Facing the trend of the 4th industrial revolution, the self-study capacity of students has a very important meaning in improving the quality of training. Therefore, the study aimed to evaluate the factors affecting the intention of self-study of An Giang University students. The study uses the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB) on the basis of collecting data from 300 students studying the faculties of An Giang University. The study use methods of testing the reliability of scales by Cronbach’s Alpha coefficient, exploratory factor analysis (EFA) and multivariate regression analysis. Research results show that there are five factors that influence students' intention to self-study of students, such as: (1) Expectations for effort, (2) motivation for learning, (3) Perception of ease of use, (4) habits and (5) social influences. At the same time, this study provides some implications for management to help the school have strategies to support students' self-study to improve the quality of training to response the social needs

Hang, Nguyen Thi Diem

Thao, Nguyen Phuong

English

ASEAN / Asian Academic Society International Conference (AASIC) Proceeding Series

 410 | Proceeding Book 7th Asian Academic Society International Conference 2019  Some Factors Affecting The Intention Of Self-Studying Students Of An Giang University  Nguyen Phuong Thao1,*, Nguyen Thi Diem Hang2,* 1Faculty of Education, An Giang University, Ho Chi Minh, Viet Nam 2Faculty of Economics and Business Administration, An Giang University, Ho Chi Minh, Viet Nam *Correspondending authors, E-mail address: npthao@agu.edu.vn; ntdhang@agu.edu.vn  Abstract  Facing the trend of the 4th industrial revolution, the self-study capacity of students has a very important meaning in improving the quality of training. Therefore, the study aimed to evaluate the factors affecting the intention of self-study of An Giang University students. The study uses the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB) on the basis of collecting data from 300 students studying the faculties of An Giang University. The study use methods of testing the reliability of scales by Cronbach’s Alpha coefficient, exploratory factor analysis (EFA) and multivariate regression analysis. Research results show that there are five factors that influence students' intention to self-study of students, such as: (1) Expectations for effort, (2) motivation for learning, (3) Perception of ease of use, (4) habits and (5) social influences. At the same time, this study provides some implications for management to help the school have strategies to support students' self-study to improve the quality of training to response the social needs. Key words:self-study, career interest, determination  1. Introduction  An Giang University is a university with a training scale raised with 57 training programs with nearly 12,000 students. In addition, the trend of the 4th industrial revolution, the self-study role of students has a very important meaning in improving the training quality of An Giang University in particular and universities. college in general. The study of students'self-study issues is a very important role in re-assessing some factors affect to students' self-study intentions and help managers having solutions toenhance the positive role of self-study while promoting the self-study process of students. Therefore, we conducted doing research on "Some factors affecting the intention of self-studying’students of An Giang University" to implement the above objectives. In addition, this study will help educational managers in the other educational institutions to reevaluate and make improvements appropriate to the situation of their units. This study will also contribute the data on learners' intention of self-learning behavior as well as additional research on behavioral theory in governance. 2. Rationale and research model  2.1. Rationale 2.1.1. Self-study activities According to Thai Duy Tuyen (2003), self-study is an independent activity that dominates the knowledge, skills, and techniques; is brainstorm, think, and use intellectual capacities (observation, comparison, division…) together with motivational and emotional qualities to occupy knowledge of a certain field of knowledge or historical and social experiences of mankind, making it our own property learn". There are many different understandings about self-study. Nguyen Canh Toan et al (2002) said that "Self-study is self-brainstorming, thinking, using intellectual abilities (observation, comparison, analysis, synthesis ...) and sometimes muscles(when it comes to using tools) and its qualities,motivation, emotion, human, worldview (like honesty, objectivity, not being  afraid of...) to dominate the knowledge” However, not in class-time, students have many different activities besides self-study controlling the time fund such as social and political activities, cultural and artistic activities, physical training and sports activities, fun activities. entertainment and income generating activities. There are many factors that are both subjective and objective that affect the use of students' extra-class time. Subjective factors include, such as, student awareness, planning, effort to implement the plan, ability to participate; There are also objective factors including, such as, the university's facilities, environment, training objectives, and the school's regulations on the evaluation of students' overtime work results. According to (Nguyễn Hữu Đặng et al., 2014) for self-study activities, there is a clearly differences between students from different schools, residences, gender in the use of over-class-timefor self-study.    411 | Proceeding Book 7th Asian Academic Society International Conference 2019  2.1.2. Intention to conduct behavior There are many theories to explain about human behavior in general and consumer behavior in particular. In it, the intention to carry out acts with Theory of Reasoned Action (TRA)  (Ajzen & Fishben, 1975) and Planned behavior theory (TPB) (Ajzen I., 1991). These two theories are widely used in explaining the intention of human behavior. Then, Davis (1985) introduced the TAM (Technology Acceptance Model) technology adoption model to explain the factors that influence the adoption of technology and user behavior on the basis of TRA. The TAM model examines the relationship and impact of perceived ease of use factors, perceived usefulness to attitudes, thereby affecting intent and behavior in accepting information technology of user. Intention is considered a premise that directly leads to behavior of using technology in TAM model. Research by Zhang, Zhu, & Liu (2012) also confirms the intention to use is a very important concept in consumer behavior research and is also the most important factor to decide on actual consumer behavior. The intention of action defined by (Ajzen I., 1991) is human action guided by the consideration of three beliefs in behavior, in norms and in control. The stronger these beliefs, the greater the intention of human action. This intention is determined by: attitudes towards specific, subjective behavior. TPB (Ajzen I., 1991) is an extended theory of the TRA (Fishbein & Ajzen I., 1975), it show that intention is the main factor leading to behavior, it is an indication of how hard people will try, or how much effort is intended to make a particular behavior. Thus, in this new doctrine, the author has confirmed that the intention to carry out the behavior is influenced by three factors: (1) attitude toward behavior, (2) subjective standards, (3) acceptance behavior control mode. According to Nguyễn Hữu Đặng et al. (2014), the expectation of self-effort has an impact on students' self-study time. This result is consistent with the study of Nguyễn Bá Châu (2018). Research by Nguyen Thi Thu An et al (2016) suggests that learning motivation has an impact on students' learning outcomes. Learning habits have a great impact on students' learning motivation (Nguyen Ba Chau, 2018). In addition, with the results of this study, the author points out that the sense of self-learning has an important role in building learning motivation. Fishbein & Ajzen I., (1975) define subjective standards as socially perceived pressure to conduct or not to conduct certain behaviors. Ajzen I. (1991) further developed from his definition of subjective standards, indicating that the individual intends to take action after considering the support of those who influence themselves and individuals. realize that many people also act in the same way as they intended. The above studies show a positive correlation between subjective standards and behavioral intent. Therefore, the more support consumers receive from many sources, the more likely it is that the intention of behavior will arise. Therefore, awareness of self-study is a subjective standard that influences behavioral decisions. Subjective standards are the pressure that society places on each person when considering whether or not to perform an act. In studies of Nguyen Phong Tuan (2012); Le Thuy Huong (2014); Effendi (2015); Mingyan Yang (2014)  also affirmed that there is a positive influence between subjective standards and intention to use the service. Studies on the perception of convenience such as the study of Nguyen Van Thuan and Vo Thanh Danh (2011) suggest that the convenience in purchasing goods affects the intention to use the service. 2.2 Research model and research hypothesis Based on the TPB of Ajzen (1991) and previous works and studies, the author proposed a research model: Intention to self-study = f(Expectations of self-effort, force of learning, Habits, Self-awareness, Social influence, Perception of ease of use) along with research hypotheses: H1: The more students expect to make efforts, the more they intend to learn by themselves H2: The more motivated students are, the more likely they are to learn by themselves H3: The more students have the habit of studying properly, the more they intend to learn by        themselves H4: The more students become aware of self-study, the more they intend to learn by themselves H5: The more students are affected by the learning society, the higher their intention to learn H6: The more students are aware of ease of use, the more they intend to learn by themselves       412 | Proceeding Book 7th Asian Academic Society International Conference 2019  3. Research methods  3.1. Data collection methods The author uses convenient sampling method with stratified criteria according to faculties and training courses to interview 300 students studying at the University.Phadditional grace under training (90 students the first year, second year 80 students, 70 students third year, fourth year 60 students). 3.2. Methods of data analysis The analytical methods are used in solving the objectives, testing the research hypotheses of the topic, including: descriptive statistical methods, exploratory factor analysis (EFA) and analysis Multiples linear regression.  4. Results and discussion  4.1. Analyzing the reliability of the scale through the Cronbach ’Alpha coefficient According to Hoang Trong and Chu Nguyen Mong Ngoc (2008), Cronbach’s Alpha coefficients have values from 0.8 to nearly 1 indicating very good measurement scales; From 0.7 to nearly 0.8 indicates that the usable scale and Cronbach's Alpha with a value of 0.6 or more are usable in case the concept is new or new to respondents in the research context. The results of Cronbach's Alpha analysis for the elements of the model show that the two coefficients of total variable (Item - Total Correlation) and Cronbach's Alpha if variable (Cronbach's Alpha if Item Deleted) are as follows: in all scales Measurements include: (1) expectations on self-effort; (2) motivation for learning; (3) study habits; (4) A sense of self-study; (5) influence learning society; (6) awareness of ease of use and (7) Intention to self-study have Cronbach’s Alpha coefficient above 0.6. With the above Cronbach’s Alpha values, the measurement scales are usable in the research context of the topic. Below are the results of the Cronbach’s Alpha coefficient analysis for the scales. 4.2. Exploratory factor analysis (EFA) 4.2.1. Independent variables The results of the correlation test between the factors, we have KMO = 0.781> 0.5; Sig, test of Bartlett’s Test = 0,000 <0.05. Statistical results show that the variables are correlated with each other and are completely consistent with the exploratory factor analysis. The next is the factor matrix that is implemented with Varimax rotation shown in the following table: Table 1. Rotated matrix results (last modified)  1 2 3 4 SKCL8 0,889    SKCL6 0,871    SKCL7 0,857    MT3  0,880   MT2  0,839   MT1  0,766   GG3   0,935  GG1   0,927  KT4    0,925 KT3    0,911 KT2    0,593 Eiginvalue 5,118 1,383 1,289 1,089 Cumulative (%) 46,527 59,102 70,819 80,72   The factor analysis table shows that all 11/25 variables reached the EFA requirement, if Eiginvalue in the analysis is 1,089> 1, the 11/25 observed variables are reduced to 4 factors, In this table, we also see the Comulative cumulative variance equal to 80.72%> 50%, so the 4 factors that are extracted explain more than 80% of the variation of the data. The factor load factor of all variables is greater than 0.5 and satisfies the requirements of this research requirement.  4.3.2. Dependent variable We have results of KMO = 0,847> 0.5; Sig, test Bartlett’s Test = 0,000 <0.05. This result shows that the variables are correlated with each other and are completely consistent with the exploratory factor analysis.  413 | Proceeding Book 7th Asian Academic Society International Conference 2019  Table 2. Factor matrix results Variable Group of factors 1 I will find out the study 0,861 I have the plan starting the study 0,859 I do plan increase the time to self-study in my time 0,847 I am going to self-study in recent time 0,835 I will definitely self-study in the recent time 0,751  From the above matrix of results, it can be seen that all three observed variables have factor loadings greater than 0.5 and satisfactory in factor analysis. 4.4. Multiples linear regression analysis The combined results show that the coefficient of determination R2 = 0,821 and the adjusted coefficient R2in the model is 0.819, besides, the F-test shows the significance level of Sig = 0,000, which indicates that tissue suitability The picture is 81.9% or in other words the independent variables explain 81.9% of the variance of the dependent variable. The magnification coefficient of variance VIF <2 shows that the independent variables do not have a close relationship with each other so there is no multicollinearity phenomenon. To consider the level of influence of each factor on the dependent variable, the credit rating we consider the following regression weight table: Table 3. Regression weight table (Coefficientsa) Model unstandardized Regression coefficient standardized Regression coefficient T Sig, Multicollinearity  B Std, Error Beta T VIF Constant -0,591 0,129  -4,567 0,000   KV 0,188 0,031 0,190 6,160 0,000 0,639 1,564 DL 0,463 0,029 0,502 16,039 0,000 0,620 1,613 SD 0,373 0,031 0,336 11,910 0,000 0,763 1,311 TQ 0,175 0,038 0,133 4,577 0,000 0,722 1,385 From the above regression results, we have the regression function rewritten as follows: YTD = -0.591+ 0.188 * KV + 0.463 * DL + 0.373 * SD + 0.175 * TQ  With the expectation of self-effortfactor affecting self-study intention in accordance with the research of Nguyen Huu Dang et al. (2014). With awareness of ease of use factor affecting self-study intention in accordance with the study of Nguyen Thi Thu An et al (2016). The perception of usefulness and habit is consistent with the theory of service behavior published by the authors Nguyen Van Thuan and Vo Thanh Danh (2011). Considering the regression table we see four factors: KV (expectation of self-effort), DL (Learning motivation), SD (awareness of ease of use) and TQ (habit) having a positive impact on the dependent variable YĐMH because the regression weight B of these 4 factors is statistically significant (p <0.05), If considering the impact of these 4 factors on the dependent variable YĐTH, we have sequentially high and low effects of each factor corresponding to the standardized beta level as follows: DL (β = 0,502), SD (β = 0,336), KV (β = 0,190) and TQ (β = 0.133) 5. Conclusion  The study was conducted in two steps: qualitative and quantitative. The quantitative research results with a valid sample size of 300 have shown that the scales have ensured reliability, permissible values and 4 accepted research hypotheses, 2 are rejected, namely 4 factors that positively affect students' intention to self-study by the level of diminishing impact:: DL (learning motivation) has β = 0,502, SD (awareness of ease of use) has β = 0.336 , KV (expected self-effort) with β = 0.190 and TQ (habit) has β = 0.133. Research results show that learning motivation plays a very important role in the students' intention to study, this is a key factor to help managers encourage learning motivation for students. . In addition, the convenient awareness of ease of use in the process of self-learning such as facilities and lecturers' requirements encourages students to self- 414 | Proceeding Book 7th Asian Academic Society International Conference 2019  study. Research has found that students have a habit of self-studying, self-aware of their learning, the intention of self-study is increasing. This helps parents practice their self-study habits. The study contributes to the educational administrators have a comprehensive assessment of the problem of self-study of students and the factors indicated in this study will help educational institutions build a system to promote pushing students' self-learning process to improve the quality of the school's training, helping learners get the appropriate skill-building environment.  References Ajzen I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. Ajzen, I., & Fishben, M. (1975). Belief, attitude, intention and behavior. An introduction to theory and research. Mass: Addison - Wessley. Davis, FD (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results (Doctoral dissertation). MIT Sloan School of Management, Cambridge, MA. Fishbein, M., & Ajzen I. (1975). Belief, attitude, intention and behavior. . . An Introduction to Theory and Research Reading. Ha Nam Khanh Giao, & Ha Van Thien. (2017). Factors affecting the intention of Ho Chi Minh City to buy safe vegetables. Journal of Industry and Trade, (9). Hoang Trong, & Chu Nguyen Mong Ngoc. (2008). Analyze research data with SPSS. Hanoi: Hong Duc Publishing House. Ihsan Effendi. (2015). Analysis of Consumer Behavior of Organic Food in North. Sumatra Province, Indonesia, Journal of Business and Management, 4(1), 44–58. Le Thuy Huong. (2014). Investigate factors that influence urban residents' intention to buy safe food - Take, for example, in Hanoi City. National Economics University. Mingyan Yang. (2014). Consumer Attitude and Purchase Intention towards Organic Food A quantitative study of China. Linnӕus University. Nguyen Ba Chau. (2018). Study on the actual situation of factors affecting the learning motivation of Hong Duc University students. Journal of Education, Special Issue(June 2018). Nguyen Huu Dang, Le Tin, Bui Dien Giau, Nguyen Hong Thoa, Ha My Trang, Le Tran Phuoc Huy,  Ho Huu Phuong Chi. (2014). Factors affecting student self-study time: case of students of Faculty of Economics & Business Administration, Can Tho University. Science Journal of Can Tho University, 33. Nguyen, TH (2012). Key factors Concurrent purchase purchase - A study of safe vegetable in Ho Chi Minh City, Vietnam. University of Economics, Ho Chi Minh City. Nguyen Thi Thu An, Nguyen Thi Ngoc Thu, Dinh Thi Kieu Oanh, & Nguyen Van Thanh. (2016). Factors affecting academic performance of I-II students in Can Tho University of Technology and Technology. Science Journalof Can Tho University, 46, 82–89. Nguyen Van Thuan, & Vo Thanh Danh. (2011). Factors affecting safe vegetable consumption behavior in Can Tho City. Science Journal of Can Tho University, 17B, 113–119. Thai Duy Tuyen. (2003). Teaching self-study for students in professional colleges. Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 5(28), 1902–1911.             

Some Factors Affecting The Intention Of Self-Studying Students Of An Giang University

http://aasic.org/proc/aasic/article/download/509/506

Some Factors Affecting The Intention Of Self-Studying Students Of An Giang University

Abstract

Similar works

Full text

Available Versions

ASEAN / Asian Academic Society International Conference (AASIC) Proceeding Series