Đề tài môn học xuất sắc ueh500 năm 202 tên công trình a survey on factors that cause difficulty for university students in online learning

The study found that there are 2 main barriers that have the most impact on university students’ online learning: Economic barrier and Psychological barrier.. The survey shows that 4 mai

ĐỀ TÀI MÔN HỌC XUẤT SẮC UEH500 NAM 2023

TÊN CÔNG TRÌNH: A SURVEY ON FACTORS THAT

CAUSE DIFFICULTY FOR UNIVERSITY STUDENTS

Abstract:

In recent years, learning plays an important role in our daily lives, which is always appreciated in all fields In this modern era, besides studying in traditional ways like before; nowadays, more and more modern equipment is being invented to meet our demands, especially in learning Thanks to those new updates, people can study whatever or whenever they want without going to class Between 2012 and 2019, the number of distance-only students at traditional universities increased by 36 percent Besides that, with the outbreak of the Covid-19 epidemic, all human activities, especially, learning is limited Therefore, online learning has been applied more People can study at their home and interact with their teachers through learning platforms Online learning is increasingly improving, helping students to be more autonomous in their learning However, online learning still has many obstacles for students

For these reasons, we carried out this survey to analyze the general model about the factors that cause difficulty for students in online learning Our group surveyed 127 participants from different universities in Ho Chi Minh City There are 5 barriers that

we propose in this project: Technological barrier, Psychological barrier, Economic barrier, Environmental barrier, and Social interaction barrier The study found that there are 2 main barriers that have the most impact on university students’ online learning: Economic barrier and Psychological barrier Our group proposed some suggestions for universities and educational institutions to these challenges based on the results

CHAPTER 1: INTRODUCTION

1.1 Background and Reason (Problem statement)

For a couple of decades now, technological advancements have resulted in many changes in people's habits, from shopping to eating, as well as substantial

improvements in schooling Because of the Covid-19 epidemic in 2020 and 2021, we can see a significant transition from traditional learning to online learning From 2011

Il

to 2021, the number of learners reached by massive open online courses (MOOCs) increased from 300,000 to 220 million (Dhawal Shah, 2021) while the circumstances

of the COVID-19 pandemic in 2020 rapidly accelerated that growth by an additional

92 percent (IPEDS, 2020) Ahuge number of learners and educators are required to participate in online learning worldwide

It is widely accepted that online learning has significant advantages Online learning enables universities to reach learners at a distance, increases convenience, and expands educational opportunities; it also offers students such advantages as accessibility, flexibility, equality, collaboration, and active learning Online learning allows

participants regardless of age, gender, and education level to participate in learning activities

Despite the numerous benefits that online learning brings to our education system, barriers to the effectiveness of this method are still present We want to better

understand what barriers students face the most when attempting to learn online, and ultimately how we can help individuals in their learning by understanding their

particular obstacles This research will summarize barriers to online learning and, thus, serve as a suggestion for students and teachers to improve the online learning

experience in the future

1.2 Aim of research

Given the growing importance of online learning and its applications in the university environment, it is critical to understand the barriers that act upon it The purpose of this study was to determine factors that have the most negative impact on college students’ experience with online classes This will enable students and educators to focus on the most critical potential barriers to successful online learning

implementation and provide students as well as educators with suggestions for these problems

1.3 Research question

- What barriers did students encounter during taking online classes?

- Place: Ho Chi Minh City

Research sample: 127 students from universities in Ho Chi Minh City

Research object: Elements that make online learning challenging for university students

1.5 Research contribution

-Theoritical aspect:

Identify and provide evidence for factors that contribute to difficulties experienced by university students in online classes Moreover, contribute to the development of the understanding of the intersection of the barriers to online learning, and their impact on academic outcomes

-Practical aspect:

Provide insights for educators and administrators about the challenges students face in online classes, which could inform the design of online courses and the provision of support services The research also aims to help ensure that university resources and support are directed towards the areas of greatest need, based on evidence about the factors that contribute to difficulty for students in online classes Table of contents:

Contents

CHAPTER I: INTRODUCTION cc ceeccceecereeeeeneeeeecneeeeeneeeesacuneeesniteeesneneeeeteneetess |

1.1 Background and Reason (Problem statemen) Q2 2n S2 Hs xe

1.2 Aim of research ceeeee cece eects ceeeeeececneeeeteeeeesenneeetecaeeeesieeeetnineeetnnneeeeeees II

1.3 Research Question oo cccccccccccccceccceecceeeceeeeeeeeeeeees cece eesseesssaaeesessaeeaaeeeaeeeeaeenes II 1.4 Research scale, sample, and object - - cv 2v vn ren Il

1.5 Research contribufiOIn c1 HT TH TH TT KT ghe lII

CHAPTER II: THEORETICAL BASIS .Í L0 22212 21H Hành 6 2.1 Related researCh .L HT HH HH TT KT TT nen KT TT TK TH kkk 6

2.3 Proposed research model: - c2 1 2110111111 1v v1 ve 8

CHAPTER III: THE METHODOLOGY - Đ 0S 22211221121 112 HH ghe 10 CHAPTER IV: RESEARCH RESULT: L2 2-1 1222 12H HH Hà nhe 17

4.1 Descriptive statistics of survey sample: c2 S2 ven 17 4.1.1 General information of parficipanfs nh HH Hee 17 4.1.2 Learning platform usage .- -c c0 0 0n n HH HH HH HH HH n TH HT TH nen 18

LÍ: TP - caadaaaaiiiiiiiiiaÝŸ 20

4.1.4 Learning locafion c0 221 2n v1 v1 vn Tnhh 22 4.2 Analytical data from key quesfiOns . .cccccnn HH n HH HH HH HH nhe 22 4.2.1 Reliability test: Cronbach’s Alpha 22x22 S2 xe 22 4.2.2 EFA— Exploratory factor analySIS - TQ TQ n SH HH HH HH nn nghe he 30

1-9) 2017757 ai 48 Appendix 1: The content of the SUFV©V Q00 Q00 Qn HH n HH HH Hn TH Tnhh ng t2 key 48

5 Yếu tố tâm lý - 1 c2 : 2121 111111111111111 0101111111111 1010111 011011101 00110111 g 55

Appendix 2: Result of Cronbach Alpha HS HT SH Tn ng HH khe Hay 56 Appendix 3: Result of EFA Q00 2 2S HH TK 62 Appendix 4: Result of Pearson Correlation and Regression Analysis 74

CHAPTER 2: THEORETICAL BASIS

2.1 Related research

Our group’s project took inspiration from another survey that was conducted by

Nguyen Thi Bich Lien (Barriers affecting students’ online learning in Ho Chi Minh

Rao can vé kinh té }

University of Economics (UEH) with 33,3%; 14,4%; and 11,8% participation rates respectively

After calculations are made for each barrier it is shown that:

Economic barrier: College students rate the scale as moderate which means that they

do not see the economy as a barrier that bothers them too much when studying online

7 There is also no difference in how students feel about this barrier that is from different universities and different courses

Social interaction barrier: The impact of this barrier on online classes is rated by college students as “quite impactful” The analysis shows that there is a big difference

in how college students feel about this barrier that are from different universities and

courses

Psychology barrier: “Lack of concentration” is the factor rated highest in this

category (3,97) This is a common problem for every individual that participates in online classes The analysis shows that there is a major in how each student rates the barrier

Environmental barrier: A major drawback of studying online is that it fully relies on

an Internet connection, which means that if your electricity cuts out or your Internet connection is unstable, it will have an impact on your studies and affect your academic performance College students regard this as the most impactful barrier

The survey shows that 4 main barriers affect online studying: Psychological barrier , Economic barrier, Environmental barrier, and Social interaction barrier

2.2 Definitions:

- Barrier:

Barriers to online learning are obstacles encountered during online learning (at the beginning, during the program, and upon completion of the training), which can have a negative impact on people's learning experience study (Mungania, 2004) The influence on online learning is very diverse such as psychological, economic, social, and technical (Balakrishnan, 2012)

- Online learning:

Online learning is a method of distributing learning materials and content based on modern electronic tools that are implemented entirely through a learning management system (LMS) such as Blackboard, WebCT, and Moodle Most of the interaction

8 between teachers and students, the interaction between students is done with the support from learning management systems (Bender, 2003) In a typical online classroom, each student has an account to access wherever and whenever they want Popular learning activities on the online learning system include participating in discussion forums, watching instructional videos or lectures, reading materials posted

by instructors, submitting homework, taking tests, or practicing the language In this learning environment, computers provide learners with all kinds of resources they need based on learners’ choices and feedback

2.3 Proposed research model:

9 barriers to online learning are the lack of equipment Besides that, (2) technology is still the main barrier to online learning

Therefore, our proposed hypothesis is:

H1: Technological barrier has a positive impact on Difficulty in online classes 2.3.2: Economic barrier:

The lack of financial aid is one of the biggest economic barriers to online learning Besides that, the core element in online learning is technology, which is very expensive for learners; therefore, this factor is considered one of the significant economic barriers

Therefore, our proposed hypothesis is:

H2: Economic barrier has a positive impact on Difficulty in online classes

2.3.3: Interaction barrier:

Interaction plays an important role in online learning Thanks to interaction, students are stimulated in learning, leading to great improvement in their learning and their abilities in joining other online classes However, some learners have difficulty communicating in class, so they feel no connectivity and feelings with their lecturers and lessons The differences between online and offline interaction become a concern and a barrier for the learners with this learning method

Therefore, our proposed hypothesis is:

H3: Interaction barrier has a positive impact on Difficulty in online classes

2.3.4: Environmental barrier:

With the importance of studying online, a large number of students have difficulty in their learning space Most of the students study at their home but with families not having their private learning space, it is difficult for them to have an ideal place to

10 study The effect of the place, noise, surrounding, etc also has a significant impact on student performance

Therefore, our proposed hypothesis is:

H4: Environmental barrier has a positive impact on Difficulty in online classes 2.3.5: Psychological barrier:

Learners often feel worried, depressed, and embarrassed and really want to receive a quick reply from lecturers about the lessons, exercises, and responsibilities of online classes The lack of motivation when studying online, and the lack of confidence in their capacity and skills in technology are factors leading to the psychological barrier

of learners when joining online classes

Therefore, our proposed hypothesis is:

H5: Psychological barrier has a positive impact on Difficulty in online classes

CHAPTER 3: THE METHODOLOGY

To analyze the factors that cause difficulty to university students in online learning, our group has separated it into five elements for better understanding: Technological barrier, Economic barrier, Social interaction barrier, Environmental barrier, and Psychological barrier

3.1 Qualitative research

After researching and discussing, our group proposed a Likert and a measurement scale for the previously given model We then referenced our classmates as well as reported to the instructor on the class’s sheet for approval to make suitable adjustments

to our model After making the necessary changes, we proposed our final model 3.2 Quantitative research

Our group primarily used 2 sampling methods below:

- Convenience sampling: We used the Google Forms platform to survey the difficulty

in online classes by sending the question form to social media pages, group chats, and studying groups where there are many university students

- Snowball sampling (Chain-referral sampling): We sent out the question form to our close friends in other universities as well as our classmates at UEH and asked them to continue passing the form to their friends

3.2.4 Sample description

We received a total of 127 samples, the respondents are from 32 different universities, however, UEH students are the majority due to the question form mainly being passed within the university Due to this, a large number of the participants’ majors are

Economics — Business — Management More than half of the answers are from first- year university students, this can be explained by the same reason stated above, where the form is mainly passed to friends and classmates of the group

3.3 Data analysis method:

We uploaded the answers from the Google form into SPSS 25.0 for analysis and reliability testing

3.3.1 Cronbach’s Alpha reliability test

3.3.3 Pearson Correlation

When the reliability and factor analysis tests were done, we continued on with the Pearson Correlation analysis We created new representative variables of the qualified factors from EFA, then ran the analysis to explore the relationship between the independent variables and the dependent variable, as well as to check for possible collinearity scenarios

3.3.4 Multivariable regression

After exploring the relationship between independent variables and dependent variables, we continued with the Multivariable regression analysis to confirm those relationships Through the result, we wanted to check for the suitability of the model

as well as the normal distribution of residuals

3.4 Measurement scale of variables

Number Measurement scale Source of measurement sca

Adapt (with modification)

A Technological barrier scales from previous

C Social interaction barrier

Adapt (with modification) scales from previous researches

| have many opportunities to prov

42 myself in the class

My lectures are one-way only ani

15

My learning space is cramped,

Relying on devices and the intern

17 makes my lessons inflexible

48 Notifications from devices make me distracted

E Psychological barrier

Adapt (with modification) scales from previous researches

| have difficulty focusing in class

19

| feel unmotivated to learn and

20 interact with my lessons

| often procrastinate with my worl

22 | feel anxious and stressed witho

interacting with my friends

17

CHAPTER 4: RESEARCH RESULT

4.1 Descriptive statistics of survey sample

We conducted a survey asking university students on the online questionnaire platform Google Forms After the survey ended, we examined the data and recorded 127 samples, the data then went through SPSS 25.0 for analysis Our group’s results are

displayed in the following tables:

4.1.1 General information of participants

Table 4.1: General information

Count] Column N %

Economics — Business — Management is the group of majors that account for the most compared to others This is due to the survey mainly being sent within UEH

Engineering — Technology — Information has 7 answers, accounting for 5.5%, Social sciences — humanities follow with 3.1% Other majors have 23 answers, which is

18.1%

Because the survey was mostly sent to K48 students of UEH and their friends, as well

as from other universities, Year 1 has the highest number of answers, accounting for 51.2% Year 2 and Year 4 have 16.5% and 26% respectively, while Year 3 accounts for the least answers with 6.3%

In terms of gender, Females take up the majority of the answers with 82 votes (64.6%), this makes sense for the gender distribution of UEH, as well as other economic majors since they account for the greatest number of answers Male has 45 answers, which is

35.4%

4.1.2 Learning platform usage

Table 4.2: Platforms used for online learning

20

21

Among the devices used by university students, Laptop/PC is the most chosen option

with 77 answers in “Very often”, accounting for 60.6% and 38 answers (29.9%) in

“Often” In contrast, the use of tablets and TVs for online classes is much less

frequent, with 71 respondents (55.9%) reported to have never used a tablet for online learning and 98 answers (77.2%) in “Never” for TV usage Mobile phone has 48

answers (37.8%) in “Very often” and 33 (26%) in “Often”’

22 4.1.4 Learning location

Table 4.4: Learning locations

4.2.1 Reliability test with Cronbach’s Alpha Table 4.5: Results of evaluating reliability of “Technological barrier” scale

23

| usually have sound 11.69 14.281 597 817| Suitable

The user interface in 12.30 13.005 12 785) Suitable

| lack the skills to use 12.63 13.267 603 818] Suitable

The Cronbach’s Alpha result of the “Technological barrier” scale is 0.838 The

Corrected Item-Total Correlation values of all the observed variables of the scale are above 0.4 Also, none of the Cronbach’s Alpha if Item Deleted value is greater than

0.871 Therefore, all the observed variables of this scale are qualified to be used for the factor analysis

Table 4.6: Results of evaluating reliability of “Economic barrier” scale

24

“Economic barrier” Scale: Cronbach’s Alpha = 0.871

Online courses’ fees 9.57 9.708 675 853) _

The Cronbach’s Alpha result of the “Economic barrier” scale is 0.871 The Corrected

Item-Total Correlation values of all the observed variables of the scale are above 0.4 Also, none of the Cronbach’s Alpha if Item Deleted value is greater than 0.871

Therefore, all the observed variables of this scale are qualified to be used for the factor analysis

Table 4.7: Results of evaluating reliability of “Social interaction barrier” scale (1%

time)

25

Deleted | Correlation| Deleted

“Social interaction barrier” Scale: Cronbach’s Alpha = 0.61

| value the 11.11 5.099 502 460

| have many 11.59 4.752 462 481) _

myself in the class

My lectures are one- 11.56 6.010 203 679 ;

except for “My lectures are one-way only and lack contributions” with a value of

0.203, indicating that it has a weak link to other observed variables of the scale Therefore, we eliminated the unsuitable observed variable and reran the Cronbach’s Alpha test, and received the results:

Table 4.8: Results of evaluating reliability of “Social interaction barrier” scale

(2"4 time)

26

Table 4.9: Results of evaluating reliability of “Social interaction barrier” scale

(3 time)

27

The Cronbach’s Alpha result of the “Social interaction barrier” scale is 0.731 The

Corrected Item-Total Correlation values of all the observed variables of the scale are above 0.4 Therefore, all the observed variables of this scale are qualified to be used for the factor analysis

Table 4.10: Results of evaluating reliability of “Environmental barrier” scale

Variables

Scale Mean

if Item Deleted

Scale

Variance if Item Deleted

Corrected ltem- Total Correlation

Cronbach's Alpha if Item Deleted Conclusion

28

“Environmental barrier” Scale: Cronbach’s Alpha = 0.816

| don't have privacy 14.46 12.632 637 70)

Suitable

variable roommates

My learning space is 14.76 12.420 626 S73)

Suitable cramped,

The Cronbach’s Alpha result of the “Environmental barrier” scale is 0.816 The

Corrected Item-Total Correlation values of all the observed variables of the scale are above 0.4 Also, none of the Cronbach’s Alpha if Item Deleted value is greater than

0.816 Therefore, all the observed variables of this scale are qualified to be used for the factor analysis

Table 4.11: Results of evaluating reliability of “Pychological barrier” scale

29

“Psychological barrier” Scale: Cronbach’s Alpha = 0.800

| have difficulty 14.35 12.167 593 763) Suitable

| feel unmotivated to 14.46 11.806 587 #82

Suitable learn and interact

| feel anxious and 14.84 11.277 500 791

The Cronbach’s Alpha result of the “Psychological barrier” scale is 0.8 The Corrected Item-Total Correlation values of all the observed variables of the scale are above 0.4 Also, none of the Cronbach’s Alpha if Item Deleted value is greater than 0.8

Therefore, all the observed variables of this scale are qualified to be used for the factor analysis

30 Table 4.12: Results of evaluating reliability of “Difficulty in online classes” scale

Suitable

causes me many

variable problems

The Cronbach’s Alpha result of the “Diffuculty in online classes” scale is 0.886 The Corrected Item-Total Correlation values of all the observed variables of the scale are above 0.4 Also, none of the Cronbach’s Alpha if Item Deleted value is greater than 0.886 Therefore, all the observed variables of this scale are qualified to be used for the factor analysis

4.2.2 Validity check of measurement with factor analysis — EFA 4.2.2.1 Exploratory analysis for independent variable scales

After analyzing the Cronbach’s Alpha reliability coefficient, the scales were further

evaluated by the exploratory factor analysis (EFA) The results of Cronbach’s Alpha

31 show that there are 21 observed variables of 5 components measuring the difficulty of university students in online classes that are qualified

We used the extraction method of Principle Component Analysis with Promax rotation

to analyze factors for the 21 observed variables The requirement of the exploratory factor analysis is the KMO coefficient (Kaiser - Meyer — Olkin) is larger than 0.5 and the Barlett’s Test of Sphericity has the sig value smaller than 0.05 in order to show the validity and correlation of the observed variables

After the first analysis, the received results are: KMO = 0.833 > 0.5; Barlett’s Test of Sphericity Sig = 0.000 < 0.05; Total Variance Explained = 67.018% > 50%; and the Eigenvalues of all the 5 components are higher than 1 All the factor loading

coefficients of the observed variables are higher than 0.4 From this, we can conclude that the data is appropriate and the observed variables are correlated Therefore, the requirements of the EAF are satisfied

Table 4.13: Results of KMO and Bartlett Tests of Sphericity (15 time)

Kaiser-Meyer-Olkin Measure of Sampling 833

33

| have difficulty focusing in class 834

| feel unmotivated to learn and interact with f64

lessons

| often procrastinate with my work and tasksl 782

| feel anxious and stressed without interactir 588

34

The user interface in unfriendly t

me

138

I don’t have enough equipments

for learning

.607

| lack the skills to use learning

software

.800

Online courses’ fees cause

difficulty for me

134

| have difficulty paying for the

learning equipments

815

| have difficulty maintaining my

internet plan

.870

Service fees of online classes ca

much of my budget

.898

| value the interactions between

professors and students

173

Interacting with classmates is

necessary to me

905

| don't have privacy from my

35

demotivating

Relying on devies and the intern 820

makes my lessons inflexible

| feel unmotivated to learn and 730

interact with my lessons

| often procrastinate with my wor 827

and tasks

| feel anxious and stress without 669

interating with my friends

| feel more laid-back and 143

unserious without being monitoreé

After the second analysis, the received results are: KMO = 0.837 > 0.5; Barlett’s Test

of Sphericity Sig = 0.000 < 0.05; Total Variance Explained = 67.361% > 50%; and the Eigenvalues of all the 5 components are higher than 1 All the factor loading coefficients of the observed variables are higher than 0.4 From this, we can conclude that the data is appropriate and the observed variables are correlated Therefore, the requirements of the EAF are satisfied, and the observed variables were qualified to be used for the next correlation analysis

After running the EFA twice for independent variables, all variables except “I am

disturbed by traffic noises” satisfied the requirements

36 4.2.2.2 Eploratory factor analysis for dependent variable scales

Table 4.15: Results of KMO and Bartlett Tests of Sphericity of dependent

After the analysis, the received results are: KMO = 0.745 > 0.5; Barlett’s Test of

Sphericity Sig = 0.000 < 0.05 From this, we can conclude that the data is appropriate and the observed variables are correlated

Table 4.16: Results of EFA of dependent variables

Component Observed variables

1

| genuinely have difficulty learning online 892 Online learning is more challenging than | 904 expect

Online learning causes me many problems 813

The factor analysis was done with the extraction method of Principal Component Analysis and Promax rotation For the analysis there are 3 observed variables of 1 component, with the results of: Cumulative Variance Explained = 81.553% > 50%; Eigenvalue coefficient is 2.447 >1; all the factor loading coefficients of the observed

37 variables are higher than 0.4 Therefore, the requirements of the EAF are satisfied, and the observed variables were qualified to be used for the next correlation analysis 4.2.3 Pearson correlation

Table 4.17: Pearson correlation table

statistical meaning We can conclude that there is a positive correlation between Difficulty in online classes and Economic barrier