Postgraduate Financial Aid and Academic Process in Science and EngineeringMajorFields: Implication on Learning and ResearchIntegration
YANG Xi, LI Wenli
Paper presented at the British Educational Research Association Annual Conference, Institute of Education, University of London, 6-8 September 2011
Abstract:The Humbolditian principle of Integration of research and learning is an ideal goal for modern university. In China, postgraduate education is changing from a learning-centered program to a learning-research paralleled system, in which students are getting increasing access to research projects. This transformation is in part realized through postgraduate financial aid reform, as is laying more emphasis on students’ research involvement. However, there are concerns over the balanced academic development for postgraduate students, especially for those in science andengineering majors, who are inclined to put more effort in research while neglecting the traditional course learning and knowledgeaccumulation.
Based on postgraduate student data drawn from 2008 Beijing College Student Survey, this paper is intended to investigate how financial aid policy influences students’ behavior and performance in learning and research, and further affectsthe postgraduate degree process for science and engineering graduate students.
The analysis is built on the student integration theory (Astin, 1984; Girves & Wemmerus, 1988;Tinto, 1987), and an input-output framework will also be adopted. We take the financial aid as the first stage input, research and learning involvement as mediating factors, performance and student’s degreestudy process as the outcome measurement. A Structural Equation Model isapplied to detect the multiple relationships between these variables.
We find theresearch grant significantly raises research involvement and achievement; however, no evidence supports the hypothesis thatfinancial aid promotes learning -research integration. It’s found that scholarship and research grant even create certain degree of tension between learning and researchwithin the academic process, which further hamper comprehensive academic development for the postgraduate students in science and engineering majors.
Keywords: Financial aid; Learning-research integration; Postgraduate education
As science and technology has increasingly become a crucial impetus for economy growth and regional development, graduate education in Science and Engineering (S&E) should begiven more attention since it is the primary incubator for future scientific and technical talents. China’s government used to take full responsibility in postgraduate education finance. Most of the graduate studentsreceive moderate but stable scholarship or grant which can fully cover their tuition fees and certain amount of living expense. These financial aids are mostly connected to one’s learning outcome, such as average GPA in schooling year. Nevertheless, financial support for S&E graduates have been confronting with constraint fiscal budget since the late 1990s when the higher education witnessed a rapid expansion. Inadequacy in graduate financial aid might cause brain drain and damage the quality of S&E education. With this background, transforming graduate financial aid has been put on agenda in a reform scheme since 2006. One of the most noticeable changes is to introduce a strong linkage of postgraduate financial aid to the research system. Normally, advisors are required to offer certain amount of financial aid for any additional student they recruit, while students no longer enjoy guaranteed grant but have to serve as RA or TA in exchange for certain amount of financial support. This research grant is expected to alleviate the problem of insufficiency in financial aid, and meanwhile provide stronger incentive in research participation.
S&E majors are considered as feasible fields in implementing this policy sincethe amount of research funding in these majors seems to be more sufficient to support such financing system. However, considering students responsiveness, the effect of the research-based financial aid system still requires further investigation. There are some researchers supporting the research grant to be an effect measure in preventing dropout and increasing probability of graduation (Girves &Wemmerus, 1987). But there also exist concernsover this research-oriented tendency. Clark et al. (1993) conducted in-depth comparative study over graduate education system across different nations, and they still has some reservation about the capacity of universities to operate as centers of research training where students may not destined for academic or research careers. In this study, we are interested to examine the effect of financial aid on the learning-research relationship in Chinese graduate education system. The concept “learning” here is in a narrow sense, which refers to course learning in traditional taught program. “Research” is regarded as a kind of problem-based learning that student get knowledge and ability advancement through solving practical problems and cooperating with faculties and other students in research projects.
Given the limited time and energy of postgraduate students, it may impose tension between research and learning, so it is very important to figure out whether financial aid system promotes the integration or aggravate the contradiction between learningand research.Unfortunately, most empirical studies focused on the final outcome rather than the mechanism of financial aid in the degree process, and researcheson the graduate education are even more scarce. In this paper, we intend to fill this research gap by looking into the graduate degree process. Three questions are going to be discussed:
1. Whether financial aids affect students’ integration in learning and research involvement?
2. Whether financial aids influence students’ research and learning integration concerning academic outcome?
3. What is the influence of learning-research integration on graduate student degree process?
The relationship between financial aid and academic performance has been examined in a lot of empirical studies.Financial aid showed positively relate to academic performance (Stater, 2009), persistent and graduation (Paulsen & St. John, 2002; St. John et al. 2000; Bettinger, 2004; Dynarski, 2008). These studies usuallyadopt aninput-output approach to evaluate the effect of financial aid, through which education outcome is assumed to be directly affected by the aid policy as well as other individual and institutional factors, such as gender, race, family socioeconomic background, academic aptitude, school/department type, etc.
One concern for our analysis is how to deal with the concept of learning-research integration. Previous studies in general neglect the process of education andacademic behaviors, such as learning-research integration. The conceptual model in our study is planned to incorporate the integration theory to solve this problem.
Developed by Tinto(1975, 1993), Pascarella(1985) and Astin(1984) , integration theory delves into the academic development process with focus on student’s integration, which is considered as one’s interaction with his/her institution academically and socially(Tinto，1975). It is the integration that serves as an mediating factor in the academic process. On one side integration links to a series of initial input factors, such as student’s socioeconomic background, ability, integration with peers and faculty, institution type and support (financial aid, e g.), and on the other side it influences individual’s academic achievement such as grades in exams, persistence rate and graduation. This theory meets the purpose of this study in two aspects. For one, both learning and research are important components of “academic integration” in S&E graduate education. Synergy of learning and research reflects that graduate student can achieve a balance between the two in the academic integration process,thereby raise one’s academic achievement and foster the degree study progress. For another, integration theory provides explanation to the connectionbetween the education input and output; therefore we are able to investigate how the financial aid works on graduate academic outcome as a type of financial input.
Another concern in building our theoretical framework is how to treat student research experience. For the graduate education, especially for S&E graduate education, there is no doubt that research plays a crucial role in the academic process. Girves& Wemmerus (1987) developed a model for graduate student degree process and found that financial aid affects one’s degree process partly through research involvement. Tinto(1993)also explains the persistence of doctoral student through an integration model, in which research opportunity and student’s relationship with faculty are put on a significant position. These theoretical models also laid foundation for this study.
Based on input-output theory and integration theory, we build our theoretical framework as depicted in Figure 1. The graduate academic process is divided into 4 phases.
Phase I represents the preconditions (or input) for graduate development, which are: (1.1) students’ family socioeconomic status (SES), (1.2) student’s aptitude, (1.3) level of institution, (1.4) access to scholarship and (1.5) access to research grant. These initial factors are assumed to be correlated with each other. We are going to discuss which factors affect the distribution of financial aid.
Phase II and III constitute the academic integration stage. Considering the purpose of our research, we only enter variables reflects “academic integration” into this stage while exclude “social integration” from the analysis. According to previous literature, academic integration is usually measured in two areas. One is student self perception on certain academic behaviors, such as time investment in academic activity, academic interaction with teachers and peers, etc; Another is student’s cognitive development which is usually measured by academic achievement, such GPA (Pascarella &Terenzini, 1980; Pascarella &Chapman, 1983; Cabrera,et al., 1992). Phase II takes factors reflecting one’s academic behavior, which includes: (2.1) Course involvement (interaction with staff and peers) (2.2) time in learning after class; (2.3) time in research after class. The first two items are categorized as learning involvement while the third is research involvement. These involvement measurements are assumed to be influenced by factors in Phase I. Phase III is consisted by indexes of student’s achievement, which are: (3.1) academic ranking; (3.2) number of published papers; (3.3) knowledge and ability development. The first two items are objective measurement of one’s learning and research achievement, and the third item measures student’s subjective perception on his/her cognitive development. These factors are affected by academic involvement as well as student initial endowment.
Phase IV represents the final outcome of graduate degree process. In Tinto’s( 1993) model, PhD completion is taken as the outcome indicator. But in mainland China, the completion rate is too high, so that it’s not a good construct to measure academic outcome. Alternatively, student’s propensity in choose PhD degree (PhDchoice) is used as the index ofpostgraduate education outcome, asfostering research talents is one of the major goals for S&E postgraduate education. It is assumed that successful academic integration during phase II and III will encourage S&E graduates to continue their doctoral degree. Moreover, initial input factors are expected to affect PhD decision too.
Based on the theoretical framework above, there are 3 conditions which are treated as necessary conditions to determine learning-research integration with respect to the financial aid system.
C1: Improve academic involvements in both learning and research;
C2: Raise achievements in both learning and research;
C3: Promote general academic achievements（knowledge and ability） and encourage PhD choice.
The first condition suggests the learning-research integration happens within the second stage when student’s more involvement in one activity will not reduce another. It is a rigorous condition. In reality, though, this state is relatively difficult to attain since students are likely to focus on one activity while subordinate another due to limit time and energy. The second is a comparably looser condition that defines learning-research integration in the third phase. It reflects substitutive relationship between learning and research, which means extra learning input can facilitate research through preparing one with more solid knowledge foundation, while research experience can also improve learning performance through widening student’s scope, sharpen their understanding of the textbook knowledge, etc. In such case, financial aid policy promotes integration as long as it exerts positive influence on either research or learning involvement. But the second type of integration may not be stable if the financial aid is inclined to raise one input while undercut the other. Synchronous improvement in learning and research is difficult to accomplish when research or learning input drops to a very low level.
Derived from the first two necessary conditions, there are 4 hypotheses to test whether the financial aid system promote learning-research integration.
H1: Scholarship is positively related to research involvement;
H2: Research grant is positively related to learning involvement;
H3: Scholarship is positively related to research achievement through academic involvement;
H4: Research grant is positively related to learning achievement through academic involvement;
As listed in condition 3, integration between research and learning are expected to facilitate further academic integration, which is characterized by (1) enhancing student’s general academic achievements measured by knowledge &ability; (2) encouraging one to pursue doctoral degree. We have 2 additional hypotheses to test these propositions.
H5: Scholarship grant promote knowledge &ability development and PhD choice through academic integration;
H6: Research grant promotes knowledge &ability development and PhD choice through academic integration.
If most of these hypotheseshave to be rejected by the empirical analysis, we claim that the aid system cannot promote integration between learning and research. However, the three conditions are not sufficient to justify the aid system as the one that enhance learning-research integration, as integration may realized through other mechanism which are not included in our model.
3.Data and Empirical strategy
Sample of this study is drawn from 2008 Beijing College Student Development Survey of the Graduate School of Education in Peking University. This survey aims at investigating the quality of higher education in Beijing, and the questionnaire covers many aspects including student’s background information, academic integration and performance, students’ perception on institution quality, etc. The dataset consists of 8117 valid samples in different majors coming from 39 higher education institutions in Beijing. We select respondents who are (1) master degree candidate, (2) majoring Science and Engineering, (3) enrolled into the graduate institution before 2008. Finally, we adopt list-wise deletion and limit our analysis sample to 1018 cases. The majority of S&E graduates are from low and middle income families. About 59.63% S&E graduates comes from families with annual income lower than ￥20,000, 37.32% comes from middle-income families with annual income between￥20,000 to ￥100,000; Only 3.05%graduate are from families with annual income higher than ￥100,000.Most participants come fromvery selective universities. 40.96% sample are in ‘985’ universities (top level higher education institution in China); 38.8% are in ‘211’ universities (advanced level higher education institution), the remainder 20.24% come from ordinary colleges and universities. In terms of financial aid, 34.97% S&E graduate student have received scholarship, and 52.75% get research grant. Mean of scholarship is ￥2530.69, higher than average research grant ￥1299.96. Table 1 in the appendix gives detailed description on the explanatory variables.
Table 2 presents constructs for further analysis. We categorize them into two groups: manifest variable and latent variables.
Manifest Variables can be observed directly and are one-item measure. In this study those factors based on objective measurement are mostly classified as manifest variables, which include: school level, scholarship, research grant, learning time, research time, academic rank, number of published papers, PhD choice.
Latent variables cannot be directly observed but have to be inferred from other manifest variables. We have 4 constructs be treated as latent variables, which are:
Family socioeconomic status (SES). It is measured by 3 items considering student’s family annual income, father’s education level and father’s occupation level.
Academic aptitude. It is usually measured by standardized aptitude test; however there is no such kind of exam in China for postgraduate student. So we find other two variables to represent this construct. “Undergraduate rank” reflect student’s intellectual capability and previous academic achievement; “Research Interest” measuring via the 4-point Likert scale ranging from 1(Strongly disagree) to 4(strongly agree).It allows us to assess student academic aspiration for graduate education.
Course involvement. It is gauged by 3-item construct including the frequency of class discussion, asking teacher questions on class, consulting teachers after class. All subscale is rated on 4-point frequency scale, ranging from 1(never) to 4(often).
Knowledge and Ability development. This item is gauged by 9 self-report questions concerning one’s: (1) professional knowledge, (2) practical ability, (3) scope of knowledge, (4) mastery of academic norm, (5) mastery of research methods, (6) ability to conduct interdisciplinary research, (7) ability of independent learning, (8) independent research and innovation, (9) analytical capacity and critical mind. The score of all questions are 4-point ordinal scale, ranging from 1(low) to 4（high）.
Structural Equation Model (SEM) is utilized for the analysis in this study. SEM is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumption, which can provide researchers with a comprehensive mean for assessing and modifying theoretical models (Joreskog, 1982). It is known for several statistical strengths that meet our needs in this study. Unlike traditional regression model, SEM can handle many dependent variables at the same time, thus enable us to investigate student’s learning and research outcomes at the same time. Also, SEM excels at dealing with complicated structural relationships. It not only estimates factor relationship but also the structure of factors, therefore provides us a way to probe into the interrelationship between financial aid, research and learning. Moreover, SEM is able to deal with latent variables such as student “knowledge and ability development” that cannot be observed directly but need to be measured by other variables. In SEM analysis, the measurement model is constructed to capture the relationships between measurement variable and latent variable, so that the latter can be more accurately estimated.