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ISSN : 2671-4981(Print)
ISSN : 2671-499X(Online)
Journal of Business Economics and Environmental Studies Vol.9 No.3 pp.27-38

Effectiveness of Learning Performances According to Financial Motivation of University Students

Young-Sool PARK*,Lee-Seung KWON**,Eun-Mee CHOI***
* First Author. Professor, Department of Health Care Management, Catholic Kwandong University, Tel: +82-33-649-7582. E-mail:
** Professor, Department of Health Care Management, Catholic Kwandong University,
Tel: +82-33-649-7274. E-mail:

© Copyright: Korean Distribution Science Association (KODISA)
This is an Open Access article distributed under the terms of the Creative Commons Attribution NonCommercial License ( which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
*** Corresponding Author, Professor, Department of Health Care Management, Catholic Kwandong University, Tel: +82-33-649-7583. E-mail:
March 13, 2019. June 30, 2019. July 05, 2019.


Purpose - The aim of this study is to explore the effectiveness in educational differences between students of the government's financialfunded groups and the non-financial-funded groups at a university in Korea.
Research design, data, and methodology - The study was conducted using a survey tool of National Assessment for Student Engagement in Learning. In total, 334 participants were surveyed, of which 290 students were participants in economic support program and 44 were nonattendance program students. The general characteristics of all of the participants were investigated by frequency analysis. The analysis of participants’ collective characteristics used independent t and f-test, and one-way ANOVA with IBM SPSS Statistics package program 22.0.
Results - The number of participating students is higher than that of non-participating students in relation to in-activities of university immersion, but the number of participating students is lower than that of non-participating students in relation to in-quality of student support. However, there was no statistical significance. The confidence coefficient of the university-immersion and student support questionnaire is 0.860 and 0.913, respectively.
Conclusions - There is no significant difference in the activities of university immersion and student support between students who participate in the economic support program and those who do not.

JEL Classifications: G41, I21, I22.


1. Introduction and Theoretical Background


1. 1. Introduction


A role of learning is to transfer an organized pattern of thought or behavior (schema) developed in the working (short-term) memory to long-term memory so that the learner becomes familiar with finding solutions to any similar problems (Abeysekera & Jebeile, 2019). Financial incentives related to academic learning performance have been proposed in a cost-effective way as a motivation to support improvements in learning. Since the motivation to study and engage in academic activities play a key role in students' learning experience and well-being, gaining a better understanding of dentals' motivations can help educators implement interventions to support students' optimal motivations (Orsini, Binnie, & Jerez, 2019). Similar methods can be applied not only to dental students, but also to medical care management students. 

However, one reason why students may fail to exert the effort necessary to reach their potential is that they are not sufficiently motivated to do so (List et al., 2018). Among their traditional role, governments heavily subsidize higher education through giving direct institutional support, provide students with financial assistance, and play a primary role in overseeing institutions (Cheslock & Hughes, 2011).

With regard to Ministry of Education's financial support in Korea, it is first important to understand the content of the university education capacity enhancement project. The university education capacity enhancement project provided a starting point for financial motivation for undergraduate education away from the research-oriented financial support system, and the formula financial support system was adopted. The importance of educational activities to improve the quality of education as a process has been highlighted, and the importance of assessment of education courses has been emphasized in recent university assessment and financial support projects (Bae et al., 2015). In addition to providing information on the factors that affect the performance of university education, there is a growing interest in the use of information, and ultimately the degree of university commitment has become a positive measure (Choi et al., 2018). While attending school, students make decisions about the time and effort they devote to learning activities (Oswald & Backs-Gellnet, 2014).

Korea's university financial motivation projects adopted a general support program for almost all universities until the early 1990s. However, the size and type of special purpose support projects, including the nature of special purpose support projects, have increased significantly since the announcement of the educational reform measures in 1995 and have been switched from a general purpose support method to a special purpose support system that emphasizes choice and concentration in order to strengthen the competitiveness of universities (Song et al., 2018). From 2008, formula funding was introduced to select targets for financial support and to determine the size of financial support (Hwang & Jung, 2018). Formula funding is based on vertical fairness in which more resources are allocated to universities striving to improve the quality of education.

In particular, it can be construed that the characteristics of universities most influential in promoting the characterization of university convergence are the composition of departments and majors of universities. Therefore, it is emphasized that the direction and strategy of characterization taken by universities can also be differentiated depending on the composition of the academic field (Lee & Lee, 2015).

Not surprisingly, a growing empirical literature investigates the role of incentives in education in general and the role of financial incentives for student performance in particular (Fryer, 2011). Unfortunately, however, there is little research on the quality of student support and university immersions related to university participation in programs that have an economic incentive effect in Korea.

In the meaning of immersion, Blumenthal and Jensen (2019) suggested three distinct stages in the immersion process -- “involvement triggers”, “involvement words” and “state of immersion”, and each stage was connected to an increasingly higher level of involvement. The effect of immersion on satisfaction and loyalty was stronger when social interactions were low and weaker when social interactions were high (Hudson et al., 2018).

However, in this study, the meaning of university immersion was considered to be a factor affecting the performance of university education and utilized in various theoretical and empirical studies. In general, the characteristics of university students, such as concentration environment, attitudes and interests, and pre-school education experience, influence university immersion in college and the level of integration of students into academic and social systems. From human capital theory, we would expect subsidies to increase the net return to education and help to offset credit constraints (Gunnes et al., 2013).

Therefore, the present study seeks to investigate how and how participation in the specialization project will affect the quality of student support and the activities of university immersion activities for students who participate in the specialization project due to economic motivation.

The specific objectives of this study are as follows.

1. Identify the differences in the gender, age, high school grades, type of admission, university immersion activities by grade, and student support of the entire survey target.

2. Identify the differences between grades of students who participate in specialization, such as university immersion and the quality of student support

3. Through the analysis of the quality of university immersion activities and student support, the difference between specialized and non-participating students is identified.

4. Through analysis of the detailed factors of the teaching and learning process, the difference between students who participate in characterization and nonparticipation is identified.


1. 2. Theoretical Background


Although there are three basic theories of learning that are fundamental to the understanding of instructional design like a behaviorism, cognitive, and social constructivism (Salehinejad & Samizadeh, 2017), this study explores learning interventions of economic motivations, including all of the above three theories. The main proliferation of school intervention in the last decade encourage students to improve school achievement. Many studies suggest that while such programs can have positive effects for certain groups of students, they can have none or even negative effects for other student groups (Oswald & Backes-Gellner, 2014). So far, the reason for this heterogeneous behavioral response to financial incentive programs in education is relatively small.

The Creative Korea (CK) is a project to strengthen university competitiveness based on the characterization of universities considering their role and function in the community. It is financial support project that began in March 2014 and lasted until February 2019 (Choi et al., 2019).

The "Quality in Undergraduates Education" (QUE) participated by 21 universities in four U.S. states, the "Wabash National Study," which conducted a final study on the results and influencing factors of liberal arts education and the "Educational Education Improvement Program," which is centered on the Office of the Vice-President of Stanford University, is the main measure in enhancing the quality of teaching activities (Shin & Choi, 2014).

The Korea National Survey of Student Engagement (K-NSSE) diagnostic tool (revised in 2013), which is widely used as a tool to measure the quality and performance of university students' learning experiences at American universities, was revised and supplemented in the context of Korean universities (Astin & Antonio, 2012).

In 2015, the Korean Educational Development Institute (KEDI) developed a survey titled "NASEL, National Assessment of Student Engagement in Learning" by teaching, learning process, performance measurement, and evaluation method and began applying it to the performance management of Korean university characterization education (Cho & Kwon, 2015). In particular, the degree of university immersion by university students is one reason to judge whether they are active and positive based on their affiliation and attachment and also to see if they have a positive influence on teaching and learning (Choi et al., 2019).

A survey of university students related to teaching and learning is generally conducted by students (Seo & Cheon, 2018), and satisfaction level (Kim & Park, 2016; Min & Loh, 2016), quality and performance of undergraduate education (Shin & Choi, 2014; Pedersen, 2010) and learning capacity (Choi et al., 2018) are being used in a variety of fields.

In addition, by analyzing the data from the Korean Education Employment Panel, participation in schools improved learning performance and strengthened the educational accountability of universities through the formation of positive relationships between schools and students (Kim & Kim, 2013). Currently, school-participation improvement measures are an important topic of school reform, addressing all school problems and contributing to academic performance (Mark, 2000; Taylor & Robinson, 2012).

However, the tangible and intangible conditional rewards of financial support in real universities are motivations for students' desire to learn or to perform in a manner that stimulates external motivation (Hwang & Jung, 2018). If the university has leadership and excellent capabilities through financial support in certain areas of the university, it can be seen as an incentive for voluntary participation in industry-academic cooperation in at least that area, which will greatly help students not only to strengthen their capabilities but also to find employment (Han & Yim, 2018).

The influx of universities, which refers to the degree to which students perceive to fit in with the university they are attending (Bean, 1985), has drawn attention as a key factor in predicting the performance of university education, including academic continuation, in some university effectiveness studies. Research that focuses on the nature and operation of university immersion is still insufficient. While university immersion has been considered one of the main factors in many prior studies, it is relatively recent that university immersion itself has emerged as a key subject of research. In particular, only a limited number of researchers has studied university immersion (Hong & Bae, 2015).

The definition of university immersion is based on the definition that has been conceptualized as having a sense of belonging to the university in which one is attending, confident of one's choice of university and feeling that one and one's university are generally well suited.


2. Research Method


2. 1. Survey Target and Period


The study analyzed A University, a four-year university located in Gang Reung-city in Korea. The survey period was conducted for about 10 days from April 3, 2018 to April 13, in 2018 within the campus. The specialization project group consisting of a single department of medical care management was newly selected for the university characterization program from September 1 in 2016 from the Korean Ministry of Education. The number of students enrolled in the medical care management department of the university specialized project group was 290, all of whom were naturally surveyed, and 44 students from other departments who were not included in this business group were also surveyed as control groups.  As such, questionnaires were distributed to 334 students in the school.


2. 2. Key Survey Contents and Questionnaires


The survey was conducted using NASEL, which consisted of about 200 items. Main contents of NASEL include the general background of students, the content of university life surveys, and the criteria for the examination of teaching and learning capabilities. Among 200 questionnaires, the actual distributed 33 questionnaires were selected from 173 items related to this study. In other words, there are 8 general characteristics, 7 of the survey questions related to university immersion, 10 questions on the quality of student support, and 8 items of detailed factor of teaching and learning process.

The scale for the survey consists of Likert's four-point scale (1=not at all, 2=no, 3=yes, 4=very much), and the higher the score, the more positive it means.


2. 3. NASEL as a Research Tool for "Strategic Exploration of University Teaching and Learning Quality"


The questionnaire used in this study was NASEL (National Assessment for Student Engagement in Learning). In fact, at Korean national universities, NASEL is considered to be a survey tool that is suitable for teaching, learning process and performance, so it is highly utilized in the field of teaching and learning (Cho & Kwon, 2015). The NASEL consisted of seven large areas: activities in class, activities outside the class, interaction with the professor and student relationship, learning performances, support services of universities, university immersion, and personal background, and 173 questions in detail, including university student support services and university immersion.

As Table 1. suggests in the category of university immersion activities and the quality of student support, other personal backgrounds consisted of eight questions: age, sex, grade, high school grades, type of university entrance (new, incorporated), type of student admission (frequent, regular time), department of affiliation (medical care management, other), and major transfer.





2. 4. Research Design and Statistical Analysis Method


2.4.1. General Characteristic Analysis

The general characteristics of all the subjects were mainly frequency analysis and technical statistical analysis.


2.4.2. Group Characteristic Analysis

The quality study analysis of all survey subjects' activities to universities immersion and students support conducted T-testing and F-testing.


2.4.3. Analysis of economic assistance program participation and non-participating program group characteristics

The difference in analysis between participation in economic support programs, non-participatory activities, and the quality of student support and the detailed factors of teaching and learning courses was conducted via T-test, and the difference analysis by grade was done via F-test.


2.4.4. Study on the Quality of University Immersion Activity and Student Support: Analysis of the Internal Content of the University


The inter-question internal load carrying value analysis on the study of the quality of university immersion activities and student support was conducted by the Cronbach's alpha coefficient. The package program IBM SPSS Statistics 22.0 was used for all statistical analysis.


3. Research Result


3. 1. NASEL Participant Status and General Characteristics


3.1.1. Status of Participants in the Survey

The main subject of the study is the students of the specialized business unit department (medical care management), which received financial support. However, since a control group is needed to compare their immersion into universities and the quality of student support, students from non-economic studies were also included in the study list.

As Table 2. shows, a total of 372 students participated in the survey, of which 302 were financially supported and 70 were non - financed students. With the exception of the missing 38 students, a total of 334 completed surveys were available for the analysis including 290 students in financial support and 44 students in non-financial support.





3.1.2. General status of survey subjects

The general status of all the students who responded to the survey was given in Table 3. In age, 44.1 percent of those were under the age of 21, with 32.1 percent aged 22-23 and 23.8 percent aged 24 and older. In terms of gender, males numbered 174 with 60 percent, while females numbered 116 with 40 percent.

According to the admission status, 97.6 percent of all students were new students, and only 2.4 percent were transferred. Admission to university was 54.5% for early admissions and 42.8% for regular admissions. Prior to university admission, the average high school grades were 42.8 percent, with the third and fifth graders at 27.9 percent and 16.2 percent.


3. 2. Status of the study on the quality of student support and the activities of university entrance for the entire survey


3.2.1. Current status of university immersion activities


The results of the university immersion activity survey show that the responses in all questions are positive on the four-point scale of at least 2.5 points. Students who responded 'yes' and 'very much' to the idea of becoming university and departmental members showed the highest rates with 79.6% (2.82), 81.1% (2.82), respectively, and a positive response rate of about 60%, except for the question of whether the university met expectations and satisfaction with the university.







3.2.2. Quality of Student Support

The status of the quality of student support is given in Table 5. The survey found that the average of all questions in the quality of student support was more than three points, indicating that overall, students were satisfied with the student support service. In particular, the highest average was 3.29 in psychological counseling, teaching and learning support programs, and domestic and foreign service programs. Here, the health welfare service refers to various illness education related to the student's health, prevention vaccination, and health consultation or examination and welfare refers to various scholarship and social culture programs. Mentoring services refer to personal career guidance, grievance counseling, or career counseling.


3. 3. The Characteristics of the Overall Survey Participants' Group-Specific Activities in Universities


3.3.1. The Characteristics of Group-Based University Immersion Activity

Table 6. shows the differences in the group's survey participants' involvement in university. The average of the composition questions of university immersion was shown to be 2.61. The analysis of differences among groups according to the individual characteristics of students showed differences in gender and specialty category characteristics, and no differences between groups were found in the other four characteristics. The average number of male students is higher than that of female students. The average number of medical care management students is higher than that of other students.







3.3.2. Study on the Quality of Student Support by Group


Table 7 shows the quality characteristics of student support. The average of the quality composition questions for students was high overall at 2.91, with no statistically significant differences in all the individual characteristics of students.





3.4.1. Yearly Difference of Students with Specialized Participation


As a result of looking at the year-to-year difference in Table 3.7, the medical care management department students who participated in the project were divided by grade, the criteria for the diagnosis of professor/study capabilities, and details of the teaching/learning capabilities.

The difference analysis between groups of factors was conducted. According to a survey on the criteria for the ability of professors and students to study, there is little difference between university immersion and the quality of student support in the academic year. However, Duncan's post-test results on the quality of student support showed some significant results.





3. 5. The Differences of University Immersion and Student Support by Students in Specialization


3.5.1. Analysis of the Difference Between Students with Specialized Participation and Non-Participation


Table 3.8 presents differences between characterized participation and non-participation groups. In the 2018 survey, a distinction was made between the participating and non-participating students of the project group and different groups were conducted on the criteria for the diagnosis of teaching and learning capabilities. As a result, there is a significant difference between groups of business students of students belonging to a non-business group, and the average of participating students (2.77) was somewhat higher than non-participating female students (2.61). However, in the quality of student support, non-participating female students (2.94) had a somewhat higher average than participating students (2.91) but did not show statistically significant results.





3.5.2. Study on the Differences Between Specialized Students and Non-Participating Students in the Teaching and Learning Process


In Table 10, the differences were greatest in three of the eight areas of detailed factors in the teaching and learning process, particularly in the case of in-school student activities, active participation in classes, and higher thinking activities. In the case of in-school student activities, active participation in classes, which is the reason for the high average value of participating students, is that they could be provided various scholarships and mileage benefits through participation in various curricular activities, comparative activities, lectures, and seminars. On the contrary, in the case of higher-order thinking activity, the reason for the high average value of non-participating students is that each student carries out various unconventional thoughts and experiences.






Next, Table 11 used two variables: 'university immersion' and 'quality of student support' as subordinate variables to verify the effectiveness of participation in the college characterization project in terms of the course. Each question was settled on a four-point recurrent scale (1=nearly, 4=very often). Specific measurement questions and factor loads of the variables dependent on teaching and learning are shown below, and the Cronbach's alpha was very good with 0.860 and 0.913 respectively.




4. Discussion and Conclusion


4. 1. Discussion


The role of personal and professional development" stated that professional learning is the period of one’s growth that consolidates both the experiences of within the class and other formal experiences of outside the class as well as conferences (Parveen et al., 2014).

In many ways, financial motivation in relation to learning outcomes can serve as a stimulus for performance of work as a stimulant to perform certain tasks. Academic motivation is a key determinant of academic performance and deserves closer attention (Linnenbrink & Pintrich, 2002). Financial trends are in many ways forging the directional landscape of higher education in the 21st century (Jacob & Gokbel, 2018). Motivation has also an important influence on a learner’s attitude and learning behavior (Hakan & Munire, 2014).

Fundamentally, financial motivation does not always bring positive results to students for learning. Oswald and Backs-Gellner (2014) have suggested that financial incentives are most effective at the beginning of an educational program, when real labor market benefits are in the distant future. According to the standard human capital theory (Becker, 1962), students do so by comparing the present discounted value of the benefits (i.e., expected advantageous labor market outcomes, such as higher future earnings or lower unemployment risk) to the present discounted value of the costs (i.e., direct and indirect costs of exerting learning effort).

In addition, although the Ministry of Education has promoted various financial support projects for universities at the national level over the past decades, there is a tendency for universities to decide the number of specialized universities within the scope of education finance (Kim, 2012), rather than the actual characterization of education-oriented universities, industry-academic cooperation and research-oriented universities at the national level. In view of this, the practical university characterization policy needs to consider whether the nation is pursuing the characterization of voluntary and autonomous bottom-up rather than economic assistance or inducement to universities in a top-down manner, the characteristics appropriately linked to the industrial structure of the community at which universities are located, and the related industries (Lee & Lee, 2015).

The country's economic support program is that universities themselves should be applied as some means for voluntary characterization education. The government is effectively regulating universities by relating financial support to various evaluations and universities that are following the government recommendations in order to secure financial support (Kim & Park, 2018). This evaluation of the government can be a difficult factor for the university itself to qualify for qualitative education and characterization. In other words, there is a possibility that the educational project will be changed in the sense that the evaluation of the government should have good results from the viewpoint of the university.

The fact that there is little difference between the financial-funded and the non-financial-supported groups has obvious limitations to encompassing the broad notion of quality or excellence in education. In detail, no matter how good and accurate performance indicators are, they are not sufficient to evaluate various aspects of education quality and excellence, as in Shin and Choi's study (2014) that is consistent with previous research. Generally, Alemu and Gordier (2017) showed that the provision of financial services, such as scholarship, was indicated as one of the important determinants of the overall students’ perceived service quality. Rewards are not harmful, which is proved by some researches, and there is a certain interrelation between external motivators and task-oriented motivation which is confirmed by the cognitive approach (Jovanovic & Matejevic, 2014; Cameron & Pierce, 1994).

Using the data from the 7th and 8th years of the Korean Education Ending Study, the interaction formed by university students with professors and fellow students was typified, the effect of each type on college immersion and the effect of university level variables were analyzed, and it was demonstrated empirically that social immersion and university immersion had significant relationships (Shin & Choi, 2014). Autonomous motivation, in contrast to controlled motivation and amotivation, should be supported to benefit students with regard to their approaches to learning and well-being since it can promote students' vitality, self-esteem, deep over surface study strategies, and enhanced academic performances (Orsini et al., 2019). Extrinsic incentives, once removed, may crowd out intrinsic motivation on subsequent, similar tasks (List, Livingston, & Neckermann, 2018; Gneezy, Meier, & Rey-Biel, 2011; Fricke, Lechner, & Steinmayr, 2018).

Although learning is financially motivated, students are expected to have a learning effect only if they include autonomy or self-directed learning in addition to financial motivation. Namely, due to the crowding out of intrinsic motivation, the provision of financial incentives may reduce individual performance (Oswald & Backs-Gellner, 2014).

The intertemporal choice of students might be affected by the financial incentives in education, and the financial incentive effect in teaching and learning process is closely related to the time preferences in terms of student's preference to spend in the present over the future. Individuals have rational expectations and maximize their present discounted value of expected lifetime utility by making annual schooling choices (Kemptner & Tolana, 2018).


4. 2. Conclusion


In total, 334 students were surveyed, of whom 290 students were participating in economic support programs and 44 were non-attendance students. The survey period lasted about 10 days, from April 03, 2018 to April 13, 2018 in the university.

According to the results of the survey, there were 174 male students, 60% of all surveyed students, and 116 female students, 40% of all surveyed respectively. In terms of the age, 44.1% are under 21 years old, 32.1% are 22-23 years old, and 23.8% are over 24 years old. By grade, 23.1% of first grade students, 25.5% of second grade students, 27.3% of third grade students, and 24.1% of fourth grade students participated in almost all grade levels.

More specifically, in relation to age,high school academic record, university academic year and gender, the older the active-collaborative learning, and the professor-student interaction, the higher the high school record and university academic year, the higher the male students were than the female students.

The main results of this study are as follows.

1) There is no significant difference in the quality of university immersion and student support between students who participate in the economic support program and those who do not participate.

2) The average of the composition questions of university immersion was 2.61. And the analysis of differences among groups according to the individual characteristics of students showed differences in gender and specialty category characteristics.

3) According to the analysis of the differences between groups on the criteria for the diagnosis of teaching & learning capabilities and the detailed factors of teaching, learning process and performance, there is little difference between students belonging to the business group and those belonging to the non-business group in all categories.

4) The quality of student support survey found that the average of all the questions in the quality of student support was more than three points, indicating that students were satisfied with the student support service in the first half.


5. Limitations of research


University characterization projects are artificially established specialization projects in terms of teaching, learning process and management. Therefore, the Korean university characterization project mentioned in this study has a limitation that does not include all the contents or courses of the characterization project as a whole. In other words, the specialization project of this research refers to the quality of university immersion and student support, which is part of the criteria for diagnosing teaching and learning skills.




  1. Abeysekera, I., & Jebeile, S. (2019). Why Learners Found Transfer Pricing Difficult? Implications for Directors. Journal of Asian Finance, Economics and Business, 6(1), 9-19.
  2. Alemu, A. M., & Cordier, J. (2017). Factors influencing international student satisfaction in Korean universities. International Journal of Educational Development, 57, 54–64.
  3. Astin, A., & Antonio, A. (2012). Assessment for excellence: The philosophy and practice of assessment and evaluation in higher education. Journal of College Student Development. 55(4), 427-429.
  4. Bae, S. H., Kang, M. S., & Hong, J. I. (2015). Validation of the National Survey of Student Engagement(NSSE) Model in the Korean Context. Asian journal of education, 16(4), 77-104.
  5. Bean, J. (1985). Interaction effects based on class level in an explanatory model of college. American Educational Research Journal, 22(1), 35-64.
  6. Becker, G. S. (1962). Investment in human capital: a theoretical analysis. Journal of Political Economy, 70(5), 9–49.
  7. Blumenthal, V., & Jensen, Ø. (2019). Consumer immersion in the experiencescape of managed visitor attractions: The nature of the immersion process and the role of involvement. Tourism Management Perspectives, 30, 159–170.
  8. Cameron, W. J., & Pierce, W. D. (1994). Reinforcement, reward, and intrinsic motivation: A meta-analysis. Review of Educational Research, 64(3), 363-423.
  9. Cheslock, J. J., & Hughes, R. P. (2011). Differences across states in higher education finance policy. Journal of Education Finance, 36(4), 369–393.
  10. Cho, H. C., & Kwon, S. J. (2015). A Exploration Study on Practical Use of National Diagnostic Assessment Results for Developing Teaching and Learning Competencies of Local University. Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 5(4), 521-528.
  11. Choi, E. M., Park, Y. S., & Kwon, L. S. (2019). The Impact of State Financial Support on Active-Collaborative Learning Activities and Faculty-Student Interaction. International Journal of Industrial Distribution & Business, 10(2), 25-37.
  12. Fricke, H., Lechner, M., & Steinmayr, A. (2018). The effects of incentives to exercise on student performance in college. Economics of Education Review, 66, 14-39.
  13. Fryer, R. G, (2011). Financial incentives and student achievement: evidence from randomized trials. Quarterly Journal of Economics, 126(4), 1755-1798.
  14. Gneezy, U., Meier, S., & Rey-Biel, P. (2011). When and why incentives (don't) work to modify behavior. Journal of Economic Perspectives, 25, 191-209.
  15. Gunnes, T., Kirkebøen, L. J., & Rønning, M. (2013). Financial incentives and study duration in higher education. Labour Economics, 25, 1–11.
  16. Hakan, K., & Munire, E. (2014). Academic Motivation: Gender, Domain and Grade Differences. Procedia - Social and Behavioral Sciences, 143, 708–715.
  17. Han, S. S., & Yim, D. S. (2018). Path Dependence in Industry-University Cooperation- In terms of Industry’s Voluntary Participation. International Journal of Industrial Distribution & Business, 9(3), 45-56.
  18. Hong, J., & Bae, S. H. (2015). The effect of professor-student interaction on college immersion in college students. Education and Administration Studies, 33(3), 351-379.
  19. Hudsona, S., Matson-Barkatb, S., Pallaminc, N., & Jegouc, G. (2018). With or without you? Interaction and immersion in a virtual reality experience. Journal of Business Research, on line 16 November.
  20. Hwang, S. Y., & Jung, H. J. (2018). The Interactive Effects of Motivation and Contingent Rewards on Employee Creativity. International Journal of Industrial Distribution & Business, 9(7), 71-82.
  21. Jovanovic, D., & Matejevic, M. (2014). Relationship between Rewards and Intrinsic Motivation for Learning – Researches Review. Procedia - Social and Behavioral Sciences, 149, 456–460.
  22. Jacob, W. J., & Gokbel, V. (2018). Global higher education learning outcomes and financial trends: Comparative and innovative approaches. International Journal of Educational Development, 58, 5-17.
  23. Kemptner, D., & Tolana, S. (2018). The role of time preferences in educational decision making. Economics of Education Review, 67, 25–39.
  24. Kim, B. J., & Park, N. G. (2018). Lessons learned from financing universal higher education in Korea. International Journal of Educational Development, 58, 116-127.
  25. Kim, S. C. (2012). A Study on Efficiently Designing Customer Rewards Programs. Journal of Distribution Science, 10(1), 5-10.
  26. Kim, S. M., & Park, C. H. (2016). Development and Validation of CK Satisfaction Scale, The Educational Research Institute. The Journal of Educational Research, 14(4), 41-60.
  27. Kim, S. Y., & Kim, J. E. (2013). Analysis Research for the Effect of School Engagement on Learning Outcomes and Related Factors in Higher Education. Asian journal of education, 14(4), 73-96.
  28. Lee, H. S., & Lee, Y. M. (2015). Analyzing the Current States of Universities' Interdisciplinary Fields and Influential Factors Impacting on the Fields. Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 5(2), 167-174.
  29. Linnenbrink, E. A., & Pintrich, P. R. (2002). Motivation as an enabler for academic success. The School Psychology Review, 31(3), 313–327.
  30. Marks, H. (2000). Student engagement in instructional activity: Patterns in the elementary, middle, and high school years. American Educational Research Journal, 37(1), 153-184.
  31. List, J. A., Livingston, J. A., & Neckermann, S. (2018). Do financial incentives crowd out intrinsic motivation to perform on standardized tests? Economics of Education Review, 66, 125-136.
  32. Min, G. O., & Loh, J. H. (2016). Impact of Educational Service Information Distribution on Students’ Satisfaction and Achievement Rate. International Journal of Industrial Distribution & Business, 7(4), 17-31.
  33. Orsini, C. A., Binnie, V. I., & Jerez, O. M. (2019). Motivation as a Predictor of Dental Students' Affective and Behavioral Outcomes: Does the Quality of Motivation Matter?. Journal of Dental Education, 83(3), 228-236.
  34. Oswald, Y., & Backes-Gellner, U. (2014). Learning for a bonus: How financial incentives interact with preferences. Journal of Public Economics, 118, 52–61.
  35. Park, M. J. (2018). A Study on College Students’ Perceptions on CK-Ⅰ: Based on Analysis of Importance and Satisfaction, Korean Association for Learner-Centered Curriculum and Instruction. The Journal of Learner-Centered Curriculum and Instruction, 18(10), 589-613.
  36. Park, S. Y., Kim, E. H., Kim, S. W., & Yim, J. W. (2018). Effects of the Engagement of University for Creative Korea (CK) on Students’ Teaching-Learning Competency: Focusing on the Performance Outcomes of K University Specialization Project Team. Humanities and Social Sciences 21, 9(5), 155-168.
  37. Parveen, M., Ullah, O., Salam, M., & Zakir, N. (2014). Impact of Teachers’ Professional Development on Students’ Performance. International Journal of Industrial Distribution & Business, 5(3), 15-24.
  38. Pedersen, D. E. (2010). Active and Collaborative Learning in an Undergraduate Sociological Theory Course. Teaching Sociology, 38(3), 197-206.
  39. Salehinejad, A., & Samizadeh, R. (2017). A Conceptual Framework for Determination of Appropriate Business Model in e-Learning Industry in Iran. East Asian Journal of Business Management, 7(4), 17-25.
  40. Seo, K. T., & Cheon, M. S. (2018). A Study on the Analysis of the Difference between Professor and University Student about Teaching Competencys Recognition. Asia-pacific journal of multimedia services convergent with art, humanities, and sociology, 8(4), 471-482.
  41. Shin, H. S., & Choi, J. Y. (2014). Examining Effects of Grant on Achievement and Adjustment of college students: Focusing on Differential Effects by Family Income and Institutional Location. The Korean Society For The Economics And Finance Of Education. The Journal of Economics and Finance of Education, 23(2), 153-177.
  42. Song. Y. J., Chang, W. S., & Chang, J. H. (2018). The Effective Factors of Professional Learning : Study on Accounting Firms in Korea. Journal of Asian Finance, Economics and Business, 5(2), 81-94.
  43. Taylor, C., & Robinson, C. (2012). Student engagement in higher education: theory, context, practice. Journal of Applied Research in Higher Education, 4(2), 1-3.