International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol  17 No  02 (2023)


Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

The Use of Personal Learning Environment to Support 
an Online Collaborative Strategy in Vocational 

Education Pedagogy Course 
https://doi.org/10.3991/ijim.v17i02.34565  

Muchlas1(), Pramudita Budiastuti1, M. Khairudin2, Budi Santosa1, B Rahmatullah3 
1 Universitas Ahmad Dahlan, Yogyakarta, Indonesia 

2 Universitas Negeri Yogyakarta, Yogyakarta, Indonesia 
3 Universiti Pendidikan Sultan Idris, Perak, Malaysia 

muchlas.te@uad.ac.id 

Abstract—Online distance learning, on the one side, makes the learning 
process more efficient and flexible. However, on the other hand, it produces 
learning loss within a particular educational period and makes students less 
enthusiastic about building a collaborative attitude. In general, online learning 
platform providers have provided support for collaboration activity features, but 
in reality, they have not been able to support effective interaction. Experts believe 
that using the Personal Learning Environment (PLE) as an IT tool in the learning 
process can help create an effective online collaboration environment. This study 
found that PLE was proven to increase collaborative activities in online learning 
significantly. The reflection feature is the type of PLE that has the most 
significant influence on creating a good collaboration environment. The research 
also found that suitable collaborative activities can increase students' 
understanding of TVET pedagogy. 

Keywords—personal learning environment, online collaborative strategy, 
TVET pedagogy 

1 Introduction 

Advances in digital technology today have disrupted almost all sectors of human 
life. Frame digital disruption as the change that occurs when new digital technologies 
change customer experiences, business processes, and business models, thereby 
changing how they create shared value in an ecosystem [1]. Recently, digital disruption 
has accelerated due to the acceleration of the emergence of the COVID-19 virus 
pandemic. The digital interactions percentage of the company's customers worldwide 
increased drastically from an average of 8% in 2017 until 2019 to 26% at the beginning 
of the pandemic in 2020 [2]. The characteristics of education have changed due to the 
COVID-19 pandemic. Educators are required to be able to take advantage of fun 
graphics/visuals to improve learning. Students understand better when the material is 
presented using writing and pictures when compared to oral presentation only [3]. 
Meanwhile provides compelling evidence: people are struggling during the pandemic 

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https://doi.org/10.3991/ijim.v17i02.34565


Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

to change digital behavior, such as cultivating digital attitudes, promoting digital social 
norms, increasing perceptions of digital behavior control, and improving digital 
behavioral decisions [4]. Both studies have indicated that the pandemic has indeed 
accelerated digital disruption. The phenomenon of this suddenly accelerated disruption 
in the education ecosystem has changed the old habits oriented towards face-to-face 
classical learning, shifting to distance learning with the support of the global internet 
network. The application of distance learning must also be supported by digital 
evaluation of learning outcomes. Digital evaluation of learning outcomes also needs to 
be considered to be able to analyze the process and results of students [5]. 

The turbulence of these changes has a positive effect because the world of education 
can take the opportunity to take advantage of digital technology to help adapt to its 
environment so that it can immediately make efforts to mitigate learning quickly. 
However, on the other hand, this situation has an unfavorable impact because it causes 
learning complications in various forms. In addition to the cognitive aspect, with 
reduced knowledge in a particular educational period, the acquisition of skills aspects 
is also reduced during distance learning. The difficulty of fully obtaining the 
psychomotor aspects of learning is felt by students, especially those who study within 
the scope of vocational education, which generally get a lot of hands-on activities. The 
tremendous impact also afflicts the affective aspect; in this case, the improvised 
perfunctory online learning design causes students to have difficulty building a 
collaborative attitude and eliminates human relations in classroom interactions. The 
leading cause of these difficulties is that online distance learning tends to make students 
feel contemplative or isolated [6] and lack a portion of interaction [7]. Therefore, 
learning done at home is expected to improve the quality of life which has a direct 
effect so that the level of loneliness is reduced, happiness is increased, and internet 
addiction is reduced [8]. 

Interaction is an essential factor in distance learning because it determines learning 
success and has even become a component of an online learning model structure [9]. 
The learning design features an intensive and effective reciprocal interaction between 
students, student-teacher, and student-material through collaborative work will create 
the ideal interaction in distance learning. Many previous researchers have attempted to 
embed the completeness of online learning with collaboration features. Through the 
collaborative method the majority of students believe that mobile devices can be used 
for learning and a mobile phone or tablet to study various disciplines [10]. Online-based 
collaborative learning can extend the classroom. Online-based collaborative learning 
can create relationships between students so that the speed of learning can increase 
[11]. 

As stated in Ref [7] a collaborative online environment formed using a community 
inquiry framework has been able to generate high learning motivation in vocational 
school students in Turkey. Other research shows that online collaboration can present 
an effective strategy for postgraduate students in science education in Nigeria [12]. It 
can potentially increase the exchange of information and socio-emotional skills and 
generate a positive sense of interdependence among students online at several 
universities in Peru [13]. Our research in Indonesia has proven that a learning model 
equipped with collaboration features in the form of online discussions and e-portfolios 

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Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

has become an effective strategy in e-learning learning for students of the vocational 
teacher education master's program [14]. Collaborative strategies can enhance the role 
of teachers and students in deeper online learning [15]. To achieve this, teachers need 
to make: proper learning design, more involved teachers and students, balanced course 
structure and autonomy, and active monitoring during its implementation. 

Technological innovations are constantly changing and creating new challenges for 
higher education and the importance of competency development in engineering 
education [16]. Online distance learning has inherently provided collaborative learning 
opportunities for students who follow it. However, in reality, such a platform alone 
does not automatically guarantee students access to collaborative learning 
opportunities. Distance learning providers such as universities generally design 
platforms by considering the diversity of student backgrounds and levels of access to 
digital technology resources. One way to increase students' opportunities to gain access 
to online collaborative activities is to encourage them to use the Personal Learning 
Environment (PLE) in every online lesson they take. 

Many studies have proven that involving PLE in online learning strengthens 
collaborative value. Through PLE, it is proven that students can integrate informal 
learning with formal learning, obtain various opportunities for collaborative activities 
across networks, and develop various social bonds [17]. Another study's findings 
proved that using PLE in learning is more effective in growing high-order thinking 
skills through collaboration and learning satisfaction than using a learning management 
system (LMS) alone and virtual laboratory [18]. In addition, it can also be considered 
that LMS based on learning assessment can improve computational thinking skills, so 
that LMS can be used in the learning process [19]. A review of the concept, theory, and 
implications of the design of pedagogical processes and learning ecosystems, in the 
conclusion that the use of PLE enables the creation of online learning networks that 
support students as partners, creators, and entrepreneurs, as well as agents of their 
learning [20]. Recent studies have shown that students interact more with peers and 
teachers through mobile communication and email; in online learning, enriching PLE 
is generally an essential step in learning [21]. 

Theoretically, PLE can be understood in terms of instrumental, learning philosophy 
[22], and institutional [23]. This study is more interested in choosing a definition from 
an instrumental perspective because PLE will be part of the completeness of online 
learning. PLE as a combination of tools, information sources, connections, and 
activities that everyone regularly uses to learn. This understanding implies that factors 
that form PLE are processes, experiences, and strategies that learners can apply to learn. 
In today's socio-cultural conditions, it is possible to be supported by digital technology 
[24]. 

As a tool, the provision of PLE features needs to pay attention to the required criteria 
to support online learning in creating collaborative activities. Optimal criteria for web 
tools, social media, and other applications to be used as PLEs include: (1) they must be 
easy to use, (2) open, (3) dynamic, and (4) offer collaboration options [25]. From an 
instrumental perspective, students use PLE as a tool and strategy for reading subject 
matter, writing reflections on learning outcomes, and sharing with peers in social 
activities in online learning networks as stated in [22] trough virtual learning media. 

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Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

Meanwhile, as stated in [18] views that students can create collaborative activities in 
online learning through optimal use of PLE tools which include planning and 
management, profiles & portfolios, tools for creating content, content repositories, 
recording and reflection, and collaboration as stated in Ref [18]. This study aims to 
detect the extent to which the use of PLE can contribute for increasing the effectiveness 
of collaboration strategies in online learning. This study will also detect the effects of 
online collaboration by involving PLE in raising students' enthusiasm for the world of 
learning in Vocational High Schools in Indonesia through theoretical subjects and 
vocational education learning strategies. 

This research has paid attention to other relevant research so that it has a state of the 
art. Research with the title: A personal learning environment (PLE) approach to mobile 
teaching and learning on a short-term study abroad. This research focuses on examines 
the effectiveness of a personal learning environment approach in using mobile 
technology for experiential learning during a study abroad to China. Research revealed 
valuable benefits and challenges of the PLE utilizing students' personal mobile devices 
in real time. The use of mobile devices considers mobile device knowledge, suitability 
of teaching materials, mobility, and attractiveness [26]. 

Recommendations are offered for program leaders, educators, and trainers with a 
vested interest in learners’ engagement and experiential learning [27]. Research with 
the title: towards learner-constructed e-learning environments for effective personal 
learning experiences. This research focuses on Flexible and Accessible User 
Constructed Learning Environment (FAUCLE), a learner-centred model for a learner-
constructed learning environment. This research interest on innovative ways of 
designing learner-centred learning environments that encourage active and inclusive 
learning [28]. Research with the title: the acceptance of a personal learning environment 
based on Google apps: the role of subjective norms and social image. The study aims 
to learn how intention to use a personal learning environment based on Google 
applications for supporting collaborative learning is formed, in the context of university 
student learning [29]. The use of online facilities using the Google platform can be 
considered because there are positive perceptions and increase teacher motivation in 
utilizing online learning [30]. 

Based on the descriptions of other studies that have been described, the focus of this 
research is to discuss about the use of personal learning environment to support an 
online collaborative strategy in vocational education pedagogy course. PLE was proven 
to increase collaborative activities in online learning significantly. The reflection 
feature is the type of PLE that has the most significant influence on creating a good 
collaboration environment. The research also suitable collaborative activities can 
increase students' understanding of TVET pedagogy.  

2 Method 

This study uses an ex-post facto type of research by collecting data after carrying 
out the learning process during the pandemic, namely during 2020/2021 also 2021/2022 
academic years. The research approach uses quantitative methods with the aim of 

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testing and proving the hypotheses that have been made/set. To get the data, the 
research used survey method. The survey method serves to obtain data that occurred in 
the past regarding behavioral characteristics, variable relationships and to test several 
hypotheses from samples taken from certain populations. This survey method was used 
to obtain data on the learning process during the pandemic, namely in the 2020/2021 
school year and also the 2021/2022 school year. The survey was obtained through 
distributing questionnaires. The questionnaire was developed based on the research 
objectives. The sampling technique used is Purposive Sampling (Judgmental 
Sampling). Purposive sampling is a sampling technique by selecting a sample 
according to the researcher's knowledge of the study. The selected sample is considered 
suitable for research and can provide the required information. The sample in this study 
was the first-year student of the master's program in Vocational Teacher Education, 
Ahmad Dahlan University, Indonesia. 

The data analysis method used was univariable descriptive statistical analysis. The 
selection of univariable descriptive statistical analysis was used to show a description 
of the conditions and characteristics of respondents' answers for each construct or 
variable studied. Reliability using internal consistency reliability test. Internal 
consistency reliability test is a reliability measure used to evaluate the extent to which 
different test items investigating the same construct produce similar results. Validity 
uses content validity, the selection of this validity in this study is based on research that 
wants to measure specific objectives by reflecting the statement to be measured. 

The learning design uses internet-based distance learning with the support of the 
LMS platform. Learning designs are equipped with features to support students in 
building and utilizing PLE. These features include online discussion applications, e-
portfolios based on Wiki/web platforms/social media, and arranged in asynchronous 
online mode. For building their PLE, in the beginning, students are given direction by 
the teacher always to use these tools while doing the given task. The credit weight for 
this course is two credits with a total of 14 face-to-face meetings. 

The research subjects in this study were first-year students of the master's degree 
program in Vocational Teacher Education at Ahmad Dahlan University, Indonesia, 
who had attended the Theory and Learning Strategies course for Vocational Education, 
totaling 34 people. Exploration of the variables of students' insight into TVET 
pedagogy was using the documentation method in the form of academic achievement 
scores. Other variables/aspects, including content repository, tools for creating content, 
reflection, profiles/portfolios, and collaboration, were explored using questionnaires. 
Instruments questionnaires use a Likert scale from previous researchers of Rus-Casas 
et al. (2021)[31]. The tendency of each variable in students describe using univariable 
descriptive statistical analysis. The trend criterion uses the achievement threshold of 
66%. PLE utilization is declared good if the achievement percentage exceeds the 
threshold value and vice versa. The contribution of the independent variables to the 
dependent variable was detected using multivariable analysis with multiple correlation 
techniques (regression analysis). 

The first alternative hypothesis of this research is that there is a significant 
relationship at the level of error probability of 5% simultaneously between independent 
variables/aspects: utilization of repository content (X1), tools for creating content (X2), 

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Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

reflection (X3), profile and portfolio (X4), and the collaboration activities (Y1). The 
formulation of the second alternative hypothesis predicts a significant relationship at 
the 5% probability error level between each variable, X1, X2, X3, or X4 and Y1. This 
research will also explore the relationship between collaborative activities based on 
PLE (Y1) and insights into TVET pedagogy in Indonesia (Y2) with the hypothesis that 
there is a significant relationship at the 5% error probability level between Y2 and Y1. 
These hypotheses are proven using multiple linear regression analysis. The relation 
significance of the independent variable to the dependent variable was determined 
using a partial correlation matrix between variables. The simultaneous contribution of 
all independent variables is seen based on the index of determination, namely the value 
of R2. 

3 Findings 

Table 1 presents the research data for the subject description. All PLE utilization 
data are expressed on a Likert scale with a value range of 1 until 5, while the dependent 
variable data is Y2 on a scale of 1 to 100. 

Table 1.  Subject description based on independent and dependent variable 

Name of Variable/ 
Aspect Abbreviation Mean 

Standard 
Deviation 

% 
Score Category 

Content Repository X1 3.85 0.69 77.0 Good 
Tools for Creating Content X2 3.12 0.94 62.4 Poorly 
Reflection X3 4.34 0.51 86.8 Good 
Profile & Portfolio X4 3.33 0.89 66.7 Good 
Collaboration Y1 4.45 0.48 89.1 Good 
Insights into the TVET 
Pedagogy Y2 81.2 7.05 81.2 Good 

3.1 Content repository and tools for creating content 

Based on Table 1, using the Content Repository type PLE device provides an 
average of 77% of usability score. This result shows that the device can be used 
optimally and adequately by students to support learning activities. However, there is 
one factor in this aspect with a score below the threshold, as shown in Figure 1 (a). 

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Fig. 1. Use of content repository (a), and Creating content tools (b) 

Dropbox's usability score is only 58.7%, while other factors exceed the threshold. 
The less optimal use of this type of content repository is possible because students are 
less well-known with this device; they are more familiar with more popular online 
repositories such as Google Drive (72.7%) and iCloud (79.4%) for Apple product users. 
Meanwhile, computer folders became the most preferred and used storage (80.6%). 
This offline storage is still widely used because its existence was known to students 
from the start before getting to know the online repository. Over time, students began 
to recognize online repositories, and even in this study, the teacher emphasized using a 
large selection of online drives to store learning content. These results are relevant to 
the study of Rus-Casas et al. (2021), which places the use of computer folders at the 
highest score, while online repositories such as Google Drive and others score below 
[31]. Google Drive is one of the tools included in the Google suite. Other tools in this 
suite include email to support communication; Google Docs supports collaborative 
work; Google+ for social interaction; Youtube as a means of storing and sharing 
learning videos; and Google Hangouts to support synchronous online lectures. Even 
though Google Drive is still less famous than offline folders, its existence as an online 
content repository allows teachers and students can use it as a PLE tool; this research 
yields a score of 72.7%. The study of Haworth (2016) supports this result, which found 
that Google accounts can function as PLE because they are pretty easy to use, dynamic, 
and durable as long as students want to use them and offer collaboration. Our research 
found a condition that teachers and students have easy access to this online drive 
because the university has formed a partnership with Google. Through this 
collaboration, they can use all tools that Google provides as PLE [25]. 

Table 1 shows that there is one aspect of all PLE utilized that does not meet the 
excellent category, namely X2, with a score of only 62.4%. This result means that the 
use of PLE in the form of tools for creating content by research subjects is still not 
optimal. This situation can be caused by two new applications that are not yet familiar 
to students, namely web developers and the WIKI application as tools for creating task 
content. In addition, these two applications are part of the module in the LMS with 
minimal features, so they are less attractive in providing display results. As a result, 

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Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

students find it challenging to use; they prefer to write content with tools that they feel 
familiar and easy, such as Google Plus (68.2%) or social media (74%). 

Figure 1 (b) explains that WIKI is the application most students dislike (45.6%). 
This result follows the research of Rus-Casas et al. (2021), which proves that the use 
of the WIKI application to support learning reaches 33.4%, while Google Plus and other 
social media accumulatively achieve a usability value of 69%. This result shows that 
social media is one of the PLEs that has excellent potential for creating content tools 
that are easy to operate and attractive to students. In a previous study, Venter (2019) 
also found that students not only relied on creating content tools prepared by the 
university but were also involved with other informal learning platforms, especially 
social media as stated in [17]. Meanwhile, Web/Blog tools are still better than WIKI 
(54%) because many students use web developers from Blogger and WordPress, which 
are relatively easier to operate compared to WIKI. However, web/blog developers still 
do not provide a good level of use.  

Reflection, Profile and Portfolio, the PLE tools provided to support reflection 
activities have been used very well by students as online learning tools, with an average 
score of 86.8%. Figure 2 (a) presents research results that express the usability score of 
each reflection factor. This study found that students felt they had enough time to access 
the provided PLE (87.6%). Students feel that learning by involving PLE is an activity 
that has a positive impact (87%). Even in their reflection, they feel interested in 
participating in other subjects that use PLE devices (83%). This result is exciting 
because students' awareness of the usefulness of PLE makes them enthusiastic about 
using this tool to attend other lessons in the future; this situation is similar to the results 
of the study by Ciesielkiewicz (2019) [32]. 

Student reflections also indicated that they felt the value obtained was commensurate 
with the effort put in when learning involved PLE equipment (83.6%). Another 
interesting finding, students feel that the experience of following lessons can improve 
skills and digital literacy (93.6%). This study also found that implementing learning 
activities enabled students to develop competencies and skills that were important in 
supporting the profession in the future (93.6%).  

 
Fig. 2. Use of reflection (a), and Profile & portfolio feature (b) 

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Reflection is critical in online learning because it can help students improve 
themselves in facing the following lecture. Previous research has found that in online 
lectures, reflection can: increase the depth of knowledge, identify missing or missing 
areas, personalize and contextualize knowledge, provide comparative references in 
learning, and help students build structural connections in knowledge and social 
connections between them [33]. 

From Figure 2 (b), information can be obtained that research subjects feel that the 
portfolio features provided in the LMS: have a good capacity (70%), can provide 
feedback to improve understanding (76%), and are pretty helpful in self-evaluation 
(65%) as long as students follow the lesson. This study found that students felt the PLE 
portfolio tools to be sufficient to support the growth of more intensive interactions 
between teachers and students as well as between users and the PLE tools provided 
(65%). The student felt the portfolio tool could be sufficient to increase the 
effectiveness of the learning process (67%). The subject's perception of these five 
aspects of the portfolio gives relatively the same results as the previous study by Macias 
(2012). This fact proves that the portfolio feature is needed by students who carry out 
online learning as part of PLE [34]. 

Chang et al. (2018) found that involving a PLE portfolio in online learning can foster 
new ideas, as indicated by the subject's perception rate of 77.4%. On the other hand, 
this study found that the two portfolio features provided were not good at generating 
the growth of new ideas (62%) or integrating the learning process (63%), so this result 
contradicts previous research[35]. Allegedly, students have not realized the importance 
of PLE being used daily as a tool to generate new ideas and knowledge integration. 
They thought to perceive this type of PLE as merely a requirement for attending 
lectures. This phenomenon also occurs in students abroad, as stated in the study of 
Scholz et al. (2017). Such perceptions are thought to cause students to be less intensive 
in using the PLE portfolio and even to be minimalist, even though they can use the 
portfolio as a tool to develop skills in interpretation, comparison, analysis, and 
evaluation, which are essential in growing new ideas [36]. 

Although one aspect gets poorly category, in general, the research subjects have been 
able to use the PLE device well, as indicated by the average value of all aspects of 3.68 
(74%). This fact shows that in carrying out online distance learning, students have used 
PLE tools well and intensively, including offline and online (cloud) content 
repositories, reflection features, profiles, and portfolios. The current good trend in using 
PLE is natural because most of the students who are the subjects of this study belong 
to entities categorized as millennials. This generation was born between 1982 and 2000 
[37] and had highly qualified characteristics in digital knowledge so that they can easily 
and quickly acquire skills in using new information technology tools [38]. The data in 
Table 1 has proven that students with a background as a millennial generation can 
utilize all PLE tools provided to support learning activities optimally. 

3.2 Collaboration and insights into the TVET pedagogy 

Table 1 shows that the collaboration activities (variable Y1) carried out by students 
are in a suitable expected category (achieving a score of 89%). This result implies that 

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the learning held has been able to create collaborative work among students. This study 
also found that students had exemplary achievements in insights into TVET Pedagogy 
with a score of the Y2 variable of 81.2. Figure 3 shows the frequency distribution of 
collaboration activities and the insights into the TVET Pedagogy of the research 
subjects. 

 
Fig. 3. Characteristics of Student Based on: (a) Collaboration Activities,  

and (b) Insights into the TVET Pedagogy Variables 

Figure 3 (a) illustrates that collaborative activities have an excellent trend. Seen with 
a threshold of 66% or 3.3 on the Likert scale, almost all students have a collaboration 
level score that exceeds the minimum limit, and only two out of 34 students get scores 
around the critical point. Even the number of students with the best grades exceeds that 
of students with lower grades. This result indicates that the online collaboration strategy 
applied in lectures has been running effectively. 

Characteristics of students based on variable Y2 indicate that after attending lectures, 
they have good insight and knowledge of vocational education learning strategies in 
vocational high schools. In contrast to the level of collaboration activity, which tends 
to lean to the right where there are more excellent students, the variable of insight and 
knowledge of TVET pedagogy displays a more regular frequency distribution curve. 
Figure 3 (b) depicts the majority of students achieving a view of TVET pedagogy 
around their average score. This phenomenon shows that online learning that is held 
has been able to provide a perfect level of achievement for the subject of view of TVET 
Pedagogy. This good achievement is thought to be caused by implementing an online 
collaboration strategy equipped with PLE tools. In the following analysis, it will be 
seen which aspects of the PLE device contribute to forming collaborative activities 
when students participate in online learning. 

3.3 Relationship between PLE device and online collaborative activities 

Multiple linear regression analysis is declared valid if it can fulfill several 
assumptions. These assume including the type of ratio or interval data, the residuals 
(ŷi and ȳ) are normally distributed, the relationship between the independent and 
independent variables is linear, there is no significant correlation between the 
independent variables (multicollinearity), there are no data outliers, and the variances 

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are homogeneous. All data in this study is interval because it was collected using a 
Likert scale-based instrument with a value range of 1 to 5. Based on the analysis results, 
this study found the error probability value for Shapiro Wilk was p = 0.2168 and p> 
0.05, so the null hypothesis about residual normality was accepted, which means that 
the residue is normally distributed. Based on the scatter plot analysis results, it can be 
seen that all the dependent variables Y have a linear relationship tendency towards all 
X variables so that the linearity assumption is fulfilled. This study found that all the 
data obtained did not contain outlier data. Data analysis also found that the variance 
inflating factor (VIF) for each independent variable was below 2.5. This result indicates 
that all the independent variables involved in this analysis are not correlated with each 
other. In other words, there are no multicollinearity intercorrelations among the 
independent variables.  

Characteristics of students based on variable Y2 indicate that after attending lectures, 
they have good insight and knowledge of vocational education learning strategies in 
vocational high schools. In contrast to the level of collaboration activity, which tends 
to lean to the right where there are more excellent students, the variable of insight and 
knowledge of TVET pedagogy displays a more regular frequency distribution curve. 
Figure 3 (b) depicts the majority of students achieving a view of TVET pedagogy 
around their average score. This phenomenon shows that online learning has been able 
to provide a perfect level of achievement for the subject of view of TVET Pedagogy. 
This good achievement is thought to be caused by implementing an online collaboration 
strategy equipped with PLE tools. In the following analysis, it will be seen which 
aspects of the PLE device contribute to forming collaborative activities when students 
participate in online learning. 

The first step to determine the role of PLE tools on the growth of collaboration 
activities in online learning, this research first examines the level of simultaneous 
correlation between PLE aspects (X1, X2, X3, and X4) and the level of online 
collaboration activities (Y1). Table 2 summarizes the results of the multiple regression 
analysis used in this research. 

Table 2.  Summary of multiple regression analysis 

Source Df Sum of Square Mean Square R
2 F p 

Regression 
(between ŷi and ȳ) 

4 2.2088 0.5522 0.2897 2.9568 0.0365 

Residual 
(between yi and ŷi) 

29 5.4159 0.1868 - - - 

Total 33 7.6247 0.2311 - - - 
 

Based on Table 2, this research found that F = 2.9568 with an error probability value 
of p = 0.0365. Because p<0.5, it can be stated that this study rejects the null hypothesis 
or accept the alternative hypothesis. R2 value or determination index of 0.2897 indicates 
that the PLE tools consist of Content Repository (X1), Tools for Creating Content (X2), 
Reflection (X3), and Profile & Portfolio (X4), together provide 29% support for the 
creation of collaborative activities in online learning. In comparison, variables outside 

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the research give the other influence of 71%. This result can be interpreted that 
simultaneously all independent variables consisting of X1, X2, X3, and X4 have a 
significant relationship with the dependent variable Y1. 

However, based on the partial correlation between each independent variable and 
the dependent variable, it is found that out of the four aspects of PLE, only one aspect 
has a significant correlation with Y1, namely X3 or reflection, as shown in Table 3. 

Table 3.  Correlation between variables 

Source Regression Coefficient R t p 
Effective 

Contribution of Xi 
B 2.5563 - 3.7413 0.0008 - 
X1 -0.1281 0.1543 -0.8669 0.3931 2% 
X2 0.0727 0.3124 0.6887 0.4965 2% 
X3 0.4863 0.5135 2.4475 0.0207 25% 
X4 0.0162 0.2533 0.1699 0.8662 0% 
 

Through Table 3, we can see the partial correlation of the independent variables on 
the dependent variable shows a low significance value (p>0.05) for the variables X1, 
X2, and X4, and only X3 gives a high significance value with an error probability below 
0.05 (p<0.05). The practical contribution weight of each variable is respectively, which 
are 2%, 2%, 25%, and 0%, namely for X1, X2, X3, and X4 variables, so that the 
cumulative total weight of the contribution simultaneously is 29%. Based on these 
results, it can be stated that involving all PLE devices together will be able to support 
the creation of a collaborative environment for online learning, compared to only 
partially. 

It can be seen that the highest effective contribution weight is given by the X3 
(reflection) variable, which is 25%. This fact shows that an essential aspect of PLE to 
create an effective collaborative environment in online learning is the completeness of 
reflection. This result is understandable because the reflection feature will move 
students to self-evaluate the learning process they have followed. Awareness of the 
need for this reflection encourages students to have the will to improve themselves so 
they can find their own previously unknown competencies, as the results of research 
conducted by Slepcevic-Zach & Stock (2018) [39]. The reflection process that students 
go through really needs the support of collaborative activities that will provide students 
with opportunities to deepen their reflection on the reflection of the lectures they are 
attending, which is in line with the study conducted by Campbell (2022) [40]. Research 
conducted by Heeg et al. (2020) [41] also supports this view that a collaborative 
environment is needed to support reflection so that students can externalize the ideas 
resulting from reflection and offer opportunities for other friends to reflect on each 
other's conceptual understanding.  

The low correlation of the variables X1, X2, and X4 to the Y1 variable (creating a 
collaborative environment) do not illustrate that these three are not crucial elements of 
PLE. It is necessary to pay attention here, as mentioned earlier, that the research subject 
is the millennial generation or Y-Generation. As stated in [38] they make IT a part of 
their everyday life, so it is no stranger to using the three PLE devices. They are very 

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Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

familiar and can easily use all types of content repositories, tools for creating content, 
tools for portfolios, and IT-based profiles. So before taking PLE-based lessons, students 
naturally have mastered these three tools. Therefore, the teacher's attention is 
prioritized on preparing the reflection feature rather than the three tools. 

This study also found a significant correlation between Y1's online collaboration 
activities and students' understanding of the view of TVET pedagogy (Y2). Through 
simple linear regression analysis, it was found that the value of F=4.8587 with an error 
probability of p=0.03482, where p<0.05. Even though the correlation is not very high 
(collaborating activity contributes only 13% with R2=0.1318) to students' 
understanding of TVET, it is still within the limits of a significant relationship. 
Collaboration strategies are indispensable in online learning. Through collaborative 
activities, a learning environment can be formed that is not only cooperative, but there 
are strengthening activities from one student to another to provide increased 
understanding results. The low correlation between collaborative activities and 
understanding of TVET can be caused by individual students gaining reinforcement for 
their reflections from sources outside the classroom. This study found that students 
often (at the 73% level) received information recommended by outside experts. This 
fact means that individual students are satisfied that they have obtained valid 
information from the views of experts, so they pay less attention to collaborative 
activities with their classmates. Even so, research results, in general, have illustrated 
that collaborative activities embedded as a strategy in online distance learning have 
significantly contributed to the effectiveness of student learning achievements in the 
field of TVET pedagogy. 

4 Conclusion 

This research illustrates that PLE has a significant role in creating a collaborative 
online learning environment. Reflection is the PLE feature that contributes the most 
compared to other aspects in shaping the online collaboration environment. Meanwhile, 
collaboration has proven to be very appropriate to be applied as a strategy to increase 
the effectiveness of online learning. The recommendation that can be given is that 
teachers need to prioritize the availability of reflection features in utilizing PLE as part 
of providing online learning tools. Other aspects of PLE (content repository, tools for 
creating content, portfolio, and profile) still need to get the teacher's attention by 
ensuring that students are already familiar with these tools, even if they do not show 
their relation to collaborative activities. 

In the content repository variables and tools for creating content, it can be concluded 
that WIKI is the application that students dislike the most, Google Plus and social media 
have excellent potential to create content tools that are easy to operate and attractive to 
students. Meanwhile, Web/Blog tools are still better than WIKI because many students 
use web developers from Blogger and WordPress, which are relatively easier to operate 
than WIKI. Information obtained that the portfolio features provided in the LMS have 
good capacity, can provide feedback to improve understanding, and are quite helpful 
in self-evaluation. Students feel that the PLE portfolio tool is sufficient to support the 

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Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

growth of more intensive interactions between teachers and students. Students feel that 
portfolio tools are sufficient to increase the effectiveness of the learning process. 

The collaboration and insight into TVET's pedagogy illustrates that collaborative 
activities have a very good trend. All students have a level of collaboration that exceeds 
the minimum threshold. These results indicate that the online collaboration strategy 
applied in lectures has been running effectively. The relationship between PLE tools 
and online collaborative activities can be concluded that together they provide support 
for the creation of collaborative activities in online learning. These results can be 
interpreted that simultaneously the variables have a significant relationship. Engaging 
all PLE tools together can support the creation of a collaborative environment for online 
learning, rather than just a few.  

5 Acknowledgment 

The highest appreciation and gratitude give to students in the master's program in 
vocational teacher education who have actively participated as respondents in this 
research. 

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7 Authors 

Muchlas is associate professor in the department master program of vocational 
teacher education, Universitas Ahmad Dahlan Yogyakarta-Indonesia. He graduated 
from Universitas Gadjah Mada-Indonesia with M.T. in electrical engineering in 1998. 
He held the doctoral program form the technical and vocational education in 2013 from 
Universitas Negeri Yogyakarta-Indonesia. Current research interest includes digital 
engineering, robotics, programming, educational technology and vocational education 
studies (email: muchlas.te@uad.ac.id). 

Pramudita Budiastuti is assistant professor at the department of electronic 
engineering vocational education Universitas Ahmad Dahlan Yogyakarta-Indonesia. 
She graduated form Universitas Negeri Yogyakarta-Indonesia with M.Pd. in electrical 
engineering education in 2019. Currently her research interested electrical engineering, 
curriculum development, vocational and training education (email: 
pramudita.budiastuti@pvte.uad.ac.id). 

Moh. Khairudin, the professor in control-electrical engineering, he received his 
bachelor from Universitas Negeri Yogyakarta-Indonesia at the department of electrical 
engineering education in 2002. He graduated from Institute Teknologi Sepuluh 
Nopember (ITS)-Indonesia with M.Eng. in control electrical engineering in 2004 and 
completed his PhD in control electrical engineering in 2012, from Universiti Teknologi 
Malaysia, Johor, Malaysia. His research field is in the area of Flexible Manipulator, 
Robotics and Automation, Robust Control and Intelligent Control System (email: 
moh_khairudin@uny.ac.id). 

Budi Santosa is assistant professor at the department of automotive vocational 
education, Universitas Ahmad Dahlan. He graduated the bachelor and master degree 
from the department of automotive vocational education and the technical and 
vocational education on Universitas Negeri Yogyakarta in 1985 and 2002 respectively. 
He held the doctoral program from the technical and vocational education on the same 
university in 2014. Since 1986 to 2016 he was the teacher at Vocational High School 
for the automotive vocational education. Currently his research interested vocational 
and training education (email: budi.santosa@mpgv.uad.ac.id). 

Bahbibi Rahmatullah is currently an Associate Professor in the Department of 
Computing, Faculty of Arts, Computing and Creative Industry, Sultan Idris Education 
University, Malaysia. Having received a BEng (Electrical) from Vanderbilt University, 
USA, a MEngSc from Multimedia University, Malaysia, and DPhil in Eng. Science 
from the University of Oxford, UK, she is keen on applying the technical and research 
skills gained in improving the quality of research and education in Malaysia. She has 

40 http://www.i-jim.org

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https://doi.org/10.1039/C9RP00175A


Paper—The Use of Personal Learning Environment to Support an Online Collaborative Strategy in… 

authored a wide range of publications and had been invited to review articles for high-
impact journals and conferences. Current research interest includes Image and Signal 
Processing, Pattern Recognition, Machine Learning, Learning Analytics, ICT, and 
Education (email: bahbibi@fskik.upsi.edu.my). 

Article submitted 2022-08-08. Resubmitted 2022-11-22. Final acceptance 2022-11-27. Final version 
published as submitted by the authors. 

iJIM ‒ Vol. 17, No. 02, 2023 41