media in Vietnam in 2021 by A uthors Synthesized

(Source: Datareportal.com)

Figure 4 Social media behaviors in Vietnam in 2021 by A uthors Synthesized

(Source: Datareportal.com)

Figure 5 Most-used social media platforms in Vietnam in 2021 by A uthors Synthesized

(Source: Datareportal.com)

There are have many benefits such as flexible features, ease to use, and businesses constantly developing new versions of these social media platforms which cause all activities in our lives to be affected Typical evidence of the importance of using social media in learning is that student’s study outcomes during the COVID-19 pandemic have been significantly affected Not only Vietnam but most schools in the world have to transform from teaching and learning immediately to online learning This pandemic has been and will continue to disrupt progress towards sustainable growth in the education sector without the support of social media tools for distance learning According to the latest statistics from the UNESCO Institute of Statistics (UIS), as of April 18, 2020, more than 1.57 billion students in 191 countries and territories were affected by Covid-19, accounting for over 91% of the total number of students Hence, besides the popular social networking platforms, then the specific social media platforms for learning such as Google Meet, Zoom, E-Learning, Linkedin, Youtube, in the past time have not stopped and increased the number of users significantly

By corporating social media applications into learning, it will assist us access knowledge quickly, connect with other learners and even lecturers around the world, then will improve academic performance regardless of interruptions caused by COVID-19 or not Because the application of social media to learning has such a huge role in our life, our research team decided to choose the topic <The influence of the social media

application on university students results in Ho Chi Minh City= for the research When

choosing this topic, our group had the desire to clarify the factors affecting student

learning results through the application of social media to the learning process This is a topic that has been researched in other countries, but at present in Vietnam, there is little research on this topic In addition, research on this topic will help everyone also measure sustainability in higher education, inspect student satisfaction when using social media, and provide advice to help students in Vietnam study more efficiently

1.2 Problem statement

As mentioned in the introduction, our team believes that issues are still of great concern in the world, but we brought back to our country to learn and research, likely that problem will be solved Assuming that these are things of great value or contributing to the development of our country, this is a completely worthwhile thing for us to spend time and effort on researching In this research paper, we discuss the issue of using social networks, the objects that use the most are young people, and using social media in learning the most interested audience is none other than students

It can be said that social media is also a place to learn if we permit them to do that Today, there are many articles about talented young people who take the initiative in their learning by self-study online In the adolescent ages, people can completely spend a lot of time learning through social media platforms while the time in classes is not long enough

to exchange more knowledge with teachers and peers Similar to other problems in

learning, without the support and connection to social media applications, our learning process certainly will be obstacles For example, when we have a problem that is difficult

to solve, instead of using one of the social media platforms to request questions directly

to teachers, friends or find instructional methods by ourselves, we wait until the next class session, so it will take a lot of your time and until the problem is resolved it is probably almost near the end of the semester This is the reason why today's social media affect students' learning and learning outcomes Nevertheless, in addition to the benefits

of social media in learning, it also has potential harms like students looking for other people's work and copying them into their own, from there, our intelligence, our creation

is not guaranteed and the students who do it will accidentally lose their creativity as well

as become dishonest Besides, a range of other problems students use social media in learning is that they often compare themselves to others leading to psychological illness, and the rest is caught up in the attraction Social media applications can lead to either a distraction in school or a drop in productivity of learning All these problems have

happened in the world, but because there are many cultural differences, there still exists a lot of debates in the community, that is the reason why we choose this topic to research

In our country, the subjects are young people currently studying at universities in Ho Chi Minh City, specifically those who fall in the age group of 18 and above and they can be students, Masters or PhDs are intended to be research subjects because they are the ones who know exactly which elements of the social media applications have impacted on their learning process and outcomes In general, in the current context, Vietnam is a country that tends to approach scientific and technical advances and especially

technology very quickly, therefore social networking applications will definitely have a

huge effect on the learning process and results of students, and the issues related to it really deserve attention and research

1.3 Object and scope of the study

1.3.1 Research object

Research subjects are factors of the application of social networks that have influenced the learning outcomes of undergraduate and postgraduate students at

universities in Ho Chi Minh City, Vietnam

Respondents are university and postgraduate students who have been applying social media applications to their own learning

1.3.2 Scope of the study

In terms of space: all surveys were collected from individuals currently living, studying, and working at universities in Ho Chi Minh City, Vietnam

In terms of time: the time for data collection was prepared and implemented

within 02 months from April 2021 to May 2021

1.4 Objectives of the study

Theoretically, this research is intended to check the factors of social media

applications (SMU) used for active collaboration learning (ACL) and engagement of students (EN) how did affect the learning process and outcomes of students at

universities in Ho Chi Minh City, Vietnam After the above factors are checked and analyzed, it will be the base for us to measure the sustainability of education as well as the satisfaction of students when using social networks in learning On the practical side, this research would like to further suggest that in addition to checking how the theoretical relativity of how social applications influence student's academic performance, through this research paper, students can also discover more specific social media platforms for learning as well as recommend learning methods connected to social media applications This research is made with the aim of solving learning problems on social networking applications, this is surely the topic that will get a lot of care from students

1.5 Research questions

In order to achieve the above research objectives and orientation for the research, our group has identified these question to solve the following problems:

▪ How factors Interactivity with Peers (INP), Interactivity with Lecturers (INL),

Active Collaborative Learning (ACL), Perceived Ease of Use (PEOU), and

Perceived Usefulness (PU) were affected when students use social media

applications for their studies to lead to their academic outcomes?

▪ Has the application of social media to learning influenced positively or negatively

on student learning outcomes?

▪ What solutions and suggestions will help students learn with social media

effectively and achieve high outcomes?

1.6 Significant of research

Our team is believed that this research really has value if the questions in the research are clarified When our research was successful, the first thing we did was we made a tremendous contribution to the basis of the theory of tectonic theory, which proves that the research model from our previous papers is both rational and as well as highly efficient when we do it in our country Secondly, the research will help us to distinguish specific factors that have an impact on students' academic performance as they use social media applications in their study and whether the impact is beneficial Finally, based on the student outcomes after this research, schools, and businesses that develop social media applications will be able to see it as a foundation for improving, developing other social media platforms, or updating superior versions containing for helping students to learn better as well as to find methods to improve their learning outcomes

1.7 Structure of the research paper

The research topic of the group is divided into 5 main chapters, specifically as follows:

▪ Chapter 1: Introduction

This chapter introduces an overview of the research topic

▪ Chapter 2: Literature review

This chapter examines previous scientific papers related to research topics as well as giving a theoretical framework of this research

▪ Chapter 3: Research methodology

This chapter clearly analyzes the methods used in the research

▪ Chapter 4: Data analysis and result

This chapter summarizes the conclusion outcomes after researching and discussing the

results of data analysis

▪ Chapter 5: Conclusion and recommendation

This chapter includes a summary of the research topic, making recommendations for the research subjects as well as other stakeholders

CHAPTER 2: LITERATURE REVIEW

2.1 Concepts and theories

Our team has researched and selected from previous studies to be able to find out which research models are suitable for survey subjects in Vietnam Below is the group's research model picture This study considers INP, INL, ACL, PEOU, and PU as

independent variables, EN and SMU as the intermediate, and dependent variables are SS and SAP In addition, it was also developed into a total of 14 hypotheses, to learn more about this model, we had to study each variable definition as well as find a meaningful mutual relationship among them

2.1.1 INP and INL

Guiding the book Didactic Strategies and Technologies for Education published in

2012, author Alice Christudason defined "Interactivity with Peers" [1]as a form of collaborative learning among students to enhance the value of Interacting as well as providing a variety of favorable learning outcomes By interacting with peers, students can learn a lot by explaining their ideas to others or listening to others contribute from friends and then build up knowledge that they themselves still lack

In 2006, the authors’ group including Krause, Bochner, and Duchesne defined

"Interactivity with Lecturers" [2] as positive interactions that express acceptance,

affection, intimacy, understanding, trust, respect, care, and cooperation between teachers and students in the classroom This relationship is based on a lot of efforts from both sides and teachers play an essential and proactive role in communicating with students to help them understand the lecture content

2.1.2 ACL

Active collaborative learning is defined by Marjan Laal and Mozhgan Laal

(written in Procedia - Social and Behavioral Sciences, Volume 31, 2012) [3] as an

educational method that uses groups of two or more students by Face-to-face, with computers, to enhance learning while working together Students will discuss, solve problems and complete a task in classrooms and when active collaborative learning is practiced effectively, it turns the classroom into a positive learning environment

2.1.3 PEOU and PU

Fred D Davis defined these two concepts in his book MIS Quarterly published in

1989 [ ], he argues that Perceived Ease Of Use (PEOU) is the degree to which one 4believes that using a particular system will be effortless and effortless, while perceived usefulness (PU) is the level of the degree to which a person believes using a particular system will improve their productivity and performance

In this study, we also mention The Technology Acceptance Model - TAM, which

is the research model developed by Davis based on the theory of reasoned action - TRA

In the TAM model, there are two main factors: perceived usefulness and perceived ease

of use, through this research model we can see the acceptability of a system and it will

make people have the attitude as well as the intention to use technology, In this situation

is the application of social networks to the learning of college students However,

perceptions may vary depending on age and gender because each person is different

2.1.4 EN

As defined by Michael Stephens in 2020 [5], Engagement is described as the time, effort, or degree of emotional engagement as well as the motivation for students to

collaborate in the learning process and early learning and invest in their academic

assignments This participation refers to the level of attention, curiosity, interest,

optimism, teaching, and passion when a student is studying or teaching in a university setting, from which participation leads to progress in their learning process

2.1.5 SMU

According to the group of authors including Joe Phua, Seunga Venus Jin, and Jihoon (Jay) Kim defined in 2017 [6], Social media application is a useful tool to improve citizens' social capital Through facilitating the sharing of ideas, thoughts, and

information, social media platforms will help us strengthen existing relationships or connect and keep in touch with people in life

2.1.6 SS

The phrase "Student Satisfaction" was defined in 2001 [ ] by Elliott, K & Healy 7

M as a short-term attitude, which is the result of after students evaluating the educational experience that they get Not only that, it has been described as the degree to which students expect to teach, teacher, or in this research situation is the satisfaction of

effectively applying social media to learning It is also seen as a positive precursor of student loyalty and a result of the educational system assessment (Zeithaml, 1988) [8]

2.1.7 SAP

According to Erina L MacGeorge and seven other authors (in 2008) [9], Student’s Academic Performance can be defined as the result of education when anyone reaches their educational ambitions after training and ongoing efforts In this paper, the student's academic performance also helps universities achieve the educational goal of gaining knowledge and developing skills for students and as a basis for assessing the

investigating how SMU factors used for active collaborative learning and engagement affect students' academic performance in evaluating education sustainability and their

satisfaction with its use The constructivism theory and TAM were used as the

investigation model in this study, and a quantitative method was used and evaluated based on surveys of 192 King Faisal Undergraduates The feedback were organized into nine factors and analyzed using structural equation modeling to describe students'

academic performance through evaluating education sustainability, as well as their

satisfaction The findings were analyzed using structural equation modeling, which revealed that all hypotheses were accepted and positively linked to Sustainability for academic achievement, confirming the positive relationship between the use of SMU and the remaining variables considered in our model interactivity with peers, Interactivity with lecturers, Active Collaborative, Engagement, perceived ease of use, perceived

usefulness, SMU, student satisfaction, and academic performance of students The field

of this research is from the Computer Science Department, Community College, Faculty

of Social Sciences and Humanities, Faculty of Technology Management and Business

Figure 6 Research model of the relationship between social media application and

student’ academic performance (2020) by Authors Synthesized

The study results were analyzed using structural equation modeling, and it was discovered that all the hypotheses were backed and significantly associated with

educational sustainability verifying meaningful relation between SMU and the remaining variables in our model interactivity with peers, interactivity with lecturers, Active

collaborative, Engagement, perceived ease of use, perceived usefulness, SMU, student satisfaction, and students' academic performance

However, despite its contribution to the research area, the research's limitations should then be recognized One of them will be the sample, which is limited to

undergraduates at a specific higher level of education and from a specific Saudi Arabian university, the results may differ in other contexts, within each country

2.2.2 Support paper: The research conducted by Nasser Alalwan, Waleed Mugahed Al-Rahmi, Osama Alfarraj, Ahmed Alzahrani, Noraffandy Yahaya, and Ali Mugahed Al-Rahmi (2019)

Nasser Alalwan and partners research on the topic <Integrated Three Theories to Develop a Model of Factors Affecting Students’ Academic Performance in Higher

Education=, 2019 In particular, it can be said that the article helps to reduce the material differences in the use of social media for collaboration and communication and its effect

on student learning outcomes A questionnaire survey of constructivist theory, technology adoption model, and communication theory was used as the primary method of data collection Collaborative learning as well as online communication through the media enhances students' learning activities and allows them to share their knowledge through the media We encourage young people, students to actively use media in their studies, to use media for educational purposes They made this research on the Computer Science Department, Community College, Faculty of Social Sciences and Humanities, Faculty of Technology Management and Business

Figure 7 The research model illustrates the factors Affecting Students' Academic

The results of the study show that perceived interest as well as the perceived usefulness of using the media, thereby increasing students' behavioral intentions in using the media The use of media in learning and information exchange The use of TAM with constructivist theory and communication theory in testing students' behavioral intentions

in using media for collaborative learning and online communication

There is one problem of this research is Student perceptions or observations may different from the instructor's perceptions or from what students do, and moreover, it does not consider differences between different fields of study Future works are

suggested to repeat the study in other provinces rather than in Malaysia, having dissimilar environments and considering these further limitations

2.2.3 Support paper: The research articles performed by Jaffar Aman, Mohammad Nurunnabi, and Shaher Bano (2019)

This research paper examines the problem <The Impact of Social Media on

Learning Behavior for Sustainable Education: Evidence of Students from Selected

Universities in Pakistan= by Jaffar Abbas and his Co-research,2019 In this research, he mentioned that nowadays, social media is taking an important part in the learning

performance of university students to achieve better education Social media’s effect on education is becoming necessary and motivates elementals The world has become an international village and the use of new technology has made the world smaller through social media So, the purpose he made this research the first research about this problem

is one of the few focused investigations about exploring the relationship between the positive and negative side of social media and the performance of university students toward better education Though, the goal of this research is to consider the constructive and adverse factors that affect student’s minds and how those elements helped the student

to share positive and negative aspects with other people More and more people realized that social media websites and their applications brought huge benefits and risks to

university students and their affection for student’s psychological adjustment or learning performance is not clear This research adopted the cluster sampling method and

responder from five chosen regions Researchers gave 1013 tables of questions among the targeted sample of university students with an age from 16 to 35 years, and they have collected 831 full/valid answers This research applied the social satisfaction theory to examine student’s performance in using social media This research has specific

determination 18 the constructive and adverse facts from these previous data The results are showing that social media usage in Pakistan harms student’s performance compared

to positive aspects The results may not be generalized to the entire student community because it was answered by chosen responders This research presents a relationship between unscientific features and the creativity of social media and shows the new roads

to study in the future by more understanding about social media usage based on webs He made this research from social media, learning attitude, sustainable education, social networking in Pakistan

Figure 8 Research model about the relationship between positive media factors (PMF),

The result of this study showed that approximately 65% of the technology experts play an important role in the study process of university students in Pakistan, while the rest support using social media for study but they believe students do not do well in the learning process by using social media But this result still gives a clear signal about how important social media affects the study performance of universities in Pakistan

However, there is a limitation which is the research scope of only a few selected

to develop the model of factors affecting students' academic performance in higher

education while the content in the next support paper only gives positive/negative effects from social media applications to student learning behavior Therefore, the selected research model generally meets the research needs, desires, and purposes of our group and we would like to build the research based on this model

Figure 9 Research Model by A uthors Synthesized

2.3.2 Hypothesis

2.3.2.1 Factors effect on Engagement (EN): Interactivity with Peers (INP) and

Interactivity with Lecturers (INL)

In the article "exploring magic cottage", a team of researchers including Patera, Draper, and Naef claim that Social Media Applications (SMU) for learning permit the discussion between pupils and teachers about content and tasks become more efficient (Patera, 2008) [10] Many researchers observed and indicated that students usually spend

a lot of time using SMU to fulfill their homework or their learning processes when they are in the online environment (Bryer, 2010) [11] Through the article "Facebook usage, socialization, and academic performance" published in a scientific journal named

"Computer and Education", interrelates in educational contexts can support EN in

learning communities from collaboration to communication (Ainin, 2015) [12] Besides that, some previous studies (Al-Rahmi, 2018) [13] explained that interaction with

members from teamwork proceeding as well as peers has an important relationship between Active Collaborative Learning (ACL) and Engagement (EN), two elements that could promote the idea that Interactivity with Peers (IN-P) and Interactivity with

Lecturers (IN-L) affect Students' Academic Performance (SAP) Hence, in this research the group of authors suggested the following hypotheses:

▪ Hypothesis 1 (H1): The noteworthy relationship between Interactivity with Peers

(IN-P) and Engagement (EN)

▪ Hypothesis 2 (H2): The noteworthy relationship between Interactivity with

Lecturers (IN-L) and Engagement (EN)

2.3.2.2 A factor effect on Engagement (EN): Active Collaborative Learning (ACL)

According to Pierre Dillenbourg who wrote this issue in "What do you mean by collaborative learning?" in the year 1999, he explored issues related to active cooperation

in learning such as the meaning of learning and collaboration, effects and theories of collaborative learning, and so on As he said, ACL is a circumstance in which two or more pupils study together (e.g., face-to-face or through social media foundations like Facebook, Instagram) (Dillenbourg, 1999) [14] They said that the effect of Social Media Application (SMU) use on Interactivity with Peers (INP) expedites communication and knowledge creation, and thus creates favorable conditions for Active Collaborative

Learning (ACL) (Liu, 2003) [15] In this respect, as long as it spreads learning out of the classroom, SMU will allow the creation of spaces for the formation of knowledge

(Bryer, 2010) [16] Through SMU, lecturers are responsible for building a training design aimed to improve ACL (Fewkes, 2012) [17] The first thing, it is really important to select SMU because we know that different SMU have sole characteristics (Cheng, 2016) [18] The second thing, we should also consider the design of components like the task or assessment, these things can act as facilitators or as obstacles to collaboration (Al-Rahmi, 2017) [19] Moreover, many extensive open online courses such as MOOCs have been perceived to be positively influenced by the extended conformation model (ECM) from online ACL, which shows Students' Satisfaction (SS) and Perceived Ease of Use (PU) (Junjie, 2017) [20] Also in the early research stages, the hypothesis about the important relationship between Active Collaborative Learning (ACL) and Engagement (EN) was carried (Al-Rahmi, 2019) [21], so this research recommended the hypothesis as follow:

▪ Hypothesis 3 (H3): An important relationship between Active Collaborative

Learning (ACL) and Engagement (EN)

2.3.2.3 The relationship between Perceived ease of use (PEOU) and Perceived

usefulness (PU) as well as the effect of each factor on Engagement (EN) and Social media application use (SMU)

As mentioned in the definition above, PEOU and PU are the two basic elements of the Technology Application Model (TAM) This model has a significant impact on

research assessing the acceptability of technological advances and the use of social media for learning According to previous studies showing that using social networking

applications is very easy when we use them to improve the learning process of students (Zeithaml, 2000) [22] Besides the combination of two variables PEOU and PU in the TAM model, there are also other variables, so there exist TAM variations that combine in many different ways with the variable of Student’ Academic Performance (SAP)

However, our research model involves only two fundamental variables in the TAM model as well as Engagement (EN), Student’ Academic Performance (SAP), and student satisfaction (SS) when they use social media for learning

When a student becomes aware that using social networking applications will be beneficial for their studies, they will begin to think about it more positively (Lin, 2011) [23] In this case, PU is considered as the factor that has the greatest influence on the application of mobile technology platforms in learning (Almaiah, 2019) [24 25, ] A group

of 4 study authors has demonstrated that students have found it useful to use social networking applications and that they have high intentions of using it as an online

learning resource (Hsu, 2012) [26] Besides, not only students but lecturers also feel useful when applying social networking applications to their lectures Through the above information, this study gives the following Hypothesis:

▪ Hypothesis 4 (H4): A meaningful connection between perceived ease of use

(PEOU) and Engagement (EN)

▪ Hypothesis 5 (H5): A strong relationship between Perceived usefulness (PU)

and Engagement (EN)

▪ Hypothesis 6 (H6): A considerable link between perceived ease of use (PEOU)

and Social media application use (SMU)

▪ Hypothesis 7 (H7): A positive impact was observed between the use of

perceived usefulness (PU) and Social media use (SMU)

▪ Hypothesis 8 (H8): A massive relation between perceived ease of use (PEOU)

and perceived usefulness (PU)

2.3.2.4 Students' Engagement (EN) is a factor effect on Social media application

use (SMU), Student’s Satisfaction (SS) and Student’s Academic

Performance (SAP)

All technological innovations are meaningless without the participation of anyone (Rueda, 2017) [27] and social networking platforms are no exception (Junco, 2013) [28] The use of personalized social media platforms allows each student to design their

learning and this will make it easier for them to build knowledge For instance, Facebook has provided many features and social benefits to students when they apply this platform for learning (Camus, 2016) [29] When students participate in social networking

applications for learning purposes, they will have a greater sense of learning, know how

to participate in tasks, allow me to have and thus their performance, learning outcomes will significantly improve and students will surely be satisfied with it (Moafa, 2018) [30,31 32 33, , ] Therefore, this study has proposed the following hypotheses:

▪ Hypothesis 9 (H9): Engagement (EN) impact on Social media use (SMU)

▪ Hypothesis 10 (H10): Engagement (EN) impact on Student’s Satisfaction (SS)

▪ Hypothesis 11 (H11): Engagement (EN) impact on Student’s academic

performance (SAP)

2.3.2.5 A factor effect on Student’s Satisfaction (SS) and Student’s Academic

Performance (SAP): Social media application use (SMU)

The use of social media is believed to be a key factor contributing to improving student learning outcomes, thereby measuring sustainability in education as well as related to student satisfaction when using it (Al-Rahmi, 2019) (Al-Maatouk, 2020) (Cao, 2013) [34 35 36, , ] This is why this study has attempted to find a relationship between them, but unlike previous studies, this paper has been consulted from the perspective of many different universities in Ho Chi Minh City Because the learner has increased the popularity of social media use among students and faculty, it is seen as playing a very useful role in improving, enhancing learning outcomes as well as improving for students

to be satisfied when using Therefore, this study gives the following hypothesis:

▪ Hypothesis 12 (H12): Social Media Use (SMU) impact on Student’s

Satisfaction (SS)

▪ Hypothesis 13 (H13): Student’s Academic Performance (SAP) has impacted

by Social Media Use (SMU)

2.3.2.6 The relationship between Student’s Satisfaction (SS) and Student’s

Academic Performance (SAP)

This research studied and pointed out that when students achieve learning

outcomes as expected, they will get satisfaction, specifically in this case they were satisfied when using social networking has brought good benefits in learning Therefore, this study focuses on the relationship between SS and SAP, the hypothesis is given as follows:

• Hypothesis 14 (H14): Student’s Satisfaction (SS) has a great connection

with Student’s Academic Performance (SAP)

CHAPTER 3: RESEARCH METHODOLOGY

3.1 Research design

The research process of the group goes through two main stages: experimental and formal research Because of the limited time and resources available at the experimental stage, the team does not use any of the methods but only the models and scales of

previous studies so that it can adjust the survey subjects to be university students in Viet Nam Later, when moving to the formal phase of research, the group decided to adopt a quantitative approach by conducting a survey directly through questionnaires

On issues related to the survey, after having examined the questionnaire, translated the questionnaire into Vietnamese in order to better suit Vietnamese students as well as submit it to their staff for review and review After the questionnaire was accepted, the group began calling for the correct study group that the students were studying at

universities in Ho Chi Minh City, Vietnam The questionnaire was designed by Google Form utility, which included a number of simple questions on the personal information section and the main questions, and chose the Likert scale for the survey

3.2 Pilot test

After the group has built the questionnaire itself and before the teacher evaluates it

as appropriate, to be able to take it to the survey, testing whether the true level of

respondents' questionnaire is essential because it will directly affect the statistical results, run the model or analyze the data In cases where, if the experimenter doesn't understand and they answer questions based on sentiment or random selection, the results will

finalize, and so the pilot experiment will be the first step that will help the group test the quality of the words used The method of asking questions and the order of questions in the questionnaires before the start of the questionnaire's release - a formal survey form, also helped the group avoid errors that were too late to be reworked

For the subjects of the pilot test, the group selected only the subjects of the survey in small numbers of about 20 However, since the group focused mainly on retrieval of quantitative data, participants in the pilot section conducted surveys using pre-existing questionnaires, after they answered the group would not ask further open questions regarding the research issue and the data collected would not enter the official data processing software However, instead the group will ask and take advice from the

participants on questions, answers, and so on So that we can then synthesize and adapt the questionnaire to a more appropriate level

• Part 1: Personal information

Gender, age, industry, and personal income were assembled to characterize the study's participants and understand the major individuals who completed the

questionnaires based on demographic standards

• Part 2: Survey content

Factor claims here include accompanying: Interactivity with Peers, Lecturers, Active Collaborative Learning, Engagement, Perceived Ease of Use, Usefulness, Social Media Use, Students’ Satisfaction, Students’ Academic Performance All of these statements are measured by the Likert scale of 5 points (from 1 Strongly Disagree to 5 – –Strongly Agree)

usefulness has 6 items; (7) Social media use has 4 items; (8) Students' satisfaction has 4 items; (9) Students' academic performance has 5 items The scale used in this study is the five-level Likert (1- Strongly disagree, 2- Disagree, 3 - Uncertain, 4- Agree, 5- Strongly agree) These variables represent the following components that influence college student learning through social networking applications:

Table 3 1 Measurement scales

INTERACTIVITY WITH PEERS (INP)

INP1 SMU facilitate interaction with peers

Patera, 2008

INP4 SMU allow me to discuss with peers

INP3 SMU allow me to discuss with peers.

INTERACTIVITY WITH LECTURES (INL)

INL1 SMU facilitate interaction with

lecturers

Patera, 2008

INL2 SMU give me the opportunity to

discuss with lecturers

information with lecturers

ACTIVE COLLABORATIVE LEARNING (ACL)

ACL1 By using SMU I felt that I actively

collaborated in my experience

Dillenbourg, 1999

ACL2 By using SMU I felt that I have

co-created my own experience

ACL3 By using SMU I felt that I had free

reign to co-create my own experience

ACL4 By using SMU I am satisfied with

active collaboration in my research

ENGAGEMENT (EN)

EN1 By using SMU I engage in interactions

with my peers

Rueda, 2017

EN2 By using SMU I engage in interactions

with my lecturers

with others effectively

EN4 By using SMU I am satisfied with the

EN in my studies

PERCEIVED EASE OF USE (PEOU)

PEOU1 I feel that using SMU will be easy in

PERCEIVED USEFULNESS (PU)

PU1 I believe that using SMU is useful for

SOCIAL MEDIA USE (SMU)

SMU1 I use SMU for interaction with my

peers

Rahmi, 2019; Maatouk, 2020; Cao, 2013

Al-SMU2 I use SMU for interaction with my

lecturers

SMU3 I use SMU for active collaborative

learning

SMU4 I use SMU for engagement.

STUDENTS’ ACADEMIC PERFORMANCE (SAP)

the concepts studied

SAP4 SMU are helpful in my studies and

make it easy to learn

SAP5 SMU improve my academic

performance

3.5 Sample

The number of samples chosen plays a crucial role because the study's results and reliability are guaranteed depending on it Theoretically, the study results are more accurate and significant in practice as the sample size increases However, as mentioned, the time and resources were so limited that the group was unable to survey large numbers

of samples, so the group used the formulas of researchers to help facilitate the sampling process

According to research by Hair, Anderson, and Black (1998), they found the minimum sample size to be five times the total observed variable The formula below is used by researchers to analyze elements (Comrey, 1973 and Roger, 2006):

n = 5 *m ( m là number of question)

According to research by Tabachnick and Fidell (1996), the minimum sample size required is:

N = 50 +8 *m (m is number of independent variables)

Based on these two formulations, my team has the following results:

N = 39*5 = 195

N = 50 + 8*5 = 90

Thus, the minimum sample size would be 195, but to increase the reliability and persuasion of the analysis, my team estimated that it would collect about 350 samples for data analysis purposes

3.6 Collection method

The average study would take about five minutes for students who were both thinking and doing, and to make this study more widely known, the group sent links to this form through forums popular with large numbers of students involved: The student community group, Fanpage /blog about student problems or even calls for conducting personal

Facebook surveys as well as sending messages to their friends through Messenger,

Instagram and Zalo

The group had begun to collect data in early April 2021, and within two weeks of the survey, between 12-25/04/2021, the number of polling notes was recorded to be 323 forms, but in a rescreening process, the full number of samples were filled, correct for use

in the analysis to only 310 samples That is, the group eliminated 13 forms of the research object type or that one that was not suitable

non-3.7 Data analysis

As mentioned in the design of the study article, the group chose a quantitative approach through an existing questionnaire The reason we use this method is that it is suitable for the study of the attitudes, opinions, and behavior of the people surveyed In addition, in 2004, Kothari argued that theories are often associated with this method to measure research factors, examining the relationship between variables in numerical and statistical form

Quantitative results from a sample group will be generalized to a larger sample overall and the software used by the em to run the data in this study is Smart PLS This is the software recommended by a lot of students and faculty because it is highly regarded

as lightweight software Make visual results compared to software of the same type that still ensures performance in model estimation In addition, Smart PLS is suitable for the analysis of primary data, in particular for studies using SEM models in business,

economics, sociology, and psychology

So to sum up, this group of children is using Smart PLS software to run their data primarily, and there are some other parts that need support from SPSS However, for a more general and relatively accurate analysis, there are parameters of this two software that the team needs to keep in mind during the process, namely:

SRMR (Standardized root mean square

Discriminant validity Sqrt (AVE) > Latent variable

correlations

Table 3 2 Criteria for measuring SEM in Smart PLS

a/ Cronbach's Alpha reliability analysis:

In 1951, Lee Cronbach developed the Alpha, which is a test designed to analyze and evaluate the reliability of the scale and has a variable value as a number in paragraph [0.1] Following are some of the standards in this scale of reliability savings:

• If a measured variable has a Total Correlation coefficient, Corrected Item - Total Correlation ≥ 0.3 then the variable is required (source: Nunnally, J (1978),

Psychometric Theory, New York, McGraw-Hill)

• For disused questions and Likert scale questions, we have a common rule for explaining Alpha:

Cronbach's alpha Internal consistency

The correlation coefficient (symbol: R), developed by Karl Pearson in the 1880s,

is a test statistic that measures the statistical relationship or links between variables dependent on continuous variables and has movement values in the continuous range − 1

to +1 Consider for example the relationship between the satisfaction of using social networks and the learning outcomes of students or the relationship between student participation in the classroom and their interaction with the faculty Some of the things to note when using this coefficient are: