Islamic Guidance and Counseling Journal
https://journal.iaimnumetrolampung.ac.id/index.php/igcj
How to cite:
Mutiah, D., Paulina, M., & Putra, M. D. K. (2023). Psychosocial Factors Affecting Self-Regulated Learning
among Indonesian Islamic College Students: The Mediating Role of Perception Feedback. Islamic
Guidance and Counseling Journal, 6(2). https://doi.org/10.25217/0020236369200
E-ISSN: 2614-1566
Published by: Institut Agama Islam Ma’arif NU (IAIMNU) Metro Lampung
Psychosocial Factors Affecting Self-Regulated
Learning among Indonesian Islamic College
Students: The Mediating Role of Perception
Feedback
Diana Mutiah1*, Melisa Paulina2,
Muhammad Dwirifqi Kharisma Putra3
1 Universitas Islam Negeri Syarif Hidayatullah Jakarta, Indonesia
2 Universitas Islam Negeri Raden Fatah Palembang, Indonesia
3 Universitas Gajah Mada, Indonesia
diana.mutiah@uinjkt.ac.id*
Article Information:
Received May 25. 2023
Revised June 3, 2023
Accepted June 26, 2023
Keywords: perception feedback;
self-efficacy; self-regulated
leaning; social support
Abstract
In facing various problems during the online learning process, individuals
need to have self-regulated learning to be able to undergo online lectures
optimally and effectively. Hence, student’s knowledge increases and
learning objectives are achieved. This study aims to investigate the
mediating effect of self-efficacy in the relationship between perception
feedback on self-regulated learning in undergraduate students. Whether
the mediation had varying effects on different age levels and sex
differences was also examined. The sampling technique used in this study
is a non-probability sampling with 410 students. This study uses a
quantitative approach with path analysis. In this study, researchers used
confirmatory factor analysis (CFA) using Lisrel 8.8 to test the construct
validity of theinstrument. The results showed that there was a direct effect
from the independent variables, namely self-efficacy, family support, and
an indirect effect through mediator variables, namely self-efficacy, family
support, friend support, and gender. The effect of self-efficacy and family
support is partial mediation on self-regulated learning. While the variables
of peer support and gender demographic variables have a perfect
mediating effect on self-regulated learning with perception feedback as a
mediator.
INTRODUCTION
The problems that exist in online learning are caused by several factors, one of which is
the unpreparedness of various aspects, such as educators, regulation, and infrastructure.
Consequently, the implementation of online learning was not optimal (Fata et al., 2021; Rahayu
et al., 2022). In carrying out online learning, students need to have self-regulated learning (SRL)
because they have to be responsible for their learning process (Mou, 2021). The SRL refers to
the process of continuously monitoring and controlling one’s learning (Vandenbos, 2016). SRL
can be defined as thoughts, feelings, and behaviors that are self-generated and oriented towards
achieving goals, and requires the ability to believe in themselves (Zimmerman, 2002).
Furthermore, self-efficacy is an internal factor that influences from within a person, so the
development of the SRL occurs in managing, and regulating the process of changing learning
https://journal.iaimnumetrolampung.ac.id/index.php/igcj
https://doi.org/10.25217/0020236369200
mailto:diana.mutiah@uinjkt.ac.id
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
2 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
from offline to online (Kuo et al., 2014; Stephen & Rockinson-Szapkiw, 2021). Thus, self-
efficacy can be said to be a belief in individuals to solve their problems during the pandemic.
Self-efficacy is crucial for students because it makes student solve their problems or task
easier. A person with a high level of self-efficacy will focus more on finding solutions to
problems than thinking about the shortcomings that exist (Graham, 2022). Previous research
found that the level of self-efficacy was found to be correlated with the level of the SRL among
Indonesian students during the Covid-19 pandemic (Ulfatun et al., 2021). Additionally, the
higher self-efficacy correlated positively with students’ level of SRL (Wijaya et al., 2020). In
parallel, based on the findings from research on Chinese students, individuals who have higher
self-efficacy tend to show more effort. Simply put, there is a positive relationship between self-
efficacy and SRL in students (Sun & Wang, 2020).
SRL is also influenced by external factors such as social support. Social support is the
provision of assistance or comfort to others, typically to help individuals cope with their
biological, psychological, and social stressors (Vandenbos, 2016). Based on research conducted
by Triwahyuni et al. (2021) there is a positive and significant relationship between social
support and the SRL during the Covid-19 pandemic. In addition, Arjanggi (2019) stated that
the higher the social support, the higher the student's SRL ability. Also, social support is found
as a predictor to increase SRL in online learning (Carter et al., 2020).
However, besides internal and external factors, SRL was also influenced by demographic
variables such as age and gender. Age and gender were re-examined in this study as
demographic variables, with the fact that there are gaps that need to be filled since another
research conducted by Zhao et al. (2014) on 2738 subjects (1630 men and 1108 women). This
study found that men tend to score higher than women, although it should be noted that younger
people had better planning, regulation, and evaluation compared to the older ones.
In contrast, Wijaya et al. (2020) found that women's SRL level was higher than men's
during the Covid-19 pandemic. Pantu (2021) in his research conducted on 296 students in
Indonesia found that age affects SRL. The results show that the older an individual, the higher
the SRL. Edisherashvili et al. (2022) revealed that various age groups had higher SRL. Based
on this research, further research is necessary to examine the role of age and gender on SRL.
Self-efficacy and social support, as well as demographic variables such as (age and
gender), affect SRL significantly. The research conducted by Oktariani et al. (2020) shows that
self-efficacy and social support provides a significant positive relationship to student SRL.
Then, Daharnis (2018) in their research on 226 subjects show that there is a significant
relationship between self-efficacy and social support which together affect SRL.
In addition, in forming the SRL, communication is also needed to inform the accuracy of
what is done. Through feedback, students can receive suggestions about their weaknesses in
learning so they can improve their performance. When students can self-evaluate and
understand the feedback that has been given, the learning objectives can be achieved (Aldowah
et al., 2019). This indicates that perception feedback can also be a mediator between social
support in influencing SRL. Ekholm et al. (2015) found that perception feedback can be a
mediator variable between self-efficacy and SRL. And there is a significant relationship
between self-efficacy and SRL which is mediated by perception feedback. Perception feedback
is defined as a student's thought response and openness to receiving feedback about assignments
(Tadlock et al, 2008). Perception feedback refers to students' thoughts about the content of
feedback provided by external sources in terms of cognitive, metacognitive, motivational, and
affective reactions. High perception feedback is characterized when individuals can receive
suggestions about their learning from teachers or peers.
The research conducted by Wong et al. (2019) shows that feedback on activities is
reflective, and reinforces the positive effects that support SRL. Perception feedback can vary
depending on the content of the feedback and can be in the form of evaluative and informative
Mutiah, D., Paulina, M., & Putra, M. D. K.
3 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
communication so that feedback has an effect as a mediator (Strijbos et al., 2021). Perceptions
between male and female students are differ, female students have higher scores than men in
the field of friendliness, verbal and non-verbal communication. Thus, perception feedback can
also be a mediator between gender variables in influencing SRL. Also, providing good feedback
can improve SRL. Through feedback, students can accept suggestions and shortcomings in
learning so that there are efforts to carry out SRL. According to Mou (2021) regular feedback
can develop SRL in students.
SRL is a very important and interesting variable for further research. In this study,
researchers will examine the role of internal factors, such as self-efficacy, and external factors,
such as social support and demographic factors that affect SRL in online learning. Hence, the
researchers took the title "Psychosocial Factors Affecting Self-Regulated Learning among
Indonesian Islamic College Students: The Mediating Role of Perception Feedback".
Rationale of The Study
The impact of the Covid-19 pandemic is a multidimensional problem faced by various
sectors, one of them being the education sector. Online learning during the Covid-19 pandemic
caused a decrease in the quality of learning for students (Sahu, 2020). Such as reduced formal
learning hours, and a lack of e-learning facilities that can be used in the learning process
(Sintema, 2020). Argaheni (2020) states that there are problems faced by students in dealing
with online learning including ineffective discussions, many students who are not actively
participating in lectures, and stressing students mentally. The difficulty of running online
learning becomes difficult, especially for universities that do not yet have an online-based
academic system, and the quality of the internet network is not evenly distributed throughout
Indonesia.
In facing various problems during the online learning process, individuals need to have
the SRL to be able to undergo online lectures optimally and effectively, so that student’s
knowledge increases and learning objectives are achieved. In this case, students are required to
be able to regulate themselves or apply the SRL in achieving the desired learning objectives.
The SLR can help students carry out their learning (Mou, 2021). There are so many research
that has been conducted on SLR, but in Indonesia, research on the SRL among Islamic students
during the online learning period is still limited, it is only centered on general students.
Purpuses of the study
In general, this study aims to determine the effect of self-efficacy, social support, and
demographic variables on the SRL at Universitas Islam Negeri Raden Fatah Palembang (UIN
Palembang) during a COVID-19 pandemic. In particular, we postulated that the relationship
between independent variables and dependent variable is mediated by perception feedback as
mediator variable. Simply put, we want to examine whether there are direct and indirect effects
on the SRL.
Research Hypotheses
This research aims to investigate the effect of the independent variable on the dependent
variable. Then, the analysis is carried out to see whether the variation in the relationship
between the two variables is influenced by the mediator variable. Based on this description, the
hypothesis proposed in this study is:
H1: There is an influence of self-efficacy, social support, and demographic variables
(gender and age) on the SRL in students mediated by perception feedback fitted by
data.
H2: There is a joint effect of self-efficacy, social support, and gender demographic
variables on the SRL.
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
4 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
There is a direct or indirect effect of self-efficacy on the SRL.
H4: There is a direct or indirect influence of family support on the SRL.
H5: There is a direct or indirect effect of peer support on the SRL.
H6: There is a direct or indirect influence from significant others on the SRL
H7: There is a direct or indirect effect of gender on the SRL.
H8: There is a direct effect of age on the SRL.
METHODS
Research Design
This study uses a quantitative approach with a cross-sectional design to see the
relationship between independent variables and dependent variables. The dependent variables
in this study are the SRL and the independent variables are self-efficacy, social support, and
demographic variables (gender and age). And the mediator variable is perception feedback. The
instrument used in this study was an online questionnaire through the Google form with the
Likert scale method. Then, participants were asked to choose one of the available response
options according to what the participants felt or experienced. The measuring instrument in this
study is an adaptation measurement tool that has been tested by previous researchers. In this
study, the data about independent variables and dependent variables are collected
simultaneously and allow for potraying the relationships between variables at one time.
Population and the Methods of Sampling
The subjects on this study were students of UIN Palembang. The reason the authors took
UIN Palembang students as respondents was because according to the preliminary study
conducted by the researcher, there were problems related to the importance of the SRL. Second,
during the pandemic, students are required to be able to carry out the SRL so that they can adapt
to changes and new rules. Third, the student learning method is student centered, which means
students are required to be more active in the learning processes.
The active student population of the Faculty of Psychology UIN Palembang is 809
students. The sample size used in this study was 410 students. The sampling technique used is
a non-probability sampling technique. In this technique, each element in the population does
not have the same opportunity to be sampled (Sugiyono, 2011). The sample criteria in this study
are as follows: 1) Active student of the Faculty of Psychology UIN Raden Fatah Palembang,
2) Take online lectures, and 3) Willing to volunteer to be research subjects.
The rule of thumb that we used to determine the minimum sample size is as follows:
150 - 315 respondents (Muthén & Muthén, 2002). Based on this rule of thumb, the minimum
number of respondents in this study has exceeded the minimum sample size for conducting
path analysis.
Instrumentation
The measuring tool used in this study was an online questionnaire via the Google form
with the Likert scale method which consisted of 4 categories from Strongly disagree (1) -
Strongly agree (4). This scale consists of favorable items and unfavorable items, with different
scores. On the favorable item, the highest score is given to strongly agree, and strongly disagree
is given a low score. Then, participants were asked to choose one of the available response
options according to what the participant felt or experienced. We used confirmatory factor
analysis (CFA) to check the construct validity of the instruments. We used two indices to
conduct the test of goodness of fit, namely Chi-square and root-mean-square error of
approximation (RMSEA). We used Chi-square closer to zero (p > .05) and RMSEA < .05 as
model fit criteria (Brown, 2015).
Mutiah, D., Paulina, M., & Putra, M. D. K.
5 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
In this study, we used four psychological scales. First, by Measuring self-regulation
online which was developed by Barnard et al. (2009). The SROL is self-regulated online
learning scale consisting of 24 items. The SROL consists of six subscales including
environmental structuring; goal setting; time management; seeking help; task strategy; and self-
evaluation. This scale was tested for validity using the CFA method. In the first analysis, Chi-
square = 2103, p-value = .000, RMSEA = .134. By looking at the P-value less than .05 and
RMSEA greater than .05, it can be concluded that the model is not fit.
Modifications were made to free measurement error parameters in the model. After 110
modifications, Chi-square = 157, df = 133, p-value = .069, RMSEA = .021 were obtained.
Judging from the large P-value of .05 and the RMSEA value of less than .05, it can be concluded
that the model can be said to be fit. After the fit model is obtained, the next step is to look at
the significance of the item validity, namely whether each item is significant in measuring the
variable to be measured, namely the SRL. The significance of the item can be seen from the t-
value of the loading coefficient which is positive and the t-value is more than 1.96. The results
show that all items in the SROL are valid.
Second, the self-efficacy variable is measured by the general self-efficacy scale-12
(GSES-12) (Bosscher & Smit, 1998). This instrument consists of 12 items. This scale was tested
for validity using the CFA confirmatory factor analysis method. The results of the first analysis
show Chi-square = 1070.02, p-value = .00000, and RMSEA = .214. Based on the P-value which
is still less than .05 and the RMSEA which is greater than 0.05, it can be concluded that the
model is not fit, so it needs to be modified to the model.
Modifications were made to free measurement errors for each item. And after 20
modifications, we obtained Chi-square = 43.31, df = 34, p-value = .131, and RMSEA = .026.
Judging from the large P-value of 0.05 and the RMSEA value of less than 0.05, it can be
concluded that the model is fitted with the data. After the fit model is obtained, the next step is
to test the validity of the items. Based on the results of the analysis, it is known that all GSES-
12 items are valid because all of the items have a t-value > 1.96 and the factor loading
coefficient is positive. In other words, all items in GSES-12 are valid and can be used for the
next analysis.
Third, the social support variable is measured using the multidimensional scale of
perceived social support (MSPSS) (Zimet et al., 1988). The first dimension is family support.
Testing the validity of the family support scale was carried out to test whether the 4 items in
this scale are unidimensional, which means that they only measure one variable, namely family
support. This scale was tested for validity using the confirmatory factor analysis (CFA) method
which was tested using Lisrel 8.80 software. The first analysis using Lisrel 8.80 software
obtained Chi-square = 21.92, P-value = .00002, RMSEA = .156. By looking at the P-value less
than 0.05 and RMSEA which is more than .05, it can be concluded that the model is not fit.
Modifications were made to free measurement error parameters. After 1 modification,
Chi-square = 1.00, df = 1, p-value = .316, RMSEA = .003 was obtained. Judging from a P-
value greater than 0.05 and an RMSEA value of less than .05, it can be concluded that the model
is fitted with the data. After the model fit is obtained, the next step is to examine the significance
of the item validity, namely whether each item is significant in measuring the variable to be
measured, namely family support. The significance of the item can be seen from the factor
loading coefficient which is positive and the t-value is more than 1.96. Based on the results of
the analysis it is known that all of the dimensions of family support are valid. So that these
items meet the criteria for use in the next analysis.
The validity test of the peer support scale was carried out to test whether the four items
in this scale are unidimensional, which means that it only measures one variable, namely peer
support. The first analysis show Chi-square = 4.04, p-value = .1325, and RMSEA = .05. Based
on these results, it can be concluded that the model is fitted with the data. After the fit model is
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
6 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
met, the next step is to examine the significance of item validity. The significance of the item
can be seen from the t-value of the loading coefficient which is positive and the t-value is more
than 1.96. Based on the results of the analysis, it appears that all items of the peer support are
valid. Thus, these items meet the criteria for the next analysis.
The validity test of the significant others scale was carried out to test whether the 4 items
in this scale are unidimensional, which means that they only measure one variable, namely
significant others. In the first analysis, Chi-square = 34.21, p-value = .0000, RMSEA = .198.
By looking at the p-value less than .05 and RMSEA which is more than .05, it can be concluded
that the model is not fit. Then, modifications were made to free measurement errors for each
item to be correlated with each other. After 2 modifications, Chi-square = .00, df = 0, p-value
= 1.00000, RMSEA = .000 is obtained. Judging from the large p-value of .05 and the RMSEA
value of less than .05, it can be concluded that the model is fitted with the data.
After the fit model is met, the next step is to investigate the significance of the item
validity, namely whether each item is significant in measuring the variable to be measured,
namely significant others. The significance of the item can be seen from the t-value of the
loading coefficient which is positive and the t-value is more than 1.96. Based on the analysis,
it is known that the factor loading coefficient of significant others is positive and significant, so
all item meets the criteria for analysis in the next stage.
Lastly, the perception feedback variable was measured using the Feedback Perceptions
Questionnaire (FPQ) developed by Strijbos et al. (2021) consists of 18 items. Perception
feedback consists of 18 unidimensional items. The FPQ consists of five sub-scale constructs,
namely fairness, usefulness, acceptance, willingness to improve, and affect. In the first analysis,
Chi-square = 3022.26, P-value = .00000, and RMSEA = .229. By looking at the P-value less
than 0.05 and RMSEA which is more than .05, it can be concluded that the model is not fit.
Modifications were made to free measurement errors for each item to correlate with each
other. After 55 modifications, Chi-square = 99.95, df = 81, p-value = .075, RMSEA = .024 were
obtained. Judging from the large P-value of .05 and the RMSEA value of less than .05, it can
be concluded that the model is fitted with the data. After the model fit is met, the next step is to
test the significance of item validity. The significance of the item can be seen from the value of
the factor loading coefficient which is positive direction and the t-value is greater than 1.96.
Based on the results of the analysis, it was found that all significant others items were declared
valid.
After all, items are tested for validity using CFA. Items on the instrument that have been
proven valid are used to calculate the factor score. Factor score is an estimate of the quantitative
value that an individual would have on a latent variable were it possible to measure this directly
(Vandenbos, 2016). Simply put, the factor score is the score that the researcher will later use to
carry out path analysis. The factor score in this study was computed using SPSS 23 software.
Data Analysis
For descriptive statistics, the Statistical Package for the Social Sciences 23 (SPSS 23) by
IBM was used with significance accepted if p < .05. There was no problem with missing data
as the statements of each online questionnaire needed to be 100% complete before continuing
to the next section of questionnaires. The data distribution was checked through skewness and
kurtosis to control how much the variables diverge from the normal distribution (Morgan &
Griego, 1998).
The hypothesis testing was conducted by the path analysis approach using the Lisrel
software version 8.8 (Jöreskog et al., 2006) with maximum likelihood estimation method. Path
analysis is a variation of multiple regression analysis which is used to analyze causal
Mutiah, D., Paulina, M., & Putra, M. D. K.
7 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
relationships and determine direct and indirect effects simultaneously between the independent
variables and the dependent variable (Stage et al., 2004). In using path analysis, we used several
fit indices, such as, the root mean square error of approximation (RMSEA), 90% C.I. for
RMSEA, probability RMSEA, comparative fit index (CFI), and Tucker–Lewis index (TLI).
Based on published criteria (LT Hu & PM Bentler, 1999), the following standards for good fit
were used: CFI > .95, TLI > .95, RMSEA < .05, 90% C.I. for RMSEA < .05, and probability
RMSEA > .05. After it has been proven that the model is fitted with the data, then we testing
the hypothesis of whether each direct and indirect effect is statistically significant. It can be
done by looking at the t-value (z > 1.96) and significant level (p < .05).
RESULTS AND DISCUSSION
Results
The sample size in this study is 410 participants. The subjects of this study were active
undergraduate students (S1) of the Faculty of Psychology, Universitas Islam Negeri Raden
Fatah Palembang. An overview can be seen in table 1. From the table 1 it can be seen that
perceptual feedback has the lowest score of 6.77 and the highest score of 63.15. The SRL has
the lowest score of 8.24 and the highest score of 68.07. Self-efficacy has the lowest score of
18.37 and the highest score of 64.80. The social support variable, the family support dimension,
has the lowest score of 22.94 and the highest score of 59.47 and the dimension of friend support
has the lowest score of 23.01 and the highest score of 61.43 and the significant other dimension
has the lowest score of 37.85 and the highest score of 49.9. Next overview can be seen in table
2. Model summary.
From the table above, we can see that the R2 coefficient is .459 or 45.9%. It can be
interpreted that the proportion of variance for each independent variable affects 45.9% on the
SRL while the other 54.1% is influenced by other variables outside of this study. After testing
the model, the coefficient RMSEA = .30, 90% C.I. = .0 - .14 (lower limit < .05), and probability
for RMSEA= .45, (p > .05). Hence, it can be concluded that the model meets the fit criteria. A
summary of the model fit test can be seen in table 3 below and the model diagram that has been
proven fit can be seen in figure 1. After all the criteria for the model fit are met, the next step is
to examine the direct effect between variables. The following standardized coefficients are
summarized in table 4 as follows.
From the table above we can find out some important points, such as: First, the self-
efficacy has a positive and significant effect with a coefficient of .21 on the SRL. It can be seen
from z-value = 5.07 (z > 1.96). It means that self-efficacy directly affects the SRL significantly.
It can be interpreted as the higher the self-efficacy, the higher the SRL. Second, the family
support has a positive and significant relationship with a coefficient of .20 on the SRL. It can
be seen from the z-value = 4.50 (z > 1.96). It means that family support directly affects the SRL
Table 1. Descriptive Statistics
Variabel N Min. Max. Mean Std Deviation
Perception feedback 410 6.77 63.15 50 9.6
Self regulated learning 410 8.24 68.07 50 9.5
Self efficacy 410 18.37 64.80 49.9 9.4
Family Support 410 22.94 59.47 49.9 9.4
Friends Support 410 23.01 61.43 50 9.0
Significant others 410 37.85 62.92 49.9 9.7
Table 2. Model summary
Model R R-Square Adjusted R-Square Std. Error
1 .677a 0.459 0.449 7.09061
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
8 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
significantly. It can be interpreted as the higher the family support, the higher the SRL. Third,
the friends' support has a positive and insignificant relationship with a coefficient of .08 on the
SRL.
Figure 1. Model diagram
Note: SE = Self-efficacy; FS1 = Family support; FS2 = Friend support; SO = Signicant others;
PF = Perception feedback; SRL = Self-regulated leaning
Table 3. Model fit Indices
Indices Value Estimate Model Evaluation
RMSEA < .05 .30 Acceptable fit
90% C.I < .05 .00 - .14 Acceptable fit
Probability RMSEA > .05 .45 Acceptable fit
CFI 1 1 Acceptable fit
TLI 1 1 Acceptable fit
Table 4. Coefficient of Direct Effect Between Variables
Path Coefficient S.E Z-Value Note
SE SRL .21 .04 5.07 Significant
FS1 SRL .20 .05 4.50 Significant
FS2 SRL .08 .04 1.83 Not Significant
SO SRL .06 .04 1.62 Not Significant
Gender SRL .06 .04 1.63 Not Significant
Age SRL .06 .04 1.60 Not Significant
It can be seen from the z-value = 1.83 (z > 1.96). It means that the support of friends does
not directly affect the SRL. Fourth, the significant others have a positive and insignificant
relationship with a coefficient of .06 on the SRL. It can be seen from the z-value = 1.62 (z >
1.96). It means that significant others do not directly affect the SRL. Fifth, gender has a positive
and insignificant relationship with a coefficient of .06 on the SRL. It can be seen from z-value
= 1.63 (z > 1.96). It means that gender does not directly affect the SRL. Lastly, the age variable
has a positive and insignificant relationship with a coefficient of .06 on the SRL. It can be seen
from the z-value = 1.60 (z > 1.96). It means that age does not directly affect the SRL.
In the next steps, the researchers examine the indirect effect of the variables of self-
efficacy, social support (family support, friend support, and significant others), and gender
effect on the SRL through the mediator variable perception feedback. The results of the indirect
effect can be summarized in table 5 below.
Mutiah, D., Paulina, M., & Putra, M. D. K.
9 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
Table 5. Indirect Effect Between Variables
Path Coefficient S.E Z-Value Note
SE PF SRL .28 .04 6.50 Significant
FS1 PF SRL .27 .05 5.71 Significant
FS2 PF SRL .24 .05 5.28 Significant
SO PF SRL .00 .04 -0.06 Not Significant
Gender PF SRL .09 .04 2.14 Significant
Based on the table above, it can be seen that five indirect paths affect the SRL, such as:
First, self-efficacy has a significant and positive influence with a coefficient of .28 on the SRL
indirectly through the mediator variable perception feedback, this can be seen from the z-value
= 6.50. Second, the family support has a significant and positive effect with a coefficient of .27
on the SRL through the mediator variable perception feedback, this can be seen from the value
of z-value = 5.71. Third, the friends' support variable has a significant and positive effect with
a coefficient of .24 on the SRL through the mediator variable perception feedback, this can be
seen from the z-value = 8.28. Fourth, the significant others variable has an insignificant
influence on the SRL through the mediator variable perception feedback. This can be seen from
the value of z-value = - .06. Lastly, the gender variable has a significant and positive effect with
a coefficient of .09 on the SRL indirectly through the mediator variable perception feedback,
this can be seen from the value of z-value = 2.14.
Discussion
Following the purpose of this study which aims to investigate the path analysis model of
the SLR which is theorized based on the results of research data, the final model is obtained as
shown in figure 2 below.
Figure 2. Final model
Note: Red Line = Not significant; Black Line = Significant
The model explains how the relationship between variables has an effect on the SRL,
both directly and indirectly using path analysis as an added value in this study. Some of the
variables predicted to affect the SRL are self-efficacy, social support (family support, friends
support, significant others), and demographic variables (gender and age) through perception
feedback as a mediator variable. Based on the results of the research that has been carried out,
the variable that has the strongest influence on the SRL, both directly and indirectly, is self-
efficacy. It can be interpreted as the higher the individual's self-efficacy, the higher the SRL.
These findings align with several previous research. For example, self-efficacy is an internal
factor to affect the SRL. These findings are in line with the research results of Daharnis (2018)
stating that there is a significant relationship between self-efficacy and social support which
together affect the SRL.
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
10 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
Another finding in this study is the discovery of the significant effect of social support on
the SRL. More specifically, the significant variable is the dimension of social support called
family support. The data shows that the higher the family support, the higher the SRL. This
finding is in line with a study conducted by Oktariani et al. (2020) shows that self-efficacy and
social support together provide a significant positive relationship with the SRL.
In this study, it was also found that perception feedback is a variable that can bridge the
causal relationship between self-efficacy and the SRL. These findings are in line with the study
conducted by Ekholm et al. (2015) who found that perception feedback is a mediator between
self-efficacy and the SRL. When students can self-evaluate and be aware of the feedback given
by people around them, such as teachers, family, friends, and other people around them, then
the learning objectives can be achieved (Aldowah et al., 2019).
This shows that perception feedback can also be a mediator between social support
variables affecting the SRL. In the results of this study, the social support variable, the
significant others dimension, does not have a significant relationship either through direct
influence or through a mediator. Significant other in this study is the form of support from
special people outside the scope of family and peers or in other terms the support of lovers
(boyfriends or girlfriends). It is not significant because most Islamic students do not date. After
all, it is under one of the visions of the UIN Palembang is about Islamic character. It means that
unmarried Islamic students are more careful not to date or have lovers who are not halal.
In addition, there were also research findings regarding descriptive statistics of the SRL,
self-efficacy, social support, and perception feedback made by students during online learning.
The SRL is done by students in online learning by structuring the environment, setting goals,
time management, seeking help, task strategies, and self-evaluation (Barnard et al., 2009). In
the arrangement of the environment, students choose the right location to avoid noise, choose
the time with the least disturbance and find a comfortable and efficient place to study online.
Setting student goals in online learning is done by setting goal standards, setting GPA standards
above 3.0, making long-term goals, and making a list of achievement targets for online lectures.
In addition, students also carry out task strategies in the form of taking careful notes during
online lectures, reading lecture instructions, preparing questions, and reading a lot during online
lectures.
Time management is done by setting specific time allocations for online learning, making
daily and weekly schedules, and trying to learn every day. With the SRL, it does not mean that
students do not need the help of others, but with the SRL, students know the suitable help for
themselves. As the results of this study, students find the right person to consult, try to get help
from lecturers through online media, and share problems with classmates to find solutions.
Furthermore, self-evaluation, during the online learning period, the form of self-evaluation
carried out by students was summarizing online learning materials, asking themselves about
understanding the material, and communicating with classmates to find differences in
understanding in online learning. Students' self-efficacy during online learning is on average in
the medium category. Self-efficacy consists of three dimensions, namely initiative, effort, and
persistence (Bosscher & Smit, 1998). The form of student initiative during online learning is to
keep learning and not give up studying online lecture material that looks complicated.
Furthermore, the efforts made by students are making plans to complete online lecture
assignments, and continuing to try to understand material that has not been understood, even
though online lectures are not fun, students continue to attend online lectures and directly do
the assignments given by the lecturer, and for student’s failure only makes them try even harder.
Persistence is an individual's persistence in facing difficulties, during online learning students
try to be persistent, this can be seen when students can overcome existing problems, can handle
unexpected problems, and believe in themselves to be able to complete online lecture
assignments.
Mutiah, D., Paulina, M., & Putra, M. D. K.
11 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
As the results of previous studies reveal that during online learning, students need social
support to carry out the SRL. Social support consists of three dimensions, namely family
support, friend support, and significant others (Zimet et al., 1988). Based on the results of the
study, there were only two significant effects on self-regulated learning during the online
learning period, namely family support and friend support. Family support is given to students
in online learning in the form of help and emotional support and becomes a place for discussion
in making decisions. Unlike the case with the form of support from friends who always try to
solve problems, there is online learning and for students, peers are a place to share joys and
sorrows.
Based on the results of research on perception feedback, the average perception feedback
of students in online learning is in the medium or good category. Perception feedback consists
of five dimensions, namely fairness, usefulness, acceptance, willingness to improve, and affect.
In the fairness dimension, it can be seen that students feel satisfied, and fair and can consider
feedback given by external parties on their assignments. Furthermore, in the usefulness
dimension, students perceive the feedback given during online learning as useful and useful,
and through feedback, students feel they are supported. In the acceptance dimension, students
show acceptance and do not reject feedback given by external parties on their assignments.
Willingness to improve is an act of acceptance to take action on the development of abilities
and knowledge, in this dimension, students are willing to improve and take the time to make
improvements from the feedback provided. In the affected dimension, it can be seen that
students who were given feedback during the online learning period felt satisfied, felt
successful, and not feel offended or frustrated with the feedback given.
Implications
Based on this study, it was found that the factors that influence the SRL are self-efficacy
and social support (the dimension of family support). This finding has several very useful
implications for society. First, the importance of building high self-efficacy in students.
Because high self-efficacy can increase the chances of students having high SRL. Simply put,
students who have high confidence that they can achieve their goals will have a high level of
SRL.
Second, social support (the dimension of family support) has an influence on the SRL in
online learning. What can be done by the family is to provide students with emotional assistance
and support in making decisions. For peers, always sharing and providing support to one
another, such as helping to solve problems that exist during online learning and being a place
to share joys and sorrows. Therefore, in improving the SRL for Islamic students, it is highly
recommended that the surrounding environment, especially lecturers and practitioners can
convince students that they are capable of dealing with all the obstacles they face in carrying
out online learning.
Finally, based on this study, it was found that perception feedback is a variable that can
provide a mediating effect between social support and self-efficacy. Therefore, every student
must have a good level of perception feedback. By having good perception feedback, students
can receive suggestions about their weaknesses in learning, so they can improve their
performance in learning. In the end, the learning objectives are achieved.
Limitations and Suggestions for Further Research
This research still has many limitations and shortcomings. First, in this study, the method
used for data analysis is path analysis. In future studies, it is recommended to use more
sophisticated methods such as structural equation modeling (SEM). This is crucial because
SEM can directly correct measurement errors in the model (Raykov & Marcoulides, 2012). In
simple terms, by using SEM, researchers can get more precise parameter estimation results.
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
12 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
Second, in this study, social support scores are still broken down based on dimensions. Future
research should be able to carry out an analysis by combining all social support dimension
scores (family support, friends support, and significant others) into just one score (Ex: using
second-order CFA). By doing so, it is hoped that the researchers will have a more
comprehensive understanding of the influence of social support on the SRL. Lastly, the
independent variables in this study are self-efficacy, social support, and demographic variables
(gender & age). In future research, it is better to add other variables such as motivation or
teaching models which are postulated to influence the SRL.
CONCLUSION
The results showed that there was a joint influence of self-efficacy, social support, and
demographic variables on the SRL. The results showed that the self-efficacy variable affecting
the SRL was partial mediation. It means that either directly or through perception feedback as
a mediator variable, self-efficacy still has a significant and positive influence on the SRL. Then,
the results show that the effect of social support (dimensions of family support) on the SRL is
partial mediation. It means that either directly or through perception feedback as a mediator
variable, the dimensions of family support still have a significant and positive influence on the
SRL. Another result shows that the effect of social support (dimensions of friend support) on
the SRL is perfect mediation. It means that peer support has a significant and positive effect on
the SRL when there is perception feedback as a mediator variable. Simply put, peer support can
affect self-regulated learning only when the individual has perception feedback. Another
finding is that the influence of the social support variable (significant others dimension) does
not affect the SRL, either directly or through perception feedback as a mediator. Then, the
results showed that the male gender had higher self-regulated learning abilities than women.
Then, the gender variable affects the SRL which is perfect mediation. It means that the male
gender will have a positive and significant influence on the SRL, if the male gender has
perception feedback. Lastly, the age variable does not affect the SRL significantly.
ACKNOWLEGMENT
The researchers thank the respondents for their willingness to be the subject of collection
and to the reviewers the researcher hopes for suggestions that can add value to this paper.
AUTHOR CONTRIBUTION STATEMENT
DM is responsible for conceptual, writing and analysis. MP is responsible for interpreting
research and design results. MDKP is responsible for the analysis and interpretation of data
processing results.
REFERENCES
Aldowah, H., Al-Samarraie, H., & Ghazal, S. (2019). How Course, Contextual, and
Technological Challenges are Associated with Instructors’ Individual Challenges to
Successfully Implement E-Learning: A Developing Country Perspective. IEEE Access, 7,
48792–48806. https://doi.org/10.1109/ACCESS.2019.2910148
Argaheni, N. B. (2020). Sistematik Review: Dampak Perkuliahan Daring Saat Pandemi
COVID-19 Terhadap Mahasiswa Indonesia. PLACENTUM: Jurnal Ilmiah Kesehatan Dan
Aplikasinya, 8(2), 99. https://doi.org/10.20961/placentum.v8i2.43008
Arjanggi, S. D. dan R. (2019). Correlation Between Peer Social Support and Academic
Confidence With Self Regulated Learning in. Proyeksi, 14(1), 84–93.
http://dx.doi.org/10.30659/jp.14.1.84-93
Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S. L. (2009). Measuring self-regulation
https://doi.org/10.1109/ACCESS.2019.2910148
https://doi.org/10.20961/placentum.v8i2.43008
http://dx.doi.org/10.30659/jp.14.1.84-93
Mutiah, D., Paulina, M., & Putra, M. D. K.
13 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
in online and blended learning environments. Internet and Higher Education, 12(1), 1–6.
https://doi.org/10.1016/j.iheduc.2008.10.005
Bosscher, R. J., & Smit, J. H. (1998). Confirmatory factor analysis of the general self-efficacy
scale. Behaviour Research and Therapy, 36(3), 339–343. https://doi.org/10.1016/S0005-
7967(98)00025-4
Brown. (2015). Confirmatory factor analysis for applied research. In Guilford publications.
https://doi.org/10.5860/choice.44-2769
Carter, R. A., Rice, M., Yang, S., & Jackson, H. A. (2020). Self-regulated learning in online
learning environments: strategies for remote learning. In Information and Learning
Science (Vol. 121, Issues 5–6, pp. 311–319). https://doi.org/10.1108/ILS-04-2020-0114
Daharnis, A. C. P. H. N. S. (2018a). Hubungan Antara Self Efficacydan Dukungan Sosial
Orangtua Dengan Self Regulated Learning Serta Implikasinya Terhadap Bimbingan Dan
Konseling. ANSIRU PAI : Pengembangan Profesi Guru Pendidikan Agama Islam, 2(1),
46. https://doi.org/10.30821/ansiru.v2i1.1627
Daharnis, A. C. P. H. N. S. (2018b). Hubungan Antara Self Efficacydan Dukungan Sosial
Orangtua Dengan Self Regulated Learning Serta Implikasinya Terhadap Bimbingan Dan
Konseling. ANSIRU PAI : Pengembangan Profesi Guru Pendidikan Agama Islam, 2(1),
46. https://doi.org/10.30821/ansiru.v2i1.1627
Edisherashvili, N., Saks, K., Pedaste, M., & Leijen, Ä. (2022). Supporting Self-Regulated
Learning in Distance Learning Contexts at Higher Education Level: Systematic Literature
Review. Frontiers in Psychology, 12(January).
https://doi.org/10.3389/fpsyg.2021.792422
Ekholm, E., Zumbrunn, S., & Conklin, S. (2015). The relation of college student self-efficacy
toward writing and writing self-regulation aptitude: Writing feedback perceptions as a
mediating variable. Teaching in Higher Education, 20(2), 197-207..
https://doi.org/10.1080/13562517.2014.974026
Fata, Z., Su’ad, S., & Murtono, M. (2021). Pola Pembelajaran Guru Pada Masa Pandemi Corona
(Covid-19) Sd Negeri Kramat 3 Kecamatan Dempet Kabupaten Demak. In Profetika:
Jurnal Studi Islam (Vol. 22, Issue 1, pp. 109–118).
https://doi.org/10.23917/profetika.v22i1.14769
Graham, S. (2022). Self-efficacy and language learning–what it is and what it isn’t. Language
Learning Journal, 50(2), 186–207. https://doi.org/10.1080/09571736.2022.2045679
Jöreskog, K. G., Sörbom, D., & Yang-Wallentin, F. (2006). Latent variable scores and
observational residuals. Lisrel, 1996, 10.
http://www.ssicentral.com/lisrel/techdocs/obsres.pdf
Kuo, Y. C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet
self-efficacy, and self-regulated learning as predictors of student satisfaction in online
education courses. Internet and Higher Education, 20, 35–50.
https://doi.org/10.1016/j.iheduc.2013.10.001
LT Hu, & PM Bentler. (1999). Cutoff criteria for fit indexes in covariance structure analysis:
conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.
https://doi.org/10.1080/10705519909540118
Morgan, G. A., & Griego, O. V. (1998). Easy use and interpretation of SPSS for Windows:
Answering research questions with statistics (Vol. 1). Psychology Press. Google Scholar
Mou, T. Y. (2021). Online learning in the time of the COVID-19 crisis: Implications for the
self-regulated learning of university design students. In Active Learning in Higher
Education: Vol. students.1 (pp. 1–21). https://doi.org/10.1177/14697874211051226
Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample
size and determine power. Structural Equation Modeling, 9(4), 599–620.
https://doi.org/10.1207/S15328007SEM0904_8
https://doi.org/10.1016/j.iheduc.2008.10.005
https://doi.org/10.1016/S0005-7967(98)00025-4
https://doi.org/10.1016/S0005-7967(98)00025-4
https://doi.org/10.5860/choice.44-2769
https://doi.org/10.1108/ILS-04-2020-0114
https://doi.org/10.30821/ansiru.v2i1.1627
https://doi.org/10.30821/ansiru.v2i1.1627
https://doi.org/10.3389/fpsyg.2021.792422
https://doi.org/10.1080/13562517.2014.974026
https://doi.org/10.23917/profetika.v22i1.14769
https://doi.org/10.1080/09571736.2022.2045679
http://www.ssicentral.com/lisrel/techdocs/obsres.pdf
https://doi.org/10.1016/j.iheduc.2013.10.001
https://doi.org/10.1080/10705519909540118
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Morgan%2C+G.+A.%2C+%26+Griego%2C+O.+V.+%281998%29.+Easy+use+and+interpretation+of+SPSS+for+Windows%3A++Answering+research+questions+with+statistics.+Easy+Use+and+Interpretation+of+SPSS+for+Windows%3A++Answering+Research+Questions+with+Statistics.%2C+276%2C+iv%2C+276%E2%80%93iv.&btnG=
https://doi.org/10.1177/14697874211051226
https://doi.org/10.1207/S15328007SEM0904_8
Psychosocial Factors Affecting Self-Regulated Learning among Indonesian Islamic College Students:
The Mediating Role of Perception Feedback
14 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
Oktariani, O., Munir, A., & Aziz, A. (2020). Hubungan Self Efficacy dan Dukungan Sosial
Teman Sebaya Dengan Self Regulated Learning Pada Mahasiswa Universitas Potensi
Utama Medan. Tabularasa: Jurnal Ilmiah Magister Psikologi, 2(1), 26–33.
https://doi.org/10.31289/tabularasa.v2i1.284
Pantu, E. A. (2021). Pengaruh Usia Terhadap Regulasi Diri Akademik Mahasiswa Pada
Kondisi Study From Home. Jurnal Psibernetika, 14(1), 17–23.
http://dx.doi.org/10.30813/psibernetika.v14i1.2469
Rahayu, W., Putra, M. D. K., Faturochman, Meiliasari, Sulaeman, E., & Koul, R. B. (2022).
Development and validation of Online Classroom Learning Environment Inventory
(OCLEI): The case of Indonesia during the COVID-19 pandemic. Learning Environments
Research, 25(1), 97–113. https://doi.org/10.1007/s10984-021-09352-3
Raykov, T., & Marcoulides, G. A. (2012). A first course in structural equation modeling:
Second edition. In A First Course in Structural Equation Modeling: Second Edition (2nd
ed.). Lawrence Erlbaum Associates Publishers. Routledge.
https://doi.org/10.4324/9780203930687
Sahu, P. (2020). Closure of Universities Due to Coronavirus Disease 2019 (COVID-19): Impact
on Education and Mental Health of Students and Academic Staff. Cureus, 2019(4).
https://doi.org/10.7759/cureus.7541
Sintema, E. J. (2020). Effect of COVID-19 on the performance of grade 12 students:
Implications for STEM education. Eurasia Journal of Mathematics, Science and
Technology Education, 16(7), 1–6. https://doi.org/10.29333/EJMSTE/7893
Stage, F. K., Carter, H. C., & Nora, A. (2004). Path Analysis: An Introduction and Analysis of
a Decade of Research. Journal of Educational Research, 98(1), 5–13.
https://doi.org/10.3200/JOER.98.1.5-13
Stephen, J. S., & Rockinson-Szapkiw, A. J. (2021). A high-impact practice for online students:
the use of a first-semester seminar course to promote self-regulation, self-direction, online
learning self-efficacy. Smart Learning Environments, 8(1), 6.
https://doi.org/10.1186/s40561-021-00151-0
Strijbos, J. W., Pat-El, R., & Narciss, S. (2021). Structural validity and invariance of the
feedback perceptions questionnaire. Studies in Educational Evaluation, 68(vember).
https://doi.org/10.1016/j.stueduc.2021.100980
Sugiyono. (2011). Metodologi penelitian Kuantitatif kualitatif dan R&D. In Alpabeta. Google
Scholar
Sun, T., & Wang, C. (2020). College students’ writing self-efficacy and writing self-regulated
learning strategies in learning English as a foreign language. System, 90.
https://doi.org/10.1016/j.system.2020.102221
Tadlock et al. (2008). “How Writing Feedback Perceptions Relate to Pre- service Teachers’
Achievement Goals and Self-regulation Behaviors.”. Paper Presented at the Eastern
Educational Research Association Annual Meeting, Hilton Head, SC. Google Scholar
Triwahyuni, H., Zaqiyuddin, M., Chalimy, F., & Mufidah, W. (2021). Dukungan Sosial Dan
Self Regulated Learning Siswa Dalam Menghadapi Pembelajaran Daring Selama Pandemi
Covid-19. NiCMa: National Conference Multidisciplinary, 1(1), 606–613. Google Scholar
Ulfatun, T., Septiyanti, F., & Lesmana, A. G. (2021). University students’ online learning self-
efficacy and self-regulated learning during the COVID-19 pandemic. International
Journal of Information and Education Technology, 11(12), 597-602..
https://doi.org/10.18178/IJIET.2021.11.12.1570
Vandenbos. (2016). APA dictionary of psychology (2nd ed.). In G. R. VandenBos (Ed.), APA
dictionary of psychology (2nd ed.). (2nd ed.). American Psychological Association.
https://doi.org/10.1037/14646-000
Wijaya, T. T., Ying, Z., & Suan, L. (2020). Gender and Self Regulated Learning During
https://doi.org/10.31289/tabularasa.v2i1.284
http://dx.doi.org/10.30813/psibernetika.v14i1.2469
https://doi.org/10.1007/s10984-021-09352-3
https://doi.org/10.4324/9780203930687
https://doi.org/10.7759/cureus.7541
https://doi.org/10.29333/EJMSTE/7893
https://doi.org/10.3200/JOER.98.1.5-13
https://doi.org/10.1186/s40561-021-00151-0
https://doi.org/10.1016/j.stueduc.2021.100980
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Sugiyono.+%282011%29.+Metodologi+penelitian+Kuantitatif+kualitatif+dan+R%26D.+In+Alpabeta.&btnG=
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Sugiyono.+%282011%29.+Metodologi+penelitian+Kuantitatif+kualitatif+dan+R%26D.+In+Alpabeta.&btnG=
https://doi.org/10.1016/j.system.2020.102221
https://scholar.google.com/scholar_lookup?hl=en&publication_year=2012&author=Joseph+Tadlock&author=Sharon+Zumbrunn&title=How+Writing+Feedback+Perceptions+Relate+to+Pre-service+Teachers%27+Achievement+Goals+and+Self-regulation+Behaviors
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Triwahyuni%2C+H.%2C+Zaqiyuddin%2C+M.%2C+Chalimy%2C+F.%2C+%26+Mufidah%2C+W.+%282021%29.+Dukungan+Sosial+Dan+Self+Regulated+Learning+Siswa+Dalam+Menghadapi+Pembelajaran+Daring+Selama+Pandemi+Covid-19.+NiCMa%3A+National+Conference+Multidisciplinary%2C+1%281%29%2C+606%E2%80%93613.&btnG=
https://doi.org/10.18178/IJIET.2021.11.12.1570
https://doi.org/10.1037/14646-000
Mutiah, D., Paulina, M., & Putra, M. D. K.
15 Islamic Guidance and Counseling Journal Vol. 6, No. 2, pp. 1-15, 2023
COVID-19 Pandemic in Indonesia. Jurnal Basicedu, 4(3), 725–732.
https://doi.org/10.31004/basicedu.v4i3.422
Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G. J., & Paas, F. (2019). Supporting
Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic
Review. International Journal of Human-Computer Interaction, 35(4–5), 356–373.
https://doi.org/10.1080/10447318.2018.1543084
Zhao, H., Chen, L., & Panda, S. (2014). Self-regulated learning ability of Chinese distance
learners. In British Journal of Educational Technology, 45(5), 941–958.
https://doi.org/10.1111/bjet.12118
Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The Multidimensional Scale
of Perceived Social Support. Journal of Personality Assessment, 52(1), 30–41.
https://doi.org/10.1207/s15327752jpa5201_2
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. In Theory into
Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
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