issn: 2456-9992 predictive drivers of students‟ … servqual, the prominent service quality...

International Journal of Advanced Research and Publications ISSN: 2456-9992

Volume 1 Issue 4, Oct 2017 www.ijarp.org

200

Predictive Drivers Of Students‟ Satisfaction In Open

Distance Learning In Sri Lanka

MJR Perera, Nalin Abeysekera, S.R.S.N. Sudasinghe, Isuri Roche Dharmaratne

Management and Science University of Malaysia, Graduate School of Management (GSM), University Drive, Seksyen 13,40100, Shah

Alam Selangor, Malaysia, PH-00940718258172

[email protected]

Open University of Sri Lanka, Department of Management Studies, Nawala, Nugegoda,Sri Lanka,PH-0094773028690

[email protected]

Sri Lanka Institute of Development Administration, School of Postgraduate Studies, 28/10, MalalasekaraMawatha, Colombo 7, Sri Lanka.

PH-0094712322314

[email protected]

Management and Science University, Malaysia, Colombo Learning Centre, 300,Colombo 3, Sri Lanka , PH-0094773822946

[email protected]

Abstract: The predictive drivers of students‟ satisfaction in Open Distance Learning (ODL) has become an important and competitive

criterion in service quality perspectives in higher education (HE). The customer service quality act as an antecedent of customer satisfaction,

and their relationship has beenempirically proved by many of the researchers following literature based onmarketing.Distance Education

(DE) is introduced as a supplementary method in the higher education system for the disadvantaged, and for those who have missed

entering the traditional university system of higher education due to restrictions on the number of students allowed for university admission.

The DE system removed the barriers of minimum qualifications for the courses giving moreopportunity to the public to obtain higher

educational qualifications from recognised universities operating under the Open Distance Learning (ODL) concept. The ODL system

developed rapidly with the increase in number of students, but does not reflect the number of students passing out as graduates. Just as in,

„consumer behavior‟ in marketing literature, most of the researchers have addressed the relationships between students‟ perceived service

quality, satisfaction, students‟ persistence and attrition. The development of information technology influences ODL in a positive way by

giving more interaction with web based on-line and e-learning systems. The problem of student dropouts or students‟ attrition encountered

not in the early DE environment days,even in the on-line courses have been observed as high. Many research studies have disclosed the

reasons for this situation and recommendations made to increase and assess the quality of the programmes. This studywill examine the

relationships between the independent variables of Reliability, Cost &Time and Website Content and dependent variable of Students‟

Satisfaction. This study was conducted in the six main regional centers of the OUSL spread across the island. The sample size used was 760

undergraduate students who have more than,or equaled at least one year‟s exposure with the ODL system. The statistical analysis revealed

all the independent variables were significantly related with the Students‟ Satisfaction.

Keywords: Distance Education, Open Distance Learning, Satisfaction, Service Quality

1. Introduction

Education is a significant factor to enlighten the life of the

nation (Susanti, Sule, & Sutisna, 2015). Distance

Education (DE) has originated as an alternative to

traditional education (Kutluk & Gulmez, 2012 ).DE

isdefined as,“an educational process and system in

which all or a significant proportion of the teaching is

carried out by someone or something removed in space

and time from the learner. Distance education requires

structured planning, well-designed courses, special

instructional techniques and methods of

communication by electronic and other technology, as

well as specific organizational and administrative

arrangements” (Higher Education for the Twenty First

Century (HETC) Project Ministry of Higher Education

and Research Sri Lanka & University Grants Commission,

April 2015). In recent times, a growth of distance

education could bea more flexible way (Butcher & Rose-

Adams, 2015) to acquire the higher education deprived of

time and space constraintswhich is restricted with a face to

face learning system.The DE is more economically

beneficial and desirable especially with the employed

students (Kutluk & Gulmez, 2012 ).DE is expanding and

(Khan & Iqbal, 2016) the rapid growth of distance

learning hasresulted in web based e-learning or on-line

learning. When the studentsare converted from the

traditional face-to-face to DE programs, changes should

be made to engage the learners proficiently (Khan &

Iqbal, 2016). To study the performanceof the students

with the unfamiliar new environment it is important to

study student satisfaction with distance learning programs

and how these relate to their academic achievement.

(Khan & Iqbal, 2016). The student persistence and

completion rates have faced problems with student

attrition or dropouts in DE (Simpson, Does distance

education do more harm than good?, 2010; Simpson, E-

Learning and the Future of Distance Education, 2013;

Simpson, Student Support Service for Success in Open

and Distance Learning, Feb 17, 2016; Tinto, 1975).The

enrollment in online courses is rapidly increasing due to

its flexibility, convenience and easy access but the

attrition rates remain high (Croxton, 2014).Internal,

External, and contextual factors could be influenced

dropout decisions (Croxton, 2014; Lee & Choi, 2011;

Parker, 1999; Park & Choi, 2009). Quality is important in

the input and output of higher education especially in open

and distance learning (Inegbedion & Adeyemi, Cost

indices in open and distance education in Nigerian

universities, 2013).The improvement of the quality of the

output of the educational process and the quality



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indicators must be managed in a systematic way,

(Peterson, Kovel‐Jarboe, & Schwartz, 1997). “The quality

of teaching depends on the quality of teachers in the

system” (Lekamge, 2010, p. 1). The prominent

SERVQUAL instrument with the dimensions of

Assurance, Empathy, Responsiveness, Reliability, and

Tangibilityhas been used in many educational

backgrounds to assess the service quality (SQ) and to find

the significant SQ dimensions and significant

relationships with students„satisfaction which leads to

behavioral intention (Malik, Danish, & Usman, 2010;

Mansori, Vaz, & Ismail, 2014; Pohyae, Romle, Darus,

Saleh, Saleh, & Mohamood, 2016; Stodnick & Rogers,

2008; Sembiring, 2015; Wei & Ramalu, 2011). The

student satisfaction is a multidimensional construct

(Montinaro & Chirico, 2006 ; Parasuraman, Zeithaml, &

Berry, A Conceptual Model of Service Quality and Its

Implications for Future Research, 1985), and four out of

the five constructs of SERVPERF (Cronin & Taylor,

1992), which include: responsiveness, reliability,

assurance and empathy were found to have significant

influence on satisfaction (Noor, Masuod, Said,

Kamaruzaman, & Mustafa, 2016 ). “Customer satisfaction

is a goal and an essential factor in an organization

success” (Khattab & Fraij, 2011). “Importance to conduct

research on students‟ satisfaction with distance learning

because differences in students‟ satisfaction might

influence educational opportunities for learning in a

relevant Web-based environment” (Horvat, Krsmanovic,

& Djuric, 2012, p. 1).Consequently the blended learning

courses which is a mix of face to face and online sessions

introduced as an online learning method would reduce the

cost to the students (Liyanagunawardena, Adams,

Rassool, & Williams, 2014). Universities can attract more

students to apply, if the higher education institutionsfocus

on reducing the cost of fees charged (Yusuf, Ghazali, &

Abdullah, 2017). The importance of the service

provided for students will influence the outcome of the

graduates and “ the output can be generated from the

quality of the lecturers who provide good teaching when

universities provide facilities and services to support the

advancement of knowledge and expertise” (Susanti, Sule,

& Sutisna, 2015, p. 1). Quality is very important as input

and output of higher education especially in an ODL

environment (Inegbedion & Adeyemi, Cost indices in

open and distance education in Nigerian universities,

2013)

1.1 Problem Statement

The OUSL has faced the problem of high attrition or

dropouts in the student population which has resulted in a

low graduation rate (The Open Unviersity of Sri Lanka

Corporate Plan 2011-2016 for Achieving Excellence,

Efficiency and Equity in Open Distance Learning, 2011).

Studies of the OUSL have revealed this situation

(Ariyaratne, Munasinghe, Seneviratne, Rajapaksha, &

Dediwala, 2014; Liyanagama, 2014)and recommended to

implement quality enhanced programmes to recoverfrom

this type of situation. The reliability of the service as a

promised service, the fees or cost structure of the

programmes, the content in the educational websites are

very important as service quality dimensions when

considering the student satisfaction based on the

literature (Ana Horvat, 2012; Hasan, Ilias, Rahman, &

Razak, 2008; Kutluk & Gulmez, 2012 ; Gruber, Fuß,

Voss, & Glaeser-Zikuda, 2010; Inegbedion & Adeyemi,

Cost indices in open and distance education in Nigerian

universities, 2013; Simpson, Student Support Service for

Success in Open and Distance Learning, Feb 17,

2016).This study will be used to analyse the significant

factors which affect students‟ satisfaction to complete the

courses through persistence in ODL in the OUSL.

1.2 The Significance of the study

This study is designed based on the threevariables of,

Reliability, Cost, Time and Website Content, and the

independent variable of Student Satisfaction in ODL in

the OUSL. The results of the analysis given are the

predictable variables and their related significant items.

The University‟s Academic staff, higher management and

policy makers can understand the importance of these

service quality dimensions and how they impact on

student satisfaction. Strategic decisions could be

implemented to fulfill the desired service levels of the

students

2. Literature Review The SERVQUAL, the prominent service quality

instrument was developed by Parasuraman et al (1988)

(Parasuraman, Zeithaml, & Berry., SERVQUAL: A

Multiple-Item Scale for Measuring Consumer Perceptions

of Service Quality, 1988), which consist of five

dimensions namely tangibles, reliability, responsiveness,

assurance and empathy.Reliability defined as,“the ability

to perform the promised service dependably and

accurately” (Parasuraman, Zeithaml, & Berry.,

SERVQUAL: A Multiple-Item Scale for Measuring

Consumer Perceptions of Service Quality, 1988), means

that “the organization delivers on its promises regarding

delivery, service provision, and problem resolution”

(Khattab & Fraij, 2011). In 2012,Mantovani (Mantovani,

2012) has found the significant relationship between

Reliability and Service Qualityin e-learning inODL. In

2013 Shah (Shah, 2013) has studied customer service

quality dimensions which lead to customer satisfaction in

the higher education sector in Pakistan by using

SERVQUAL instrument andshowed that the customer

satisfaction is significantly related to reliability (Shah,

2013).In 2015 Sembiring has examined the students‟

persistence with the Students‟ satisfaction with

SERVQUAL dimensions and found the dimension of

Reliability is siginificant with the students‟ satisfaction

(Sembiring, 2015). Cost can be defined as “an amount that

has to be paid or given up by a person in order to get

something that he/she desired” (Yusuf, Ghazali, &

Abdullah, 2017).In 1997 Joseph and Joseph has examined

students‟ perceptions of service quality in education and

identified seven determinants of service quality including

Cost/Time in New Zealand. He has used an

importance/performance-based approach to evaluate

service quality dimensions in education and Cost/Time

was ranked as the fourth place of the list of factors (Joseph

& Joseph, 1997). In 2004 Rashid & Harun (Rashid &

Harun, 2004) has catagorised 8 key characteristics of

service quality in the ODL in Learners‟ Perspective in

Malaysia including cost/ fees of the courses. The

cost/fees were significant with Ethnic Groups, type of

academic programs and distance between learning centres



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and home.In 2013, Sia (Sia, 2013) and in 2017 Yusuf,

Ghazali, & Abdullah (Yusuf, Ghazali, & Abdullah, 2017)

showed that the cost is very important when “college

choice” decision process.The study was conducted under

the statements of financial aids, available university

scholarships or loans, reasonable charges for the education

and accommodation, and flexible payment schemes. The

students were very much concernedabout full or partial

scholarships which depend on a student‟s results as entry

requirements,and othersnot getting the scholarships

whohave to apply for a bank loan or other bank facilites

(Sia, 2013). In 2017 Yusuf, Ghazali, & Abdullah (Yusuf,

Ghazali, & Abdullah, 2017) had found that there is a

significant relationship between cost and a student‟s

decision in selectingHE institutions in Malaysia.“If the

institution of higher education focuses on reducing the

cost of fee in the university, then it can attract more

students to apply” (Yusuf, Ghazali, & Abdullah, 2017, p.

33). The location of the institute is also considered as a

time factor. This factor was studied as the ideal location of

the university; convenience, accessibility, campus layout

and the attractiveness of the university itself. In 2008

Hasan, Ilias, Rahman, & Razak (Hasan, Ilias, Rahman, &

Razak, 2008) did not find a significant relationship

between Reliability and the student satisfaction in private

higher education institutions in Malaysia.Consequently in

2011 Udo, Bagchi, & Kirs (Udo, Bagchi, & Kirs, Using

SERVQUAL to assess the quality of e-learning

experience, 2011) also used the SERVQUAL intrument to

investigate service quality dimensions in e-learning in

ODL in the USA but did not find it significant with the

dimension of Reliability. The significant relationship

between students‟ satisfaction and Reliablility was

examined and concluded that enhancing the trust in the

students that their institution is very much active in

providing the quality education and learning environment

for their academic development (Malik, Danish, &

Usman, 2010).In 2008 Udo, Bagchi, & Kirs (Udo, Bagchi,

& Kirs, Assessing Web Service Quality Dimensions: The

E- Servperf Approach, 2008) assessed web service

quality dimensions by using E- SERVPERF approach and

Website Content was one of the significant

dimension.Consequently, the findings indicated that web

service quality is asignificant driver of behavioral

intentions, its indirect effect through customer satisfaction

is also equally important. In 2011Udo, Bagchi, & Kirs

(Udo, Bagchi, & Kirs, Using SERVQUAL to assess the

quality of e-learning experience, 2011), have used


experience, in ODL and found Website Content is a

significant dimension with the student‟s perceived

service quality.

3. Research Methodology The research Methodology is mainly dependent on the

conceptual frame work, Research instrument, Sample

frame work, Data collection and it‟s methods. It consists

of three (3) independent variables of service quality

dimensions of, Reliability, Website Content andCost&

Time. The independent variable is the Students‟

Satisfaction in ODL in the OUSL. The objectives of the

study; To examine the significant factors of Student

Satisfaction in ODL in the OUSL and confirm the

conceptual model. The research question for the study;

What significant factors do Students Satisfaction influence

ODL in the OUSL?

3.1 Conceptual Frame work and the Hypotheses

The conceptual frame work for this study is mainly based

on literature review. It consists of three (3) independent

variables of, service quality dimensions of Reliability,

Website Content and Cost& Time. The independent

variable is Student Satisfaction in ODL in the OUSL. The

research hypotheses: -

There are three research hypotheses built into this study;

1. H1: There is an association between Reliability and

Student Satisfaction in ODL in the OUSL.

2. H2: There is an association between Website Content

and Student Satisfaction in ODL in the OUSL.

3. H3: There is an association between Cost &Time and

Student Satisfaction in ODL in the OUSL.

Figure 1: Conceptual Frame work

3.2 Research Instrument

3.2.1 Data Collection

The validated questionnaire through a pilot test was

administered to collect the data. The sample of 760

undergraduate students followed a stratified sampling

procedure covering the central university and 5 of their

main regional centersisland wide which has a population

of 38,000 students.The respondents were selected from the

Regional Centers randomly as those who were willing to

participate in this survey provided they had a learning

experience with the university of more than, or equal

toone year at least.The 744 valid responses were used for

the analysis which covered 98% of the original size of the

sample.

3.2.2 Procedure

The Structural Equation Modeling (SEM) analysis was

adopted for this study which is considered as the second-

generation multivariate data analysis method (Gye-Soo,



203

2016; Hair, Hult, Ringle, & Sarstedt, 2017). The main two

methods of SEM, covariance-based SEM (CB-SEM) and

variance based approach of Partial Least Squares (PLS)

can be carried out using the PLS-Graph, VisualPLS,

SmartPLS, and WarpPLS (Hair, Hult, Ringle, & Sarstedt,

2017; Wong, 2013). SEM is used to solve the complex

research problem situations with multiple dependent and

independent variables (Akter, D'Ambra, & Ray, 2011).

PLS is a soft modeling approach to SEM with no

assumptions about data distribution (Akter, D'Ambra, &

Ray, 2011; Vinzi, Chin, Henseler, & Wang, 2010). The

advantages of SEM is when handling a small sample

size in the non-availability of sufficient theory, the

accuracy of the predictive power and confirming the

correct model specification (Wong, 2013). The software

package of SmartPLS3.2.6 was used in this current study

(Hair, Hult, Ringle, & Sarstedt, 2017). This SEM based

package used different types of fields. In the field of ODL,

service quality and student satisfaction (Mantovani, 2012;

Ribeiro & Gouvêa, 2013; Udo, Bagchi, & Kirs, Using


experience, 2011), Students‟ Satisfaction and continuance

intention in HE institutes (Al-Rahmi, Othman, & Yusuf,

2015; Chow & Shi, 2014 ; Ibrahim, Rahman, & Yasin,

2014; Shahijan, Rezaei, & Amin, 2015), Repurchase

Intention in Banking (Ibrahim, Rahman, & Yasin, 2014),

Satisfaction Industry in hospitality industry (Ali, Amin, &

Cobanoglu, 2015; Izogo, 2016), customer satisfaction

(Gye-Soo, 2016; Ringle, Sarstedt, & Zimmermann, 2011).

3.3 Survey material

Based on the conceptual model the questionnaire was

developed to collect data to test the research hypotheses.

The research instrument was based on literature and most

of the time the validated questions were used as the survey

items by modifying it more to reflect the HE and ODL

system. The questionnaire consisted of two (2) sections.

The first section was the demographic data and the second

section consistedof 27questions which have been rated on

a5- point Likert scale.

3.3.1 Reliability

The questions for this variable ismainly based on

SERVQUAL (Parasuraman, Zeithaml, & Berry.,

SERVQUAL: A Multiple-Item Scale for Measuring

Consumer Perceptions of Service Quality, 1988),

modified SERVQUAL (Udo, Bagchi, & Kirs, Using


experience, 2011) and other literature based HE studies of

(Aghamolaei & Zare, 2008; Al-Rahmi, Othman, & Yusuf,

2015; Mantovani, 2012) .There were six(7) questions to

evaluate the service quality dimension of Reliability under

the Likert scale 1-5. The Table 1 has tabulated the

Questions for the construct of Reliability.

Table 1 Questions for the construct of Reliability

3.3.2 Website Content

The eight (8) items (Table 2) were constituted for this

item based on the study of (Udo, Bagchi, & Kirs, Using


experience, 2011) rated on the 1-5 Likert scale. These

items were mainly based on (Cao, Zhang, & Seydel, 2005;

Wang, Wang, & Shee, 2007; Zhang, Prybutok, & Huang,

2006). These items are set to measure the usefulness of the

information with relation to the lessons, accuracy, quality

of information, and the applications of audio-video,

multimedia and graphics. The Table 2 has tabulated the

Questions for the construct of Website Quality.

3.3.3 Cost & Time

There were only 3 items (Table 2) for this construct and

use Likert scale (1.5) for the rating of the responses. This

construct measures the allocated of the time periods for

the courses, the payments and the available payment

schemes for the programmes. Questions were mainly

Item Question Source

REL1

REL2

REL3

The instructor consistently

provides good lectures.

The instructor is dependable.

The instructor reliably

corrects information when

needed.

(Mantovani, 2012;

Udo, Bagchi, &

Kirs, Using SERVQUAL to

assess the quality of

e-learning experience, 2011)


WSC1.

WSC2.

WSC3.

WSC4.

WSC5.

WSC6.

WSC7.

WSC8.

The web site provides

useful information.

The web site provides

accurate information.

The website provides

high quality

information.

The information on the

web site is relevant to

my lessons.

The web site uses multimedia features

properly.

The web site uses

animations/graphics

properly.

The web site uses audio

elements properly.

The web site uses video elements properly.

(Udo,

Bagchi, &

Kirs, Using SERVQUAL

to assess the

quality of e-learning

experience,

2011)

(Udo,

Bagchi, &

Kirs, Using

SERVQUAL to assess the

quality of e-

learning experience,

2011)

(Udo,

Bagchi, & Kirs, Using


quality of e-

learning

experience,

2011)

(Udo, Bagchi, &

Kirs, Using


quality of e-

learning experience,

2011)



204

based on (Joseph & Joseph, 1997). The Table 3 has

tabulated the Questions for the construct of Cost & Time.

Table 3: Questions for the construct of Cost & Time

3.3.4 Satisfaction

There were nine (9) (Table 4) questions that were set out

for this construct to measure the overall satisfaction of

their perceived service experience. The items were

adopted from the (Gruber, Fuß, Voss, & Glaeser-Zikuda,

2010; Mantovani, 2012; Udo, Bagchi, & Kirs, Using


experience, 2011; Zhang, Prybutok, & Huang, 2006) using

the 5-point Likert scale for the response rating.

Table 4: Questions for the construct of Satisfaction

4 Data Analysis and Results The instrument used for this study has been validated

through a pilot test (Table 5). The pilot test was verified

with 50 undergraduate students selected randomly from

the central university premises. The Cronbach‟s alpha and

Kaiser-Meyer-Olkin (KMO) values revealed that the

required standard of the values is greater than 0.7000

except the dimension of Cost &Time (KMO= 0.584)

(Field, 2011, p. 647; Hair, Black, Babin, Anderson, &

Tatham, 2011, p. 139) . The Cost & Time dimension has

shown the law value of Cronbach‟s alpha and KMO since

it depends on the number of items and has only 3 items

(Devi, 2015). In PLS-SEM data analysis mainly in two

Parts; Measurement Model analysis and Structural Model

analysis. Measurement Model represents the relationships

between constructs and their corresponding indicators and

is generally referred to as an outer model. The Structural

Model describes the relationships between latent variables

or constructs and referred to as the inner model (Hair,

Hult, Ringle, & Sarstedt, 2017).

Table 5: Pilot Test Results

4.1 Measurement Model Analysis

There are two measurement model specifications based on

the development of the constructs; Reflective and

Formative. The Reflective Model representingthe

causality is from the constructs to its measures. The

Formative Model which is based on the causal indicators

form the construct (Hair, Hult, Ringle, & Sarstedt, 2017).

As the first step for the reflective Measurement Model the

outer loadings (Appendix A) of the indicators were

estimated. The threshold value of 0.7 was not to be found

in the items of REL5P REL6P, REL7P, SAF8P and

SAF9P and they were removed from the constructs. An

increase in the value of Average Variance Extracted

(AVE) and R2were observed. The Indicator Reliability

(square value of outer loadings) is also another indicator

of the Measurement Model and the highest (0.812) is

given by the largest value (CT1P = 0.901) of the outer

loading. The threshold value for the indicator reliability

must be greater than 0.700 (Hair, Hult, Ringle, & Sarstedt,

2017). The quality criteria values of construct reliability

and validity were given the composite reliability and

Cronbach's Alpha. The threshold value for these values

must be greater than 0.700. The convergent validity

indicator of AVE must be greater than 0.500. The results

of Cronbach's Alpha, Composite Reliability and AVE for

this study have reached the required standard (Appendix

B). The discriminant validity indicators of theFornell-

Larcker Criterion, cross loadings and Heterotrait-

Monotrait (HTMT) Ratio Confidence Intervals (CI) in

Appendix C, Appendix D and Appendix E respectively.

The results of the Fornell-Larcker Criterion (Appendix D)

showed all the diagonal values which is equal to the

square root of the AVE and is higher than the values in the

off diagonal positions; row andcolumn. This confirms that

all these constructs are valid measures of unique concepts.

The second discriminant validity indicator of Cross

Loadings (Appendix E) showed that the indicators‟

loading on its assigned construct is higher than all its

cross-loadings with other constructs. The third indicator of


CT 1

CT 2

CT 3

Satisfied with the allocated time

period for the degree programme.

Satisfied with the Cost of

accommodation.

Satisfied with the Cost structure

allocated for my program. ( part time

payments)

(Joseph &

Joseph,

1997) modified

(Joseph & Joseph,

1997)

modified

(Joseph &

Joseph, 1997)

modified


SAT1

SAT2

SAT3

SAT4

SAT5

SAT6

SAT7

SAT8

SAT9

Would you agree to say that „„I am

satisfied with my decision to enroll with this distance program‟‟?

Would you agree to say that „„My choice to enroll in this program was a

wise one?‟‟

Would you agree to say that „„I think I

did the right thing when I paid for this

learning service?‟‟

Would you agree to say that „„I feel

that my experience with distance learning has been enjoyable?‟‟

This distance learning course meets my expectations.

My Overall experience is better than I originally anticipated.

I am satisfied overall with the programs and services offered by the

Institute.

I am satisfied with the distance course

since it will give me a better chance to

further my career development.

I am delighted with the distance

course and its contents.

(Udo,


SERVQUA

L to assess the quality

of e-learning

experience, 2011)

(Udo,


SERVQUA


of e-learning

experience, 2011)

(Udo,


SERVQUA


of e-learning

experience,

2011)

(Udo,


SERVQUA


of e-learning

experience, 2011)

Variables Cronbach's Alpha

KMO value

No. of Items

Reliability.

0.732 0.630 7

Website Content

0.807 0.786 8

Satisfaction 0.899 0.828 8

Cost and Time 0.673 0.584 3



205

HTMT ratios and the confidence intervals must be

examined and the ratios must be lower than the threshold

value of 0.85, and in the bootstrap results of HTMT,

confidence intervals must significantly be different from

1. In the (Appendix F) all the HTMT ratios have reached

the standard of less than 0.85. In (Appendix F: HTMT

Confidence Intervals Bias Corrected) the columns labelled

2.5% and 97.5% showed the lower and upper boundaries.

The value of 1 must not be included in these intervals

(Hair, Hult, Ringle, & Sarstedt, 2017). The summary of

the results of the Reflective Measurement Model is

shownin(Table 6).

Table 6: The summary of the results of the Reflective

Measurement Model

Note:

(Latent Variable(LV), Loadings (L), Indicator Reliability

(IR), Composite Reliability (CR), Cronbach‟s Alpha

(CA), Confidence Interval (CI) must not include

1(HTMT)).

4.2 Structural Model Analysis

The Variance Inflation Factor (VIF) is above 5 in the

constructs as the critical level of the multicollinearity The

results of VIF between dependent and independent

variables in (Table 7) and all values are less than 1.2 and

no issues of multicollinearity (Hair, Hult, Ringle, &

Sarstedt, 2017; Izogo, 2016) .

Table 7: The Collinearity Statistics (VIF) of the Structural

Model

The Structural Model relationships represent the

hypothesised relationships among the constructs. The path

coefficients (p values) can be obtained from the

bootstrapping test which are inbetween -1 and +1. The

bootstrap standard error enables computing the empirical t

values and p values for all path coefficients (Hair, Hult,

Ringle, & Sarstedt, 2017). The critical t value is 1.96 if the

significance level is 5% for the two-tailed test and the p

values are less than the 0.05 then the relationship can be

concluded as the significant under the considerationof 5%

confidence level (Hair, Hult, Ringle, & Sarstedt, 2017).

Table 8: The Bootstrapping results of path coefficients

Note: Original Sample (OS), Standard Deviation

(STDEV), Sample Mean (SM),

The output results (Table 8) confirmed thatall the

relationships are significant. The final model in Fig (2).

The variance extracted for the model which is considered

as a predictive power of the model is R2

is 0.5222

(52.2%). The R Square Adjusted is 0.520 (52.0%) which

is the unbiased R2 value after removing the nonsignificant

exogenous constructs (Hair, Hult, Ringle, & Sarstedt,

2017).

Figure 2: Final Structural Model

LV Indicat

ors

Convergent Validity Internal Consistency Reliability

DV

L

IR AVE

CR CA HTMT

>0.7 >0.5 >0.5

0.6-0.9 0.6-0.9 CI

Cost &

Time

CT1P 0.904 0.817

0.681 0.864 0.801 Yes CT2P 0.796 0.634

CT3P 0.769 0.591

Reliability

REL1P 0.848 0.720

0.636 0.874 0.809 Yes REL2P 0.758 0.575

REL3P 0.830 0.689

REL4P 0.748 0.559

Satisfactio

n

SAF1P 0.793 0.628

0.568 0.902 0.873 Yes

SAF2P 0.743 0.552

SAF3P 0.758 0.575

SAF4P 0.733 0.538

SAF5P 0.776 0.603

SAF6P 0.741 0.549

SAF7P 0.729 0.532

Website

Content

WCS1P 0.788 0.622

0.613 0.927 0.910 Yes

WCS2P 0.796 0.634

WCS3P 0.801 0.642

WCS4P 0.728 0.531

WCS5P 0.791 0.626

WCS6P 0.797 0.636

WCS7P 0.767 0.589

WCS8P 0.789 0.623

Construct Satisfaction

Cost & Time 1.129

Reliability 1.239

Satisfaction

Website Content 1.280

Construct Satisfaction

Cost & Time 1.129

Reliability 1.239

Satisfaction

Website Content 1.280



206

The Effect size (f2) of the relationships between

endogenous variable of Satisfactionand the exogenous

variables of Cost& Time is 0.024(small in size),Reliability

is 0.195(medium) and Website Content is 0.346 (large)

(Hair, Hult, Ringle, & Sarstedt, 2017). The Blindfolding

procedure Q2(Construct Cross Validated Redundancy

approach) suggests the value of the predictive relevance

of the model. The Q2

value is greater than zero

recommends the predictive relevance of the model for a

certain endogenous construct. With this model, the Q2 is

0.275 for the endogenous variable of Satisfaction (Akter,

D'Ambra, & Ray, 2011; Henseler, Hubona, & Ray,

2016).The values of the model fit summary; “SRMR is a

measure of approximate fit of the researcher‟s model. It

measures the difference between the observed correlation

matrix and the model-implied correlation matrix” (Garson,

2016, p. 68; Hair, Hult, Ringle, & Sarstedt, 2017).The

Standardized Root Mean Square Residual (SRMR) is

0.074 and Root Mean Square Residual Covariance

(rmsTheta) is 0.129. The threshold values are SRMR is less

than 0.08 (Hu & Bentler, 1999) and rmsThetais 0.12. The

results revealed the fitness of the final model (Garson,

2016; Hair, Hult, Ringle, & Sarstedt, 2017; Henseler, et

al., 2014)

5 Discussion and Recommendation

The research objective of this study is to examine the

significant factors of Student Satisfaction in ODL in the

OUSL and finalise the conceptual model. The three

significant factors were tested and concluded that all three

constructs can be included in the model as significant

predictors. The three hypotheses are supported from the

results of the study. The construct of the Reliability was

significant and this was consistent with the results of the

studies of (Hasan, Ilias, Rahman, & Razak, 2008; Malik,

Danish, & Usman, 2010; Sembiring, 2015; Stodnick &

Rogers, 2008)and inconsistent withthe study in Malaysia,

investigation of relationship between Service quality and

students‟ satisfaction (Wei & Ramalu, 2011). The

construct of Website Quality was significant and this

result is consistent with the study of (Mason & Weller,

2000)in a very large web-based course presented by the

Faculty of Technology in the Open University of the UK.

The results of this study were examined as a qualitative

research which uncovered the factors of the web based

course content and presentation fitness as

thestudents‟expectations and learning style. This mostly

affected students‟satisfaction. The study of (Ramayah,

2006) has showed by using extended the Technology

Acceptance Model that the perceived ease of use was

positively related to perceived usefulness of the course

website. The study of (Zhang, Prybutok, & Huang, 2006)

is also consistent with the current study results and

conformed to the Web site service quality which has

affected the consumers‟satisfaction level and further

enhancement of consumer intention. The other significant

construct is Cost & Time. The importance and

performance analysis of (Joseph & Joseph, 1997; Lim,

Yap, & Lee, 2011)confirmed the importance and it‟s4th

place in the ranking order of Cost and Time in service

quality factors in the higher education sector. In the

hospital industry results showed a significant relationship

between service experience and customer satisfaction,

which influences price acceptance of customers. (Ali,

Amin, & Cobanoglu, 2015). The cost (financial aid) is an

important decision when they select a higher education

institute (Sia, 2013). The promotions which affect cost

structures significantly influence the university selection

by the students and their parents (Zain, Jan, & Ibrahim,

2013). The recommendations on all three factors since

they are significant with the student satisfaction and

outcome would lead to positive and favorable decisions of

continuance of the studies, with the same institute. The

cost factor is very important when selecting a university

by the parents and the students. The feasible and reliable

cost structure and promotions will motivate both students

and parents and give them the impressionofeducation as

an investment for a life time (Lim, Yap, & Lee, 2011; Sia,

2013). The Factor of reliability is dependent on the sound

knowledge of the subjects, successful lectures, and the

quality of information. The quality must be assessed with

the lecturers, their professional knowledge and how they

treat their students. All the staff must have a very good

understanding of ODL delivery methods and their distance

education clientele, without frustrating the students who

have face to face sessions, by recommending to them the

hybrid method which is a mixture face to face, and on-line

learning. Visiting lecturersand other teaching staff must

offer quality enhanced trainingto continue with the

student‟s reliability in the promised service. “In the

Distance Education mode, whilst catering to larger

numbers, it also attempts to improve the quality of

training provided for teachers” (Lekamge, 2010, p.

4).Partial or full scholarships could be offered depending

on the results of the academic year. The quality of the

Website will enhance giving more reliable and a speedy

service to the students. The policy makers must take

strategic decisions to enhance the current service as an

attractive, reliable and uniquely recognised service. Future

research should be handled as a qualitative and

longitudinal way (Tinto, 1975) to understand other service

quality factors that influence the students‟ satisfaction

since the R2

has covered only 52%of this study. The term

„quality assurance‟ refers to a process of defining and

fulfilling a set of quality standards consistently and



207

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Appendix A

Outer Loadings

Items Cost &

Time

Reliability Satisfaction Website

Content

CT1P 0.901

CT2P 0.799

CT3P 0.773

REL1P 0.802

REL2P 0.706

REL3P 0.796

REL4P 0.718

REL5P 0.666

REL6P 0.591

REL7P 0.686

SAF1P 0.771

SAF2P 0.718

SAF3P 0.736

SAF4P 0.713

SAF5P 0.779

SAF6P 0.749

SAF7P 0.732

SAF8P 0.669

SAF9P 0.668

WCS1P 0.786

WCS2P 0.795

WCS3P 0.799

WCS4P 0.725

WCS5P 0.793

WCS6P 0.800

WCS7P 0.771

WCS8P 0.791

Appendix B

Construct Reliability and Validity

Construct Cronbach's

Alpha

Composite

Reliability

Average

Variance

Extracted

(AVE)

Cost &

Time 0.801 0.864 0.681

Reliability 0.809 0.874 0.636

Satisfaction 0.873 0.902 0.568

Website

Content 0.910 0.927 0.613

Appendix C

Discriminant Validity (Fornell-Larcker Criterion)

Construct Cost &

Time


Content

Cost & Time 0.825

Reliability 0.255 0.797

Satisfaction 0.341 0.561 0.754

Website

Content

0.308 0.419 0.637 0.783

Appendix D

Discriminant Validity (Cross Loadings)

Item Cost &

Time

Reliabili

ty

Satisfacti

on

Website

Content

CT1P 0.904 0.303 0.392 0.339

CT2P 0.796 0.127 0.185 0.180

CT3P 0.769 0.100 0.149 0.157

REL1P 0.165 0.848 0.529 0.379

REL2P 0.261 0.758 0.369 0.212

REL3P 0.214 0.830 0.465 0.360

REL4P 0.194 0.748 0.402 0.364

SAF1P 0.300 0.471 0.793 0.506

SAF2P 0.268 0.365 0.743 0.537

SAF3P 0.258 0.391 0.758 0.451

SAF4P 0.202 0.377 0.733 0.489



211

SAF5P 0.237 0.518 0.776 0.473

SAF6P 0.210 0.418 0.741 0.458

SAF7P 0.322 0.408 0.729 0.444

WCS1P 0.232 0.462 0.593 0.788

WCS2P 0.255 0.371 0.538 0.796

WCS3P 0.282 0.346 0.528 0.801

WCS4P 0.293 0.275 0.436 0.728

WCS5P 0.215 0.297 0.478 0.791

WCS6P 0.242 0.284 0.440 0.797

WCS7P 0.208 0.257 0.447 0.767

WCS8P 0.203 0.281 0.489 0.789

Appendix E

Discriminant Validity (Heterotrait-Monotrait Ratio

(HTMT))

Construct Cost &

Time


Content

Cost & Time

Reliability 0.268

Satisfaction 0.343 0.656

Website

Content

0.313 0.472 0.707

Appendix F

Discriminant Validity (Heterotrait-Monotrait(HTMT)

Confidence Intervals Bias Corrected

Relationship Origina

l

Sample

(O)

Sampl

e

Mean

(M)

Bias 2.5

%

97.5

%

Reliability -> Cost &

Time

0.268 0.271 0.00

3

0.19

8

0.347

Satisfaction -> Cost

& Time

0.343 0.344 0.00

1

0.26

9

0.413

Satisfaction->

Reliability

0.656 0.657 0.001

0.578

0.725

Website Content ->

Cost & Time

0.313 0.313 0.00

1

0.23

4

0.396

Website Content ->

Reliability

0.472 0.472 0.000

0.391

0.551

Website Content ->

Satisfaction

0.707 0.707 0.00

0

0.64

7

0.761

Appendix G

Collinearity Statistics (VIF)

Construct Cost

&

Time


Content

Cost & Time 1.129

Reliability 1.239

Satisfaction

Website

Content

1.280

issn: 2456-9992 predictive drivers of students‟ … servqual, the prominent service quality...

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