Predicting Retention: Sociodemographic, Motivational, and Perceived

Social Support Factors

Ria Wardani

, Ira Adelina

and Heliany Kiswantomo

Fakultas Psikologi, Universitas Kristen Maranatha, Jl. Prof. Drg. Suria Sumantri 65, Bandung, Indonesia

Keywords: Motivation, Sociodemographic, Social Support, Student Retention.

Abstract: Low student retention becoming problematic issue in many education institutions in the midst of increasingly

fierce competition in higher education. Low student retention reflects educational providers capability in

equipping their students to prepare their future. This study examines this issue through sociodemographic

factors, motivational, and perceived social support so that strategies can be formulated to increase student

retention. Using quantitative research method with first-year student research respondents, the research

employed questionnaire in assessing students demographic properties, Academic Motivation Scale (AMS-

Indonesian), Academic Retention Scale (ARS), and Multi-dimensional Social Support Scale (MSPSS).

Statistical analysis showed that internal motivation and social support contribute significantly toward student

retention; while sociodemographic factors do not contribute directly toward student retention. However, there

are some interesting findings: 1) Levels of spending is positively correlated with motivation, especially

intrinsic and amotivation (reversed); 2) Mother’s level of education, but not father’s, is positively correlated

with intrinsic motivation; 3) Students’ whose mothers are working tend to have higher retention on self-related

aspect, and motivation on both intrinsic and extrinsic. The conclusion is that first-year students with clear

academic goals and perceived sources of support for their academic activities will help to survive and

therefore avoid dropping out of college.

1 INTRODUCTION

When entering college, new students will confront

many new challenges in form of greater academic

demands, greater autonomy, and a distinct academic

structure of college life. First-year students must be

able to adapt to new social environments, to orient

themselves towards the institutions where they attend,

to become productive members of the community, to

adapt to new roles and responsibilities (such as

managing their finances), set boundaries with friends

and family, and to engage in the process of planning

their future career (Crede & Niehorster, 2012). There

is even a traditional view that leaving home to a

higher education environment is a ritual for most

individuals (Thomas & Hanson, 2014), especially if

they have to leave their hometown to a different place

away from their parents.

https://orcid.org/0000-0001-9911-5733

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The increasing difficulty of recruiting students to

its capacity requires universities to develop strategies

capable retaining students who have been accepted

until they have successfully completed their

education. This ability reflects student retention.

According to Fowler & Luna (2009), retention in

education refers to the continuity until successful

completion of a student. Retention is the act of some

students to survive and successfully graduate, while

others do not (Fowler & Luna, 2009). Although the

term itself sounds negativistic, the fact that parents,

policy makers, and educators have spent a lot of

resources on students’ education makes it especially

important to evaluate students’ progress along the

way. Here, we need to keep assessing their

engagement in order to implement a more effective

learning. In order for funds not to be wasted, steps

need to be taken to review the success of students in

the education taken and organize so that learning can

run effectively (Kim et al., 2010).

University X, one of private universities in

Bandung, also facing this phenomena. In at least three

academic years, 2014/2015, 2015/2016, 2016/2017,

Wardani, R., Adelina, I. and Kiswantomo, H.

Predicting Retention: Sociodemographic, Motivational, and Perceived Social Support Factors.

DOI: 10.5220/0010742800003112

In Proceedings of the 1st International Conference on Emerging Issues in Humanity Studies and Social Sciences (ICE-HUMS 2021), pages 33-40

ISBN: 978-989-758-604-0

and first semester of 2017/2018, as much as 880

students resigned from their chosen program of study

in this university. Half of those students chose to

mutate or move to another college, the rest chose to

change their program study at the same university.

This phenomenon continues to this day. From

September 2020 to April 2021, nearly 400 students

have resigned or were considered to have resigned

due to inactivity. Although there are various reasons

behind it, this phenomenon is an unexpected event,

both for the study program and department as well as

for the institution overalls.

Amid increasingly intense competition in

attracting new students, the phenomenon of resigning

students seems to be ironic. Hard work and promotion

are becoming less significant. In addition, the success

of educational institutions in carrying out their formal

mission of educating and preparing students to

achieve long-term life goals (Kim et al., 2010;

McCormik & Lucas, 2011) are also at stake. Tinto

(2017), argues that student retention directly reflect

students’ perseverance. Institutions may try as hard as

they can to engage students until they successfully

complete their education, but it would only work if

students have a desire to try to survive in the college

they have chosen.

Generally, vulnerable students in regard of

retention are first-year students. Hurford et al. (2017)

stated that first-year students having difficulty to

adjust to academic demands in college or feeling

unsuitable for their chosen study program, would

have disrupted academic productivity. Leaving their

home town to study in another city, being separated

from family and friends, adjusting to college life, and

having to meet family and study program

expectations are common stressors for first-year

students (Carragher & McGaughey, 2016). That's

why most student retention research is aimed at first-

year students (Kovačić, 2010).

Retention research in the first year is useful in

detecting early students are more likely to drop out so

that constructive strategies can be made. Timely and

proactive action against students at risk of dropping

out of college is needed in order to provide

administrative support to increase their chances of

surviving and completing the educational programs

they pursue (Kovačić, 2010). Tinto's model states

that the greater students academic and social

integration, the higher the retention rate would be

(Tinto 1975). Meanwhile Bandura model asserts that

individual behavior will be influenced by both

personal and environmental factors (Ormrod, 2011),

considering that students and college environment

will interact reciprocally.

Friedman & Mandel (2011) summarizes the

results of previous research on student retention. In

general there are three research focuses in examining

factors capable of predicting student retention. First,

studies focus on demographic data, such as gender

socioeconomic status, and parental education. So far,

there are still many questions involving how much

influence do demographic variables on student

retention. This study will specifically and in detail

analyze the sociodemographic factors of first-year

students in relation to student retention at University

The second research focus emphasizes the

influence of institutional variables on academic

success (Friedman & Mandel, 2011), for example the

size of the institution student and lecturer ratios,

student attachment to educational institutions, and the

effectiveness of specialized programs designed to

improve retention. The Directorate General of The

Ministry of Education has developed a college

accreditation instrument that measures university

readiness in reaching institutional and program study

standards. That said this study will not include

institutional variables as part of the research.

The third research focus emphasizes on

psychological variables, such as student motivation.

Previous studies have shown that the orientation of

student motivation also affect their performance and

ability to survive in college. Other researchers

focused on specific part of motivation, intrinsic

motivation (Morrow & Ackermann, 2012), attributes

to academic performance and retention. Meanwhile,

Slanger et al. (2015) stated that motivation is a

predictor of academic success and perseverance in

college. Therefore, this study will measure

motivation variables consisting of intrinsic, extrinsic,

and amotivation as individual psychological aspects

(Slanger et al., 2015) along with social support.

According to Einolander and Vanharanta (2015),

students who are incapable or failing to build social

support system are more likely to drop out. Tinto

(2003) also notice the importance of circumstances

that can improve student perseverance, including

academic, social, and personal support.

Based on the previous explanation, the authors

believe that research on variables dynamics student

retention at University X is an issue that needs to be

critically studied. Based on those variables, the study

aimed to find out how prevalent sociodemographic

factors, motivation, and perceived social support are

toward first-year student retention. Based on the

previous studies, the authors hypothesized that certain

sociodemographic factors, student motivation, and

perceived social support directly contribute to student

ICE-HUMS 2021 - International Conference on Emerging Issues in Humanity Studies and Social Sciences

retention. In more detail, this research also

hypothesize that certain aspects of motivational

variables and social support influence student

retention.

2 METHODS

2.1 Research Design

This research is a quantitative study that has four

variables. This study aims to find out the correlation

and contribution of sociodemographic, motivation,

and perceived social support factors to student

retention at University X.

Using purposive sampling techniques, the data is

collected online by distributing google-form links

that measure sociodemographic variables,

motivation, social support as independent variables

and retention as dependent variables.

2.2 Research Instrument

Sociodemographic factors that are asked were gender,

study program, place/region of origin, school origin,

the status of residence in Bandung (boarding

house/with parents/other), the order in the family and

sibling education, parental education, parental

employment, ethnicity, economic and social status

(SES).

Academic Retention Scale (ARS) consists of 23

statement items with seven scales. Based on the data,

when we conducted factor analysis, there were only 3

factors (subscales). Those are: social factors (8-

items), institution factors (5-items), and self-related

factor (similar to motivation, 9-items) and Internal

resources (three sub-scale statement items).

Reliability test results show satisfactory internal

consistency, both for External resources (a = .889),

and for Internal resources (a = .817). An example of

academic retention items is, "Faculty assists me in

choosing study program choices."

The Indonesian version of the Academic

Motivation Scale (AMS) was tested by Lina Natalya

and Cynthia Vivian Purwanto (2018) with seven

scales. All items have been grouped to measure

academic motivation based on the third-order CFA

and EFA.

Factor-loading value of its item is > 0.4, there no

items with zero loadings. There are three dimensions

(subscales) of AMS, those are intrinsic motivation,

extrinsic motivation, and amotivation--which is a

negative scale.

The global social support measuring instrument

(Zimet et al., 1988) consists of 12 items with seven

scales of answer options. The entire item shows a

grouping of support sources (i.e., family, friends,

significant others).

Each dimension of supporting group consist of

four items. The CFA result showed that all items were

high loading on factor and confirmed that the three

subscale gauges had measured the expected sources

of support. Example item, "My family is willing to

help me to make a decision."

2.3 Data Analysis Techniques

This research use several statistical analyses in

multiple regression, correlation, and different tests.

All data is processed by calculating the average item

score per aspect, and the total variable score is the

average aspect score.

For example:

motivation variable = [intrinsic mot + ex mot +

amotiv [r]]/3

in which case :

the amotivation [r] is [item 4 + item 13] /2.

At the end of the data gathering process, all data

were coded accordingly. Each entry was inspected

and entries with significant incompleteness were

excluded from the analysis. Retesting the validity and

reliability of the scales. Following that, score-

balancing were conducted by averaging the score of

items for each aspect in the scale. This were done

because the number of items varied between aspects.

For example, in student retention scale, there were 9-

items representing self-aspect, 4-items representing

institutional aspect, and 7-items representing social

aspect of student retention. That said, the score of

self-aspect in student retention would be the total

score of the 9-items divided by 9. The same procedure

was also done for the other two aspect of student

retention as well as the three aspects of motivation

and three aspects of perceived social support. Each

scale score was the average of its aspects, for

example, the score for retention scale would be the

average of its three aspects.

Statistical analysis was then started by doing

descriptive analysis of the whole data. Following that,

correlational analysis using Spearman Rho were done

between the aspects of the variables as well as the

variables themselves. Multiple regression then was

conducted to assess the models of interactions

between variables and their aspects. Lastly, additional

analysis were done by comparing between-subject

means of each variable and its aspects.

Predicting Retention: Sociodemographic, Motivational, and Perceived Social Support Factors

3 RESULTS AND DISCUSSION

3.1 Demographic Overview

Participants in this study are 229 students (mean age

= 18.4 years old, Standard Deviation (SD) = .687;

82.5% female; Sundanese ethnicity 26.6%, Tiong

Hoa 25.3%, Java 17.0%, and Batak 10.9%). Majority

of students have monthly expenses of 1,000,000-

2,500,000 (61.3%) with median = 1,500,000, mean =

2,220,000 and SD = 2,190,000. In general,

participants have working father (96.3%).

Educational backgrounds of their fathers are the

following: 20.1% hold post graduates degrees; 39.7%

hold bachelor degree (S1/D4); 7.9% hold vocational

(D1-D3); 29.7% high school graduates; and 2.6% did

not finish high school. Around half (54.8%) of

participants' mothers also work. Their education

background are the following: 41% hold bachelor

degree (S1/D4); 19.7% hold vocational degree (D1-

D3); 32.3% are high school graduates; and 7% didn't

finish high school.

Based on Table 1, we can see that participants

retention tendencies at X universities is quite high

(retention mean =5.373 of the maximum group scores

in retention =6.875 and SD=0.688).

On average participants have high motivation as

well (mean = 5.968 from a maximum score of = 7.000

and SD = 0.683). Lastly, on average, perceived social

support variable is also quite high (mean = 5.634 from

the maximum score = 7.000 and SD = 0.923). In

general, participants want to stay at X university, are

motivated to go to college, and perceive that they

receive social support to attend University X.

3.2 Correlation Result and Regression

Table 2 shows, in general, retention have a positive

correlation with the other two variables, with student

motivation r = 606 (p=.000) and with perceived social

support r=.669 (p=000). The correlation between

student motivation and perceived social support is

.508 (p=.000).

Correlation between variable retention, motivation,

and perceived social support can be seen in Table 2.

Meanwhile, in table 3, there were no significant

correlation between demographic factors and

retention. However, in table 4, economic status

(judging by monthly expenses) has a positive

correlation (r = .178, p = .009) with motivation,

especially in table 5, with intrinsic motivational

aspects (r=.160, p=.019) and amotivation (r=.165,

p=.016). In table 4, mother educations also positively

correlates with student motivation (r=.147, p=.026),

especially in table 6, with intrinsic motivational

aspects (r=.166, p=.012).

Table 1: Descriptive statistic of the main variable statistics of the study.

Variable Min Max Mean Std. Deviation

Retention

3.319 6.875 5.373 0.688

Social

2.625 7.000 5.366 0.776

Institutions

2.333 7.000 5.183 0.790

Yourself 2.000 7.000 5.570 0.876

Motivation 3.778 7.000 5.968 0.683

Extrinsic 3.000 7.000 5.977 0.859

Intrinsic 3.600 7.000 5.913 0.738

Amotivation [reversed] 1.500 7.000 6.015 1.139

Perceived Social Support 2.417 7.000 5.634 0.923

Significant Others 1.250 7.000 5.813 1.113

Friends on 1.750 7.000 5.531 1.010

Family 1.000 7.000 5.557 1.293

ICE-HUMS 2021 - International Conference on Emerging Issues in Humanity Studies and Social Sciences

Table 2: Correlation between variables.

Retention Motivation Support

Retention 1

(

2-tailed

)

N 229

Motivation .606

Sig. (2-tailed) 0

N 229 229

Support .669

.508

(

2-tailed

)

0 0

N 229 229 229

Table 3: Correlation between demographics and retention.

1 2 3 4 5

1.Age 1

(

2-tailed

)

N 229

2.Economic

status

0 1

(

2-tailed

)

.998

N 214 214

3.Father’s

education

-.092 .051 1

(

2-tailed

)

0,163 0,46

N 229 214 229

4.Mother’s

education

0 .032 .586

(

2-tailed

)

.996 .645 0

N 229 214 229 229

5.Retention .064 .064 .006 .007 1

Sig. (2-tailed) .337 .355 .925 .912

N 229 214 229 229 229

Table 4: Correlation between demographics and motivation.

1 2 3 4

1.Economic

Status

Sig. (2-tailed)

214

2.Father’s

education

.051 1

Sig. (2-tailed) .46

N 214 229

3.Mother’s

education

.032 .586

Sig. (2-tailed) .645 0

214 229 229

4.Motivation .178

.069 .147

Sig. (2-tailed) .009 .297 .026

N 214 229 229 229

Table 5: Correlation between economic status and aspect of

motivation.

1 2 3 4

1.Economic

Status

(

2-tailed

)

214

2.Extrinsic

motivation

.086 1

Sig. (2-tailed)

.208

214 229

3.Intrinsic

motivation

.160

.414

Sig. (2-tailed)

0,019 0

214 229 229

4.A motivation

.165

.184

.533

Sig. (2-tailed) .016 .005 0

214 229 229 229

Table 6: Correlation between mother’s education and

aspect of motivation.

1 2 3 4

1.Mother’s

education

Sig. (2-tailed)

229

2.Extrinsic

motivation

.041 1

(

2-tailed

)

.535

229 229

3.Intrinsic

motivation

.166

.414

Sig. (2-tailed)

.012 0

229 229 229

4.A motivation

.116 .184

.533

Sig. (2-tailed)

.08 .005 0

229 229 229 229

Multiple regression analysis was conducted on

motivation and perceived social support to predict

retention in order to answer the main question of this

research (table 7). Both variables predict retention

significantly, (R

= .546, p = .000).

Then, the analysis continued with multiple

regression on the aspects of each variable of

motivation and perceived social support towards

retention. In table 8, these six aspects predict

retention significantly, and slightly better than

previous model, (p = .000, R

= .675). From the six

aspects (table 9), only intrinsic motivation and

perceived support from significant others, friends and

family significantly contribute to retention.

Predicting Retention: Sociodemographic, Motivational, and Perceived Social Support Factors

Table 7: Multiple Regression Motivation and Support to

Retention.

Model R R

Adjusted

Std. Error

of the

Estimate

Sign.

1 .739

.546 .542 .465312 .000

Table 8: Multiple Regression Aspect of Motivation and

Support to Retention.

Model R R

Adjusted

Std. Error

of the

Estimate

Sign.

1 .822

.675 .667 0,397192 .000

Table 9: Sign for Regression per aspect motivation and

support to Retention.

ect of Motivation and Su

ort Si

Extrinsic Motivation .604

Intrinsic Motivation 0

A motivation .092

ort from si

nificant others .005

ort from friends .015

ort from famil

In addition to the results mentioned above, it was

also found that between women and men have

significant score differences in amotivation (reversed

score) (t(47.837)=2.206, p = .032) and perceived

social support from significant other (t(227)=2.292,

p=.023). Regarding amotivation, women (mean =

6.108, SD = 1.041) tend to have clearer purpose than

men (mean=5.575, SD=1.453). Similarly, regarding

other significant aspects of variable perceived social

support, women (mean = 5.890, SD = 1.097) feel

more supported by significant other than men (mean

= 5.450, SD = 1.124).

Students whose mothers work also have higher

scores on motivational variables, especially on

intrinsic motivation (mean

working mothers

= 6.050, SD =

.651, mean

mothers notworking

= 5.747, SD = 805;

t(194.926) = 3.074, p=.002) and extrinsic motivation

(mean

working mother

= 6.101, SD = .806, mean

mother

notworking

= 5.583, SD = 900; t(226) = 2.355, p=.019),

but there is no difference in amotivation. In addition,

students whose mothers work also have higher scores

on retention in aspects related to themselves

(mean

working mother

= 5.737, SD = .817, mean

mother

notworking

= 5.371, SD = 909; t(226) = 3.204, p=.002),

but not in other aspects.

The findings of this study showed that

psychological variables in the form of motivation and

perceived social support directly predict students

retention at University X. Results of this study are in

line with Morrow and Ackermann (2012), Slanger et

al. (2015), and Xiong et al. (2015), while the link

between social support and retention is in line with

Flynn's research (2014). Without exception, male and

female students show a similar tendency for retention

due to the presence of motivation and perceived

social support that gives them the strength to

persevere. Additionally, through this study we can

also see the difference between men and women in

terms of academic goals, i.e., women have a clearer

purpose. This findings is in line with Richardson et al.

(2012). There is a clearer goal, which cause female

students to be motivated from the beginning of their

studies, hence spending more time learning and

working harder in completing academic tasks than

male students.

Further research on relationship of motivation and

perceived social support with student retention at

University X conducted tests with regression analysis

on the three aspects of motivation and the three

aspects of perceived social support. As a result, even

the six aspects of motivation and perceived social

support significantly predict retention, but more

specifically, intrinsic motivation and support coming

from family and friends are stronger factors in

predicting student retention at University X. This

means that

growing intrinsic motivation in first-year

students cannot be separated from the influence of

family and friends support, thus further strengthening

the student's desire to maintain his or her status as a

student at University X.

Other findings how motivation can predict

retention, was obtained after analysis of the factors

covered in sociodemographic variables. As stated in

the previous section, intrinsic motivation and

perceived social support from the family become

good predictors of retention. Although

sociodemographic factors are not directly related to

retention, economic status of the family and maternal

education show a positive relationship with

motivation. Economic status and mother education

level are comes from outside the student, which in the

mechanism of the psychological process will be

internalized into a force that fosters intrinsic

motivation.

According to Tinto (2017), motivation can be

built, enhanced, or weakened by student life

experience. The family's economic status will

facilitate the

financial availability of the

instrumentals needed by students during college. The

need for a guaranteed learning can foster a sense of

calm, confidence, ensured economic stability will

provide emotional safety. Hence students can focus

only finishing they study, and intrinsic motivation for

ICE-HUMS 2021 - International Conference on Emerging Issues in Humanity Studies and Social Sciences

retention is increasingly maintained. Meanwhile, the

link between

mother education and student

motivation can be explained as well. Mother

education can inspire and encouraged to be more

ambitious with their education. The availability of

financial resources combined with the level of

maternal education becomes an intrinsic motivation

that is strengthen student retention in the study

program it pursues.

For gender factors, it generally does not show the

difference between male and female in all variables

measured, but it is not so when viewed in every aspect

of each variable. Men and women tend to differ in the

amotivation factor [reversed] and perceived social

support to significant others, i.e., women are higher

than men. Women with high amotivation [reversed]

tend to see themselves as competent in undergoing

academic activities to feel happy and proud of their

achievements because they are the result of hard work

behavior and seriousness. It could also be that higher

amotivation [reversed] in female students is likely to

have something to do with perceived social support,

especially from whom they perceived as their

significant others. Amotivation [reversed] and social

support from significant others become significant

factors on female students retention.

Although this study successfully tested

psychological and nonpsychological variables in

student retention, it did not mean that it has no

weakness. It mainly occurred because this retention

study was only conducted at one college, students

who were participants in the study were less varied

based on the study program, and still needed to

examine the extent to which the results of significant

sociodemographic factors had a relationship with

motivation and perceived social support this

illustrates the actual condition of the retention

phenomenon at this university.

4 CONCLUSIONS

Student retention at University X is directly predicted

by psychological variables, namely motivation and

perceived social support. In detail, significant aspect

in motivation is intrinsic motivation, while perceived

social support predicts retention in all of its three

aspects. Further analysis of sociodemographic

variables, albeit not directly some variables, such as

socioeconomic status and mother education, are

correlated to intrinsic motivation and perceived social

support. Meanwhile, the analysis of gender shows

difference between men and women. Women had

clearer academic objectives, showed a higher aspect

of amotivation, and felt a higher sense of support. The

extent to which these results can be generalized in

other universities still needs to be investigated. A

more comprehensive study should involve

sociodemographic factors, more research participants

from different programs, and universities.

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