Factors Influencing Students' Intention to use Online Tutoring Applications in Jakarta
RA Dyah Wahyu Sukmaningsih 1,*, Adam Kurniawan 1, Ronald 1
* Corespondence Author: e-mail: [email protected]
1 Information Systems Department; School of Information Systems; Bina Nusantara University; Jl.
Kebon Jeruk Raya No.27, Kebon Jeruk, Jakarta Barat, Indonesia; e-mail: [email protected], [email protected],
[email protected] Submitted : 09/02/2023 Revised : 23/02/2023 Accepted : 09/03/2023 Published : 31/03/2023
Abstract
As the COVID-19 pandemic has disrupted traditional learning methods, many students have turned to online tutoring as a supplementary source of education. This study aims to identify the factors that influence students' intention to use online tutoring applications. Data was collected from 401 student respondents in Jakarta through a questionnaire, and analyzed using smart PLS. The results show that perceived brand orientation, interactive course features, course quality, perceived usefulness, perceived ease of use, and trust all have a significant impact on students' intention to use online tutoring applications. These findings have implications for the design and promotion of online tutoring applications, as well as for policymakers and educators seeking to support student learning in the era of COVID-19.
Keywords: online course, e-learning, trust application, intention application, Covid-19
1. Introduction
In Indonesia, the education system mandates 12 years of schooling for students to obtain a diploma, which requires passing exams and assessments from elementary to high school. During this process, students learn different subjects, including compulsory ones like Mathematics, Indonesian Language, Science, and Social Studies, with varying levels of difficulty. To increase study hours and help students understand compulsory subjects required for passing exams such as school and national exams, many parents and students in Indonesia resort to hiring private teachers or using online tutoring services.
The COVID-19 pandemic in Indonesia has forced educational institutions to switch to online learning methods, presenting challenges for technology and internet access in remote areas, and prompting policymakers to adapt and find solutions to ensure that students in disadvantaged areas have access to education. This adjustment is realized through the Merdeka Belajar-Kampus
Merdeka (MB-KM) policy, where students are given the opportunity to gain broader learning experiences and new competencies through several learning activities outside their study program accessed on July 4, 2021 (Hendayana, 2020). In pandemic conditions like this, the Ministry of Education created an emergency curriculum which aims to provide flexibility for education units to determine the curriculum that suits the learning needs of participants, this source is accessed through (Ministry of Education, Culture, Research and Technology (Hendayana, 2020) because of this outbreak, online tutoring companies and educational institutions play an important role in helping to raise awareness of education in Indonesia.
The PISA OECD 2018 data shows that Indonesia's education level is still lacking, as it ranks 70+ out of 110 countries in reading, mathematics, and science enthusiasts. This data serves as a reference for students, educational institutions, and the government to improve the education sector. The author suggests that the evaluation results can provide insights for the development of online bimbel applications in the future.
Brands are crucial for the recognition of a product in the market and can support and increase excellence in academia, and in the case of online tutoring, brand orientation is important to build a good reputation and improve relationships with consumers, as attitudes towards brands can influence users' intention to use the application (Bellou et al., 2015; Gromark & Melin, 2013;
Halima et al., 2021). Therefore, the hypothesis H1 is “perceived brand orientation have positive relationship with percevied usefulness”.
Perceived ease of use refers to one's confidence level that a computer system can be easily understood, and the intensity of use and interaction between users and the system can also indicate ease of use; thus, it is important for online tutoring applications to prioritize ease of use to reach and market to a broader audience, as a user-friendly application can greatly increase consumer usage and vice versa for a complicated application (Adams et al., 1992; Tall, 1986). Therefore, the hypothesis H2 is “perceived ease of use have positive relationship with percevied usefulness”.
The quality of a course affects teachers' work, teacher quality, student empathy (interest), openness, and assessment quality (including student feedback quality) and explains factors including providing clear objectives, appropriate workload and level of difficulty, offering optional tasks, quality of explanations, level and speed of presentation, enthusiasm, and empathy with students' needs, which are related to student achievement (Biggs, n.d.;
Entwistle & Tait, 1990; Marsh, 1987; Walberg et al., 1986).Therefore, the hypothesis H3 is “course quality have positive relationship with trust”.
The integration of E-Learning activities such as chat rooms, discussion boards and email in online courses can promote interaction, stimulate discussion, challenge assumptions and achieve learning objectives, and an interactive learning environment can affect perceived usefulness by making it easier for users to learn (Liaw & Huang, 2013; Silberman & Lawson, 2005;
Watkins, 2005). Therefore, the hypothesis H4 is “interactive course have positive relationship with percevied usefulness”.
The concept of Usefulness, according to Eason (Eason, 1988), refers to the extent to which users can use a system with their existing skills, knowledge, stereotypes, and experiences, while a complete definition must encompass ease of use and product acceptance, which together determine actual usage in a given context, and the current definition of Usefulness includes both factors.
Therefore, the hypothesis H5 is “perceived usefulness have positive relationship with trust”.
Trust is considered as a catalyst for various transactions between buyers and sellers, so that consumer satisfaction can be achieved as expected, and trust behavior in information systems is the user's action to depend on the application or believe that the application can do what is expected (Xu et al., 2018; Yousafzai et al., 2003). Therefore the hypothesis H6 is “trust have positive relationship with behavioral intention”.
Behavioral intention, defined as the extent to which a person has formulated a conscious plan to do or not do some specified future behavior, has a significant effect on the success of online tutorial applications, which rely on the intention of users to operate effectively and support the learning process of
students or consumers of the online bimbel (Melorose et al., 1985; Webster &
Wind, 1996).
2. Research Methode 2.1. Questionnaire
The author creates a questionnaire to measure the level of trust and customer intention in using the online tutoring application, which will be distributed to students, parents, and teachers to obtain accurate data. The questionnaire utilizes a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
2.2. Data Processing
The author utilized quantitative methods and purposive sampling to process data, utilizing the SMART PLS application to determine the value of interconnected research model variables and present results such as Descriptive Statistics, Outers Loading, Construct Reliability and Validity, and Discriminant Validity, followed by analysis of the processed data and drawing conclusions to provide insights and opinions on "Interest and Trust in the Use of Online Tutoring Applications in DKI Jakarta."
3. Results and Analysis 3.1. Data Collection
The author used a questionnaire created with Google Forms to collect data for their research, which was distributed to 3rd grade junior high school to 3rd grade high school students in DKI Jakarta and included citation of previous research on the variables used, with data collection beginning on June 9 and resulting in 401 respondents by June 19, which will be processed using Smart PLS to analyze the levels of intention and trust in using online tutoring applications in DKI Jakarta.
3.2. Descriptive Analysis
Based on the data presented in Table 1, it can be inferred that the majority of respondents who participated in the study were aged 17 years old, accounting for 35.9% of the total respondents. In addition, the majority of the respondents were male, representing 53.4% of the total respondents.
Furthermore, most of the respondents were in their 3rd year of high school, comprising 38.9% of the total respondents. With regards to experience in using online tutoring applications, the majority of respondents had used them for less than a year, accounting for 46.9% of the total respondents, while only a minimal percentage had used them for more than 10 years (1.2%).
Table 1. Data Collection Result Categories
Age 14 15 16 17 18 19 20
0.5% 15.5% 22.4% 35.9% 205 2.7% 3%
Gender Male Female
53.4% 46.5%
Last Education
Junior High School Class 3
High School Class 2
High School Class 3
19.7% 26.7% 38.9%
Length of Use of Online Tutoring
< 1 year Between 1-5 years
Between 6 – 10 years
>10 years
46.9% 30.7% 21.2% 1.2%
Source: Research Result (2023)
3.3. Data Processing Using Smart PLS 3.3.1. Outers loading
Table 2. Outers Loading Result
BI_ CQ IC_ PBO_ PEU_ PU TRUST_
BI1 0.866
BI2 0.842
BI3 0.877
BI4 0.876
BI5 0.834
CQ1 0.885
CQ2 0.832
CQ3 0.874
CQ4 0.851
IC 1 0.861
IC2 0.857
IC3 0.853
BI_ CQ IC_ PBO_ PEU_ PU TRUST_
IC4 0.869
PBO1 0.861
PBO2 0.865
PBO3 0.882
PBO4 0.884
PEU1 0.844
PEU2 0.858
PEU3 0.845
PEU4 0.857
PEU5 0.847
PU1 0.881
PU2 0.861
PU3 0.866
PU4 0.869
T1 0.870
T2 0.856
T3 0.864
T4 0.857
Source: Research Result (2023)
The results of Outers loading that have been processed using smart PLS, the authors find that each of the results of the questions made by the author, has a positive response to each of the variables that are used as variables that influence interest and trust in the use of online tutoring applications in DKI Jakarta.
It is recommended that researchers do not automatically remove indicators with outer loadings below 0.70, but instead carefully consider the impact of removing these items on composite reliability and construct content validity. Indicators with outer loadings between 0.40 and 0.70 should only be removed if their removal increases composite reliability or average variance extracted above the recommended threshold value. Additionally, the contribution of indicators to content validity should be considered when deciding whether to remove them, even if they have weaker outer loadings. However, indicators with very low outer loadings below 0.40 should always be removed from the construct (Hair et al., 2011).
It can be concluded from the table 2, the overall outers loading value exceeds the 0.70 number set by Hair, Joe F. Ringle, Christian M. Sarstedt, Marko, which means that the data the authors collect shows that the overall value will affect the positive results on data reliability and validity.
3.3.2. Construct Realibility and Validity
The validity test is crucial to assess the measuring instrument's ability to measure the intended construct accurately and determine the questionnaire's overall validity. The questionnaire's validity is established when the questions can capture the intended construct adequately. Item validity is utilized when items exhibit correlations or similarities between two factors. To measure an item's validity, researchers calculate the correlation coefficient, which determines the item's feasibility for use in the instrument. Typically, a significant level value of 0.05 is used to determine whether an item correlates with the total score and is considered valid.
Table 3. Construct Realibility and Validity Result
Cronbach’s
Alpha rho_A Composite
Reliability
Average Variance Extracted (AVE)
BI_ 0.911 0.914 0.934 0.738
CQ 0.884 0.885 0.920 0.741
IC_ 0.883 0.883 0.919 0.740
PBO_ 0.896 0.896 0.928 0.762
PEU_ 0.904 0.905 0.929 0.723
PU 0.892 0.893 0.925 0.756
TRUST_ 0.885 0.889 0.920 0.742
Source: Research Result (2023)
Based on the table above, it can be seen that the Cronbach's Alpha value and the Composite Reliability and validity value are more than 0.7, while the AVE value of all variables is more than 0.5, this indicates that all variables are reliable.
Convergent validity is assessed through Composite Reliability or Cronbach's Alpha, which is a tool used to measure reliability and validity.
Composite Reliability is obtained through SmartPLS calculations, and it is the square root value of Average Variance Extracted (AVE). The interpretation of Composite Reliability is similar to Cronbach's Alpha, where a limit value of 0.7 is
acceptable, while values above 0.8 and 0.9 are considered very satisfactory (Sugiyono, 2013).
The AVE value with a minimum limit of 0.5 indicates good Convergent Validity, meaning that the latent variable can explain more than half of the Variance of its indicators. This is supported by the results shown in Figure 1, where all variables have loading factor values above 0.5, indicating that the data is valid. The overall loading factor value exceeds the minimum limit of 0.5, with an average outer loading value of 0.861. Figure 1 shows research model processing Smart PLS.
Source: Research Result (2023)
Figure 1. Research model
3.4. Hypothesis Testing
Table 4 presents the results of hypothesis testing, including the original sample, t-statistics, and conclusion.
Table 4. Hypothesis Testing Result
Original Sample (O) TStatistics (|O/STDEV|) Conclusion
H1: PBO → PU 0.486 8.060 Accepted
H2: PEU→ PU 0.181 3.408 Accepted
H3: CQ→TRUST 0.291 3.950 Accepted
H4: IC → PU 0.278 3.830 Accepted
H5: PU → TRUST 0.374 5.961 Accepted
H6: TRUST→ BI 0.586 18.270 Accepted
Source: Research Result (2023)
Perceived Brand Orientation – Perceived Usefulness
Table 4 shows that the relationship between PBO and PU is significant with a T-statistic of 8.060 (> 1.96). The original sample estimate value is positive at 0.486 which indicates that the direction of the relationship between PBO and PU is positive. Thus the hypothesis H1 in this study which states that 'Perceived Brand Orientation has a positive and significant effect on directly increasing Perceived Usefulness' is accepted.
Interactive Course – Perceived Usefulness
Table 4 shows that the relationship between IC and PU is significant with a T-statistic of 3.830 (> 1.96). The original sample estimate value is positive at 0.278 which indicates that the direction of the relationship between IC and PU is positive. Thus hypothesis H2 in this study which states that 'Interactive Course has a positive and significant influence on directly increasing Perceived Usefulness' is accepted.
Perceived Ease of Use – Perceived Usefulness
Table 4 shows that the relationship between PEU and PU is significant with a T-statistic of 3.408 (> 1.96). The original sample estimate value is positive at 0.181 which indicates that the direction of the relationship between PEU and PU is positive. Thus hypothesis H3 in this study which states that 'Perceived Ease Of Use has a positive and significant effect on directly increasing Perceived Usefulness' is accepted.
Perceived Usefulness - Trust
Table 4 shows that the relationship between PU and TRUST is significant with a T-statistic of 5.961 (> 1.96). The original sample estimate value is positive at 0.374 which indicates that the direction of the relationship
between PU and TRUST is positive. Thus hypothesis H4 in this study which states that 'Perceived Usefulness has a positive and significant effect on directly increasing Trust' is accepted.
Course Quality - Trust
Table 4 shows that the relationship between CQ and TRUST is significant with a T-statistic of 3.950 (> 1.96). The original sample estimate value is positive at 0.291 which indicates that the direction of the relationship between CQ and TRUST is positive. Thus hypothesis H5 in this study which states that ': Course Quality has a positive and significant influence on directly increasing Trust' is accepted.
Trust – Behavioral Intention
Table 4 shows that the relationship between TRUST and BI is significant with a T-statistic of 18.270 (> 1.96). The original sample estimate value is positive at 0.586 which indicates that the direction of the relationship between TRUST and BI is positive. Thus hypothesis H6 in this study which states that ':
Trust has a positive and significant influence on directly increasing Behavioral Intention' is accepted.
3.5. Research Model Analysis
Perceived Brand Orientation – Perceived Usefulness
From the hypothesis of the relationship between the Perceived Brand Orientation variable and Perceived Usefulness which has been processed using Smart Pls, the results are accepted Analysis of the relationship between Perceived Brand Orientation and Perceived Usefulness in the online tutoring teacher's room, namely that an online tutoring product/brand should have an expected relationship referring to the extent to which the actual performance of the brand application is in accordance with the expectations desired by consumers. This is similar to function alignment, which indicates the degree of conformity between system functions and product functions that consumers expect. If a product/brand wants to be said to be successful, the brand must pay attention to the system that has been created, the system that runs must be easy to use, must adjust to the wishes of users, and can make users interested
in our products. If a system works well in its daily use, it will be able to become an extra point for user attention.
There is previous research that discusses Usefulness with Brand, namely as berikit, Usefulness messages can be the first step towards building consumer relationships with brands. This is consistent with the argument (Fournier, 1998) that the execution of marketing communications to manage impressions can be interpreted as a form of brand "behavior" aimed at building consumer relationships. Such consumer-brand relationships have been shown to increase brand helpfulness and brand commitment (Aggarwal, 2004).
Interactive Course – Perceived Usefulness
From the hypothesis of the relationship between the Interactive Course variable and Perceived Usefulness that has been processed using Smart Pls, the results are accepted. Analysis of the relationship between Interactive Course and Perceived Usefulness in the online tutoring application of the teacher's room is that interaction in learning plays an important role in the usefulness of the application, if an online learning application has learning interactions that are interesting, easy to understand, and unique, it will have a positive impact on user response to the usefulness of future applications.
Previous researchers, Shu-Sheng Liaw a,*, Hsiu-Mei Huang explained that interactive course can affect perceived usefulness because: interactive learning environment (Interactive Course) is a learning environment that is integrated with users in learning, and can help facilitate users to be able to learn the subjects they want to learn. Effective learning activities affect things such as perceptual self-regulation, it can be influenced by other factors such as: learner characteristics, for example self-knowledge and emotional self, as well as the attitude of each individual's learning desire, the usefulness that users expect in the application is to feel the learning interaction environment that is beneficial to themselves, it is very much needed in interactive learning in the E-Learning environment. Therefore, the author's research perspective, showing independent factors, dependent factors can be predicted perceived satisfaction, perceived usefulness, is required to pay attention to good interaction in the E- Learning environment (Liaw & Huang, 2013).
Perceived Ease Of Use – Perceived Usefulness
From the hypothesis of the relationship between the Perceived Ease of Use variable and Perceived Usefulness which has been processed using Smart Pls, the results are accepted. The analysis of these two variables is that the application's usefulness and perceived ease of use cause people to accept or reject information technology for the application. Among the many variables that will influence system usage, previous research shows that there are two very important determinants. 1. People tend to use or not use an application to the extent that they feel it can help them do it better. The author refers to The first variable is the perceived benefit. second, Even if potential users find the application useful, at the same time, the implementation effort can go well and be targeted".
The author found previous research that discusses the relationship between perceived ease of use and perceived usefulness, namely, Thus the four external variables (Self-Efficacy, Subjective Norms, Enjoyment and Experience), as well as the ease of use and usefulness of an application that will be felt by users in order to create a sense of good behavioral intentions system owners must consider the ease and usefulness of a system as an important factor when designing, implementing in an E-Learning system, so that high user expectations can ensure the usefulness of the application is widely used by students and effective as a learning and teaching tool. To increase student acceptance of E-Learning applications, educators are required to encourage the above influential factors by: providing training and support to students including mentoring and technical support. On the other hand, E- Learning application developers should improve the ease of use and usability of the system through good design, good system functionality and providing clear system instructions to users (Abdullah et al., 2016).
Trust – Behavioral Intention
From the hypothesis of the relationship between the Trust variable and Behavioral Intention which has been processed using Smart Pls, the results are accepted, the analysis carried out by the author is, where the sense of trust from the user who use the online tutoring application will be able to arise due to
the comfort when using and the confidence of using the application he chooses, will be able to cause behavioral intention, where at this stage, users continue to believe in using the application that students choose because it has certain advantages which will later use the online tutoring application that users like continuously.
There is a study that discusses these 2 variables, namely, Trust is defined as "individual readiness to accept vulnerability on the basis of positive expectations regarding Behavioral Intention in the continued use of the application, these 2 variables are interdependent contexts" (Tarhini, 2017).
Students' trust can significantly increase the acceptance of E-Learning courses and lead to continued usage (Behavioral Intention) (Y. D. Wang, 2014).
Trust also plays an important role in knowledge sharing and as a determinant of the effectiveness of E-Learning activities. When trust exists between the system and the user, the user will certainly enjoy using the various activities and features of the application. Trust encourages them to share knowledge with other students. Students expect benefits as outcomes for their knowledge-sharing activities because learning outcomes have the strongest impact on knowledge-sharing intentions in E-Learning (Kunthi et al., 2018).
Course Quality - Trust
From the hypothesis of the relationship between Course Quality and Trust variables that have been processed using Smart Pls, the results are accepted. The author's analysis of these 2 variables is that the author takes a research on MOOC (Massive Open Online Course), which is online learning that offers open access via the internet for free or for a small fee. Some parts of a MOOC can also be done at any time, which means that students get high flexibility in seeking knowledge in the MOOC system, there are Course Quality variables that affect student trust. One of the studies we cite is Eamon Costello et all's research, explaining that MOOC is influenced by student trust, where MOOC is defined as an educational institution that provides course services where the beneficiaries are students or users of the application. What the provider hopes is that users believe and intend to use MOOC to be more interested in the teaching and learning process using MOOC.
According to (E. S. Wang et al., 2016) the quality of E-Learning design can also affect learning outcomes. In online learning the learner does not need to complete the full course but can choose modules from various courses to learn that the learner wants. Online learning can also increase efficiency in learning. Learners who are interested in E-Learning will also get high motivation in the learning process.
Perceived Usefulness - Trust
From the hypothesis of the relationship between the Perceived Brand Orientation variable and Perceived Usefulness which has been processed using Smart Pls, the results are accepted. The analysis conducted by the author on these 2 variables is, there is research that explains that the perceived usefulness variable is interrelated with the trust variable, in the study explains that: "Perceived Usefulness" (PU), affects the student trust variable because the usefulness of electronic courses will have an impact on their learning achievement. Students' perceptions of the usefulness of E-Learning with an effect on their learning performance, i.e. good usability perceived by students from E-Learning learning, will lead to user trust in the future use of the application (Tomaz, 2019).
4. Conclusion
The research examined the factors influencing the intention to use online bimbel applications in DKI Jakarta, with a specific focus on the Ruang Guru application. Results showed that trust and course quality were significant predictors of behavioral intention, with students who believed that Ruang Guru provided the best for its users having a higher intention to use the application.
Perceived usefulness was also found to be a significant factor, with ease of use and interactive courses contributing to users' positive perceptions of the application. Additionally, the study found that perceived brand orientation played a role in attracting high school students to use the Ruang Guru application.
These findings suggest that online tutoring applications should focus on building trust and providing high-quality courses to attract and retain users.
Acknowledgements
The authors wish to convey their appreciation to the reviewers for their assistance in enhancing the manuscript.
Author Contributions
RA Dyah Wahyu Sukmaningsih proposed the topic; Adam Kurniawan, RA Dyah Wahyu Sukmaningsih and Ronald conceived models and designed the experiments; Adam Kurniawan, Ronald conceived the optimisation algorithms;
RA Dyah Wahyu Sukmaningsih analysed the result.
Conflicts of Interest
The author declare no conflict of interest.
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