Exploratory Factor Analysis of the Indonesian Version of Student

Engagement Scale

Mario Pratama and Anindra Guspa

Department of Psychology, Faculty of Education, Universitas Negeri Padang, Indonesia

Keywords: Student Engagement, Factor Analysis.

Abstract: Student engagement is one of the factors that influence student academic achievement. However, there is

much debate about the operational definition and dimensionality of this construct. For this reason, this study

intends to examine dimensionality of this construct. A total of 596 students in Indonesia participated in this

study consisting of junior high school students, high school students, and undergraduate students. Data was

collected online using a student engagement scale (SES), the Indonesian version of the adaptation of the SES

by Reeve & Tseng, which contains 22 items. The results of this scale found that the Cronbach alpha reliability

coefficient was 0.927. Content validity analysis by Forward-Backward translation by linguists and by expert

judgment. Analysis of construct validity with exploratory factor analysis found that the SES version of the

Indonesian language consisted of three 3 factors accounting 57.986% of total variance explained, but it also

consisted 4 factors accounting 62.078% of total variance explained. So, based on these results, the Indonesian

version of the student engagement scale can be applied using three or four dimensions.

1 INTRODUCTION

Adolescence is a crucial development period where

adolescents experience a phase of self-identity

formation, social integration, and commitment to

learning (Skinner et al., 2009). In this phase,

adolescents are busy with activities at school,

especially in the learning process. Therefore, in this

learning process, adolescents as students should be

able to participate actively. Active student

participation which is marked by interest, investment

and student effort in school assignments and activities

both inside and outside the classroom is known as

student engagement (Wang & Holcombe, 2010).

Student engagement leads to the totality of

students to be actively and proactively involved in

learning activities in a behavioral, cognitive, and

emotional manner (Fredricks & McColskey, 2012).

According to Wang and Holcombe (2010)

adolescents who have student engagement will be

involved in their school, take the time to develop their

academic potential, channel their energies to positive

activities and mobilize their motivation to be actively

involved in classroom and outside activities. Student

engagement is also a predictor that shows the level of

attention, effort, persistence, positive emotions, and

commitment of a student in the learning process

(Handelsman et al., 2005).

Student engagement is important for students,

because this behavior supports the learning process so

that it can take place well. Klem & Connell (2004)

stated, students who are engaged in learning

activities, especially in class, are much more likely to

have good performance than those who are not

involved in these activities. Low student engagement

among students is a contributing factor to low

achievement, boredom, feelings of alienation, and

even causes students to drop out of school (Fredricks

& McColskey, 2012).

The importance of student engagement is one of

the most interesting and widely researched studies

today, including in Indonesia. It's just that researchers

have limitations in data collection instruments. Not

many studies have been found on psychometric

property testing regarding student engagement

measurement tools, so it is often the cause of

weaknesses in research on student engagement.

Based on this, the researcher is interested in

conducting research on testing psychometric

properties of dimensionality and reliability of the

Indonesian version of the student engagement

measurement tool.

Research on the psychometric properties of student

Pratama, M. and Guspa, A.

Exploratory Factor Analysis of the Indonesian Version of Student Engagement Scale.

DOI: 10.5220/0011095600003368

In Proceedings of the International Conference of Mental Health (Icometh 2021), pages 73-76

ISBN: 978-989-758-586-9

engagement has been conducted by Fredriks &

McColskey (2012). In his research, it was found that

student engagement is a multidimensional construct

consisting of three dimensions. These dimensions are

cognitive engagement, emotional engagement, and

behavioral engagement. In this study, 21 items were

valid and reliable for measuring student engagement.

Another study conducted by Reeve & Tseng (2011)

found that student engagement is a multidimensional

construct consisting of four dimensions, namely

cognitive engagement, emotional engagement,

behavioral engagement, and agentic engagement. The

results of research conducted by Veiga (Veiga, 2016)

found that student engagement consists of cognitive

engagement, emotional engagement, behavioral

engagement, and agentic engagement. Meanwhile,

research conducted by Appleton, Cristenson, Kim, &

Reschly (2006) found that student engagement

consists of two dimensions, namely cognitive

engagement and psychological engagement.

In this study, the student engagement scale (SES)

being tested is a scale adapted from the SES made by

Reeve and Tseng (2011) which states that student

engagement consists of four dimensions, namely:

Agentic engagement (AE) is student involvement in

a form that deliberately acts proactively about what

will be learned and prepare for the lesson, Behavior

engagement (BE) is the involvement of students in

the form of concentration, attention, and effort during

the learning process, Emotional engagement (EE) is

student involvement in the form of interest in learning

and the absence of emotional resistance (stress) on

lessons, and Cognitive Engagement (CE) is the

involvement of students in the form of using

strategies in learning activities.

2 METHOD

This study uses a quantitative research design. The

validity of the measuring instrument in this study was

obtained in two ways: first, through content validity

carried out through an assessment by a panel of

experts and secondly through the obtained construct

validity through exploratory factor analysis, namely to

test the dimensional properties of the construct this

student engagement. The reliability of the measuring

instrument was obtained using the alpha Cronbach

analysis.

A total of 596 students in Indonesia participated in

this study consisting of junior high school students,

high school students, and undergraduate students.

Data was collected online using a student engagement

scale (SES), the Indonesian version of the adaptation

of the SES by Reeve & Tseng (2011), which contains

22 items.

3 RESULTS

The student engagement scale used is an adaptation

of the student engagement scale made by Reeve &

Tseng (2011). The adaptation process refers to the

way described by Beaton et al., (2000) in which the

processes include: 1) Translating the original

language measuring instrument into Indonesian. In

this case the researcher translates with the help of a

licensed translator and another translator who is

proficient in psychology. 2) Synthesis of translation.

The two translations from the translators were

synthesized. 3) Backward transaction. In this case the

researcher is assisted by a translator who speaks

Indonesian and is a native speaker of the original

language. 4) Final translation assessment by expert

judgment.

From the results of data analysis with the

Cronbach Alfha test, the reliability coefficient value

was 0.927. Then to find out the factors / dimensions

that make up SES, it is done by using the EFA test,

by first doing an assumption test analysis with KMO

and Bartlett's test. The assumption test results

obtained a KMO value of 0.939 (>0.05) and a Bartleet

Test of 7000,823 (p=0.000), so it can be concluded

that the assumption test is fulfilled so that it can be

continued to factor analysis. The results were

analyzed by means of the analysis of exploratory

factor analysis (EFA). The results of this analysis

indicated that there were 3 factors that had

eigenvalues above 1, these three factors were able to

explain 57,986% of the total variance of SES. The

results of loading factors from the EFA can be seen in

the following table:

Table 1: SES loading factor results with 3 factors.

No Item

Factors

12 3

i1 .188 .265 .670

i2 .106 .065 .827

i3 .145 .099 .842

i4 .318 .213 .650

i5 .235 .106 .748

i6 .170 .801 .110

i7 .206 .759 .136

i8 .252 .796 .102

i9 .410 .697 .124

I10 .135 .548 .128

i11 .445 .616 .186

Icometh 2021 - International Conference of Mental Health

i12 .372 .610 .174

i13 .535 .603 .185

i14 .325 .329 .285

i15 .720 .292 .185

i16 .716 .240 .146

i17 .747 .199 .235

i18 .635 .196 .273

i19 .636 .174 .257

i20 .614 .313 .027

i21 .694 .237 .161

i22 .599 .284 .168

Based on the table, it is found that the SES

measurement tool forms 3 factors, namely agentic

engagement, behavioral & emotional engagement,

and cognitive engagement. However, this result is

different from the theory proposed by Reeve & Tseng

(2011) which states that SES consists of 4 factors, so

the researcher performs the EFA test again by

bringing up 4 factors. The results of this analysis

show that the SES which consists of 4 factors is able

to explain 62.078% of the total variance of SES.

However, the results of the eigenvalues of three

factors have a value above 1 and one factor has a

value of 0.900. The results of loading factors from

this analysis can be seen in the following table:

Table 2: SES loading factor results with 4 factors.

item

Factors

1 2 3 4

i1 .190 .247 .667 .108

i2 .108 .052 .825 .069

i3 .146 .083 .839 .085

i4 .342 .224 .661 -.061

i5 .229 .079 .741 .146

i6 .185 .795 .115 .099

i7 .210 .737 .134 .178

i8 .269 .791 .108 .085

i9 .424 .686 .127 .099

I10 .194 .611 .162 -.307

i11 .429 .565 .170 .312

i12 .341 .539 .149 .426

i13 .513 .541 .165 .367

i14 .239 .189 .226 .787

i15 .725 .274 .183 .088

i16 .729 .234 .150 .017

i17 .759 .192 .238 .019

i18 .642 .183 .272 .056

i19 .627 .140 .247 .170

i20 .618 .296 .025 .089

i21 .691 .209 .154 .141

i22 .596 .257 .162 .144

Based on the table, it is found that SES forms 4

factors with items 1-5 forming the AE factor, items 6-

10 forming the BE factor, items 11-14 forming the EE

factor, and items 15-22 forming the CE factor, so

these results are in accordance with the theory

submitted by Reeve & Tseng (2011).

4 DISCUSSION

The results of this study found that the SES reliability

value was 0.927. The results of the EFA test show that

the Indonesian version of SES is formed by 3 factors

which explain the SES of 57,986%. Then it could also

form 4 factors that could explain the SES of 62.078%.

In this study the Indonesian version of SES was

adapted from SES made by Reeve & Tseng (2011)

which states that SES consists of 4 factors, if we refer

to the EFA results where 3 factors have an

eiugenvalue value above 1 then one more factor has

an eigenvalue of 0.900. So that we can conclude that

there is a possibility that the Indonesian version of

SES is a multi-dimensional measuring tool that can

be used as 3 factors. Research conducted by Fredricks

& McColskey (2012) states that student engagement

is a multidimensional construct consisting of 3 factors.

The Indonesian version of SES can also be used

as 4 factors according to the basic theory. Research

conducted by Veiga (2016) on students in Portugal

also found that SES consists of 4 factors, namely

agentic engagement, behavioral engagement,

emotional engagement, and cognitive engagement.

Based on the results of the study, the Indonesian

version of SES allows it to be used by using 3 or 4

factors. However, for even stronger proof, the

researcher suggests conducting tests using

confirmatory factor analysis to test the theoretical

model whether the Indonesian version of SES is fit

with a 3-factor or 4-factor model.

5 CONCLUSIONS

The results showed that the Indonesian version of

SES has a reliability coefficient of 0.927. The EFA

results show that SES consists of 3 factors that can

explain 57,986% of SES, and form 4 factors that can

explain SES of 62.078%. So based on these results it

is possible that SES can be used with 3 factors or 4

factors. However, for further research, the researcher

suggests conducting a confirmatory factor analysis

test to ensure the correct theoretical model to explain

the theoretical construct of SES.

Exploratory Factor Analysis of the Indonesian Version of Student Engagement Scale

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