Students’ Acceptance of Mobile Application based-Ofﬁce English

Learning Material for University Students

Sri Wahyuni and Fauzul Etﬁta

English Language Education, Universitas Islam Riau, Pekanbaru, Indonesia

Keywords:

Acceptance, Ofﬁce English, Learning Material, ENFORCE, Mobile Application

Abstract:

Learning material is one of the strategic tools that can be used to achieve the learning goal. However, the

conventional learning material is still employed such as a book, printed module, etc. Responding to this issue,

the researchers have developed mobile application-based ofﬁce English learning material. The application was

named ENFORCE. Hence, this research aimed to analyse the correlation among factors and to ﬁgure out the

best factor that inﬂuenced students’ acceptance of the mobile application as a learning material for university

students. In this research, 105 students had been asked to use a supportive mobile application-based learning

material during the learning process. Further, at the end of the semester, online questionnaires were distributed

to obtain the data. In analysing the data, the correlation and regression analysis were carried out through SPSS.

The results revealed that the correlation among the factor was correlated signiﬁcantly. It was emphasized by

the signiﬁcant value which was greater than 0.01. Additionally, the result of regression analysis showed that

signiﬁcant value which was .000 that greater than 0.005. It can be declared that the best factor that inﬂuenced

students’ acceptance of mobile application-based ofﬁce English learning material for university students was

ease of use.

1 INTRODUCTION

The development of the mobile application has

been utilized for educational issues (Domingo and

Gargant

e, 2016). Speciﬁcally for language learning,

there are many mobile applications designed for

supporting language learning and providing learning

material (Hao et al., 2019). The movement of mobile

objectives has opened opportunities an alternative

media in providing an interactive learning material

(Akpan, 2017; Al-Hunaiyyan et al., 2018). Besides,

it also becomes challenges for lecturers and students

to maximize the mobile application-based learning

(Chavoshi and Hamidi, 2019).

As conﬁrmed by several studies that have

announced the advantages of language learning

through mobile applications (Pilar et al., 2013;

Shanmugapriya and Tamilarasi, 2013; Wu, 2015). In

term of the students’ acceptance of learning mobile

also showed positive attitude (Al-Emran et al., 2018;

Bozdo

gan, 2015; Dashti and Aldashti, 2015). In this

research, the students’ acceptance was determined

based on the internal factors that inﬂuenced the

students’ behavioural intention of use mobile-based

learning material such as usefulness perception and

ease of use perception (Davis, 1989).

Additionally, external factors were also

considered as affected aspect in acceptance namely

self-efﬁcacy and compatibility (Venkatesh and Davis,

2000). In consequence, the current research aimed

to reveal the correlation and the best-affecting factor

on students’ acceptance of mobile application-based

ofﬁce English learning material at the end of the

semester after using the application.

2 RESEARCH METHOD

The respondents of this research were 105 private

university students who had learned English for ofﬁce

through mobile application namely ENFORCE. The

students were asked to use ENFORCE as a supportive

learning material during 14 weeks of the effective

learning time allocation. To have the app, the

installation through play store was required for every

student at the ﬁrst week. In its implementation, the

semester learning plan was modiﬁed for applying this

application. Further, the quantitative method was

used through the survey to achieve the purpose of this

study. The 20 statements of the questionnaire were

Wahyuni, S. and Etﬁta, F.

Students’ Acceptance of Mobile Application based-Ofﬁce English Learning Material for University Students.

DOI: 10.5220/0009058700520056

In Proceedings of the Second International Conference on Social, Economy, Education and Humanity (ICoSEEH 2019) - Sustainable Development in Developing Country for Facing Industrial

Revolution 4.0, pages 52-56

ISBN: 978-989-758-464-0

adapted from (Davis, 1989); (Venkatesh and Davis,

2000); and (Chung et al., 2015) employed to collect

the data at the end of semester. The google form was

utilized to address the questionnaire to the students.

After collecting the data, SPSS was used to compute

and analyse quantitatively the data. Additionally, the

correlation analysis was carried out to ﬁgure out the

correlation among factors and regression analysis was

conducted to know the best-affecting factor.

3 RESULTS AND DISCUSSION

In this part, the researchers discussed the results and

discussion in some sub-section. To elaborate on the

research results obviously, the researcher divided the

sub-section into descriptive statistics, the result of

correlation among factors, and the result of regression

analysis.

3.1 Descriptive Statistics of Each Factor

The descriptive statistics revealed that ease of use

showed the greatest mean score which was 16.45. The

behavioural intention of use, usefulness, self-efﬁcacy,

and compatibility were 15.96, 15.84, 14.75, and 14.4

respectively. The criteria for each factor are based on

the range of average scores with levels from very high

to very low. The descriptive statistics of each factor

can be seen in table 1-5.

Table 1: Descriptive statistics of ease of use

Items SD Mean

studying English for ofﬁce through

ENFORCE App is easy for me

.994 4.05

studying English for ofﬁce through

ENFORCE App saves time

.814 4.17

studying English for ofﬁce through

ENFORCE App is convenient

.872 3.99

studying English for ofﬁce through

ENFORCE App is easy to use

.861 4.24

In term of ease of use perception, students trusted

that studying ofﬁce English class by using ENFORCE

application was easy to operate it. The evidence

of students’ perceived of ease of use can be seen

from the means score which were 4.24 and 4.05.

As well, it can save their time learning through

that application. Besides, mobile application-based

ofﬁce learning material was appropriate to use in

learning English for ofﬁce. The evidence of students’

perceived of convenience and saving the time can be

seen from the means score which were 4.17 and 3.99.

It was evidenced from the mean score that was at a

high level and the students’ perceived of ease of use

was positive (see table 1).

Table 2: Descriptive statistics of behavioural intention of

use

Items SD Mean

I am ready using ENFORCE

App to learn ofﬁce English

.898 4.10

I will continue using ENFORCE

App to learn ofﬁce English in the future

.950 3.96

Overall, I will learn ofﬁce English

through ENFORCE App

.946 3.90

I will recommend others learning ofﬁce

English through ENFORCE App

935 3.99

In term of behavioural intention of use, students

intended to use ENFORCE application to learn ofﬁce

English. It was evidenced by mean score which was

4.10. As well, they would like to promote that app for

other ofﬁce learners. It was also evidenced by mean

score which was 3.99. Overall, It can be proven from

means scores that were at a high level and students’

intention were positive (see table 2).

Table 3: Descriptive statistics of usefulness

Items SD mean

studying English for ofﬁce

through ENFORCE App is

not limited by time and place

1.182 3.67

studying English for ofﬁce

through ENFORCE App can

assist me to access the

information I need

.895 4.08

studying English for ofﬁce through

ENFORCE App improve my

learning effective

.866 3.98

studying English for ofﬁce through

ENFORCE App provides serviceable

guidance in running tasks

.870 4.11

In term of usefulness, students perceived that

using learning ofﬁce English through ENFORCE

Application can be done anywhere and anytime.

Besides, they believed that application was a very

effective learning resource during having to learn

English for ofﬁce. These statements can be proven by

the means score which were 3.67 and 4.08. Besides,

students perceived that this app was effective to

employ as a supportive learning material especially

for running the tasks. It can be proven by the means

score which were 3.98 and 4.11. Additionally, the

mean score was at a moderate level and the students’

perceived of usefulness was positive (see table 3).

In term of self-efﬁcacy, students believed that

they can solve the obstacles faced during the learning

process by using ENFORCE application. It can be

seen from the means score which were 3.60, 3.63,

Students’ Acceptance of Mobile Application based-Ofﬁce English Learning Material for University Students

Table 4: Descriptive statistics of self-efﬁcacy

Items SD mean

I can ﬁnish learning ofﬁce English

tasks through ENFORCE App if

there is no information I got from

people around me

.957 3.67

I can ﬁnish learning ofﬁce English

tasks through ENFORCE App if

someone had helped me get started

1.025 3.60

I can solve the obstacles faced when

I used ENFORCE App to study ofﬁce

English

1.058 3.63

I can ﬁnish learning ofﬁce English

assignments through ENFORCE

App, no matter what the difﬁculties

.903 3.86

3.67, and 3.86 respectively. Overall, it can be said that

in term of perceived of self-efﬁcacy was responded

positively (see table 4).

Table 5: Descriptive statistics of compatibility

Items SD mean

studying English for ofﬁce

through ENFORCE App, I

don’t have to substitute

anything I recently do

1.090 3.34

studying English for ofﬁce

through ENFORCE App

does not need changes

signiﬁcantly in my existing

work custom

1.010 3.48

studying English for ofﬁce

through ENFORCE App is

similar to using other

application that I have

applied in the past

1.027 3.57

studying English for ofﬁce

through ENFORCE App

can strengthen from computer

.976 3.72

In term of compatibility, students perceived that

using ENFORCE application was related to their

previous impression while using another application.

It also conﬁrmed by the means score which were

3.57 and 3.48. They also believed that using that

application was useful as same as another application

that they used before. It also strengthened by the

mean score which was 3.34. As well, students

perceived that this app was easy because it can be

used through computer. This statement was supported

by the mean score which was 3.72 (see table 5). It

can be said that in term of compatibility that students

positively responded.

3.2 The Correlation among the Factors

To see the correlation among the students’ acceptance

factors of ENFORCE application as a learning

resource, correlation analysis was conducted (see

table 6).

Table 6: The correlation among the factors

factors

Useful

ness

Ease

of use

Self-

Efﬁcacy

Compati

bility

Intention

Useful

ness

.778**

.000

.569**

.000

.550**

.000

.666**

.000

Ease

of use

.778**

.000

.514**

.000

.416**

.000

.704**

.000

Self-

Efﬁcacy

.569**

.000

.514**

.000

.704**

.000

.591**

.000

Compati

bility

550**

.000

.416**

.000

.704**

.000

.538**

.000

Intention

.666**

.000

.704**

.000

.591**

.000

.538**

.000

**. Correlation is signiﬁcant at the 0.01 level (2-tailed).

As could be seen in table 6, all of the factors

were correlated to each other signiﬁcantly. In term

of the perception of usefulness, this factor had a

signiﬁcant correlation with ease of use perception

calculated

=.778**> r

table

=.176), behavioural

intention of use (r

calculated

=.666**> r

table

=.176),

self-efﬁcacy r

calculated

=.569**> r

table

=.176), and

compatibility (r

calculated

=.550**> r

table

= .176)

respectively.

In term of perceived ease of use, it also had

correlated signiﬁcantly with perceived usefulness

calculated

=.778**> r

table

=.176), behavioural

intention of use (r

calculated

=.704**> r

table

=.176),

self-efﬁcacy (r

calculated

=.514**> r

table

= .176),

and compatibility (r

calculated

=.416**> r

table

.176) sequentially. Further, self-efﬁcacy

had signiﬁcant correlation with compatibility

calculated

=.704**> r

table

=.176), behavioural

intention of use (r

calculated

=.591**> r

table

= .176),

usefulness (r

calculated

=.569**> r

table

= .176), and

ease of use (r

calculated

=.514**> r

table

= .176). Next

factor, compatibility had signiﬁcant correlation with

others factor as well.

The most positive correlation was compatibility

with self-efﬁcacy (r

calculated

=.704**> r

table

=.176)

and followed by perceived usefulness

calculated

=.550**> r

table

=.176), behavioural

intention of use (r

calculated

=.538**> r

table

= .176),

and ease of use (r

calculated

=.418**> r

table

=.176).

Regard to the intention of use, ease of use perception

was the most positive correlated factor. It can be seen

from the r

calculated

=.704**. Perceived usefulness

calculated

=.666**), self-efﬁcacy (r

calculated

=.591**),

and compatibility (r

calculated

=.538**) were correlated

with the intensive attitude of use. Overall, Correlation

ICoSEEH 2019 - The Second International Conference on Social, Economy, Education, and Humanity

analysis revealed that the intensive attitude to use

the application as a learning resource had a positive

correlation with the acceptance factors (p < 0.01).

This result was conﬁrmed by previous studies

that mentioned usefulness perception and ease of use

perception had correlation to behavioural intention to

use an application in learning as a resource during

the learning process. Wahyuni & Etﬁta (2019) dan

(Weng et al., 2018) stated that perceived usefulness

and perceived ease of use inﬂuenced the attitude in

using an application as a material. (Van De Bogart

and Wichadee, 2015); (Elkaseh et al., 2016); and

(Wahyuni, 2018a) also revealed that the intention of

using an application mobile learning was the effect of

two internal factors such as ease of use perception and

usefulness perception of mobile application-based

learning material. The effectiveness of its mobile

application-based learning material was in the context

of usefulness and ease of use perception affected the

attitude use it intensively (Kitchakarn, 2016). To sum

up the research ﬁnding based on the analysis and

supported by other studies, perceived usefulness and

perceived ease of use had a correlation in inﬂuencing

the intensive behaviour on using an additional mobile

application-based learning material.

Further, the external factor namely self-efﬁcacy

and compatibly that also had a correlation to

intention of use a mobile application in learning also

emphasized by several related researchers. (Chen,

2014); (Chung et al., 2015); (Alshammari et al.,

2016) strengthened that these external factors had a

signiﬁcant correlation in effecting the intention of

using the mobile application in learning. It can be

inferred that self-efﬁcacy and compatibility should

be considered in designing mobile application-based

learning material.

3.3 The Analysis Regression Result

In ﬁguring out the best-affected factor of students’

acceptance, regression analysis was carried out. The

result was presented in table 7.

Table 7: The result of regression analysis

Factors t Sig.

Compatibility 1.644 .103 not signiﬁcant

Usefulness 1.205 .231 not signiﬁcant

Self-efﬁcacy 1.852 .067 not signiﬁcant

Ease of use 4.270 .000 signiﬁcant

The result revealed that the best factor that

inﬂuenced intention in using ENFORCE application

as a supportive learning resource was ease of use

intentionally. It can be proven from the signiﬁcant

value which was .000<0.005. Additionally, the result

was conﬁrmed that the value of t

calculated

was greater

that t

table

which was 1.6602 < 4.270 (see table 7).

As emphasized by (Abu-Al-Aish and Love, 2013);

(Davis, 1989); and (Wahyuni, 2018b), the perception

of ease of use can give positive impression on using

the learning based mobile application intentionally.

Additionally, mobile language learning meets the

students’ needs, following the digital era, and creating

autonomous learning (Shroff and Keyes, 2017).

On contrary to the research ﬁnding conducted by

(Alqahtani and Mohammad, 2015), they stated that

the most affecting factor was perceived usefulness to

behavioural intention in using the mobile application.

It could be inferred that the most considerable factor

of students in using ENFORCE application as an

additional learning material for university students

was the ease of use.

4 CONCLUSIONS

This study analysed the correlation among students’

acceptance factors and which one the best factor that

affected students’ acceptance of behavioural intention

in using ENFORCE application. The result showed

that each factor had a positive correlation to the

behavioural intention of use the mobile application.

Furthermore, the most affected factor to intention of

use was the sense of ease of use. Speciﬁcally, it

could be inferred that students believed that utilizing

ENFORCE application was easy and useful as an

alternative media for providing learning material.

It is very crucial for lecturer to design

implementation plan mobile assisted language

learning model. As well, the lecturers should

cooperate with practitioners or designer’s mobile

application to develop learning material based mobile

to provide interactive learning.

In conclusion, the research ﬁndings indicated

that the university should expand the strategic plan

and offer guideline reﬂecting in students’ acceptance

of mobile learning in order to accommodate all

on reﬂecting factors for sustainable development of

mobile language learning. The result and ﬁndings of

this study can contribute which factors can be offered

for modelling to run plan of mobile assisted language

learning in the university.

ACKNOWLEDGEMENTS

The researchers would like to deliver thank to the

willingness and participating of the students in this

Students’ Acceptance of Mobile Application based-Ofﬁce English Learning Material for University Students

study.

REFERENCES

Abu-Al-Aish, A. and Love, S. (2013). Factors inﬂuencing

students’ acceptance of m-learning: An investigation

in higher education. The International Review of

Research in Open and Distributed Learning, 14(5).

Akpan, V. I. (2017). Cell phones as effective learning

resource. Journal of Education, Society and

Behavioural Science, pages 1–8.

Al-Emran, M., Mezhuyev, V., and Kamaludin, A. (2018).

Technology acceptance model in m-learning context:

A systematic review. Computers & Education,

125:389–412.

Al-Hunaiyyan, A., Alhajri, R. A., and Al-Sharhan, S.

(2018). Perceptions and challenges of mobile learning

in kuwait. Journal of King Saud University-Computer

and Information Sciences, 30(2):279–289.

Alqahtani, M. and Mohammad, H. (2015). Mobile

applications’ impact on student performance and

satisfaction. Turkish Online Journal of Educational

Technology-TOJET, 14(4):102–112.

Alshammari, S. H., Ali, M. B., and Rosli, M. S. (2016).

The inﬂuences of technical support, self efﬁcacy and

instructional design on the usage and acceptance of

lms: A comprehensive review. Turkish Online Journal

of Educational Technology-TOJET, 15(2):116–125.

Bozdo

gan, D. (2015). Mall revisited: Current trends

and pedagogical implications. Procedia-Social and

Behavioral Sciences, 195:932–939.

Chavoshi, A. and Hamidi, H. (2019). Social, individual,

technological and pedagogical factors inﬂuencing

mobile learning acceptance in higher education:

A case from iran. Telematics and Informatics,

38:133–165.

Chen, Y.-L. (2014). A study on student self-efﬁcacy

and technology acceptance model within an online

task-based learning environment. Journal of

Computers, 9(1):34–43.

Chung, H.-H., Chen, S.-C., and Kuo, M.-H. (2015). A

study of eﬂ college students’ acceptance of mobile

learning. Procedia-Social and Behavioral Sciences,

176:333–339.

Dashti, F. A. and Aldashti, A. A. (2015). Eﬂ

college students’ attitudes towards mobile learning.

International Education Studies, 8(8):13–20.

Davis, F. D. (1989). Perceived usefulness, perceived ease of

use, and user acceptance of information technology.

MIS quarterly, pages 319–340.

Domingo, M. G. and Gargant

e, A. B. (2016). Exploring the

use of educational technology in primary education:

Teachers’ perception of mobile technology learning

impacts and applications’ use in the classroom.

Computers in Human Behavior, 56:21–28.

Elkaseh, A. M., Wong, K. W., and Fung, C. C. (2016).

Perceived ease of use and perceived usefulness of

social media for e-learning in libyan higher education:

A structural equation modeling analysis. International

Journal of Information and Education Technology,

6(3):192.

Hao, Y., Lee, K. S., Chen, S.-T., and Sim, S. C.

(2019). An evaluative study of a mobile application

for middle school students struggling with english

vocabulary learning. Computers in Human Behavior,

95:208–216.

Kitchakarn, O. (2016). How students perceived social

media as a learning tool in enhancing their language

learning performance. Turkish Online Journal of

Educational Technology-TOJET, 15(4):53–60.

Pilar, R.-A., Jorge, A., and Cristina, C. (2013). The

use of current mobile learning applications in

eﬂ. Procedia-Social and Behavioral Sciences,

103:1189–1196.

Shanmugapriya, M. and Tamilarasi, A. (2013). Design

and development of mobile-assisted language learning

(mall) application for english language using android

push notiﬁcation services. International Journal

of Research in Computer and Communication

Technology, 2(6):329–338.

Shroff, R. H. and Keyes, C. J. (2017). A proposed

framework to understand the intrinsic motivation

factors on university students’ behavioral intention

to use a mobile application for learning. Journal

of Information Technology Education: Research,

16:143–168.

Van De Bogart, W. and Wichadee, S. (2015). Exploring

students’ intention to use line for academic purposes

based on technology acceptance model. The

International Review of Research in Open and

Distributed Learning, 16(3).

Venkatesh, V. and Davis, F. D. (2000). A theoretical

extension of the technology acceptance model: Four

longitudinal ﬁeld studies. Management science,

46(2):186–204.

Wahyuni, S. (2018a). Students’ perception of using an

android smartphone application as a supplementary

learning resource. Asia Proceedings of Social

Sciences, 2(4):115–119.

Wahyuni, S. (2018b). Students’perspectives on using

telegram messenger as a learning media. ELT-Lectura,

5(1):31–37.

Weng, F., Yang, R.-J., Ho, H.-J., and Su, H.-M. (2018). A

tam-based study of the attitude towards use intention

of multimedia among school teachers. Applied System

Innovation, 1(3):36.

Wu, Q. (2015). Designing a smartphone app to teach

english (l2) vocabulary. Computers & Education,

85:170–179.

ICoSEEH 2019 - The Second International Conference on Social, Economy, Education, and Humanity