







































 

 

 

 

 

 

The Correlation of Expenditure on School 

Level and Students’ Academic Performance: 

Based on the Empirical Study in Western Poor 

Rural China 

Lili Li, Hongyu Guan, Scott Rozelle

Shaanxi Normal University, Xi’an, Shaanxi 710119, China 

Stanford University, Stanford, CA 94305-6055, USA

Abstract. As a means to alleviate poverty, the Chinese government has 

been investing in education by increasing financial resources for 
schools. However, scholarship on the relationship between school re-

sources and student academic performance has not reached a consensus. 
This study examines the relationship between school-level expenditures, 

a key aspect of school resources, and student academic performance. 

Using data collected in 94 rural primary school in designated poverty 
areas of western rural China, the empirical study found that school ex-

penditures on students and teachers account for only 12% of total ex-
penditures, while expenditures on school administration is as high as 

72%. Expenditures on students and teachers (software) are positively 

correlated with student academic performance. However, expenditures 
on school administration (hardware) were negatively correlated with 

academic performance. These findings have strong implications for the 

structure of school spending and rural education. 
Best Evid Chin Edu 2019; 2(1):145-155. 

Doi: 10.15354/bece.19.ar1031 

Keywords: Expenditure in school level; Academic performance; Hardware; Soft-

ware; Rural 

 
 

Correspondence to: Lili Li, Center for Experimental Economics in Education, Shaanxi Normal University, Xi’an, 

Shaanxi 710119, China. Email: lilili2996113@126.com. 

About the Author: Hongyu Guan, Center for Experimental Economics in Education, Shaanxi Normal University, 

Xi’an, Shaanxi 710119, China. Email: hongyuguan0621@gmail.com. 

Scott Rozelle, The Freeman Spogli Institute for International Studies, Stanford University, Stanford, CA 94305-

6055, USA. Email: rozelle@stanford.edu. 

Funding: Higher Education Discipline Innovation and Enlightenment Program (No. B16031); Outstanding Doc-

toral Dissertation Supported Project of Shaanxi Normal University (No. X2015YB08). 

Conflict of Interests: None. 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 146 

Research Background and Problem 

INCE the 18th National Congress of the Communist Party of China (CPC), the 

Party Central Committee, with General Secretary Jinping Xi as the core, made a 

series of profound expositions and comprehensive deployment of poverty allevia-

tion and development work, and clearly defined poverty-alleviation via education as an 

important way to block the transmission of poverty from generation to generation. With 

the implementation of a series of policies on poverty-alleviation via education, enor-

mous achievements have been made in education investment paired with an increasing 

growth of the investment in government finance, school and society (China Education 

Daily, 2017). As the key training target for education poverty alleviation and compulso-

ry education, the educational resources and investment obtained in rural poverty-

stricken areas was an achievement of breakthrough growth. According to the statistics, 

during the period of the 12th Five-Year Plan, 90% of the central government education-

al funds for transfer payment were used in the central and western regions, part of 

which was mainly used in poor rural areas (Zhu, 2016).  

Although the funds invested in schools in poor rural areas was continued to in-

crease, many scholars have shown that there is an imbalance in the allocation of educa-

tional resources. When the investment is uneven, the government obviously focuses on 

the proportion of investment in hardware. A lot of work has been done in transforming 

schools with weak strengths and narrowing the gaps in school hardware facilities, but 

not enough attention has been paid to the construction of “software” in schools (Cheng, 

2015). In the process of education poverty alleviation and development, although many 

schools in poverty-stricken areas have been built into “the most beautiful buildings in 

the rural region”, the quality of education is difficult to improve; there are still serious 

problems in the allocation of educational resources in poverty-stricken areas (Li and 

Xing, 2018). 

In fact, the scholarship has paid attention to the educational investment on 

school level and has identified its relationship with academic performance. The earliest 

research can be traced back to James Coleman’s Coleman Report in 1966, which re-

portedly has little to do with school resources and students’ academic performance 

(Coleman et al., 1966). This conclusion has aroused widespread controversy, leading 

many scholars to devote themselves to study the impact of school resource allocation on 

students’ academic performance. Three major factors of school expenditure (including 

school expenditure, and the scale of teachers and classes) are considered as important 

parts of education investment (Hanushek, 2002). Studies of the relationship between 

school expenditures and students’ achievements has also presented an  inconsistent con-

clusion: increasing educational facilities was not enough to improve students’ academic 

performance demonstrated by the research results of Angrist and Lavy in 1999; but 

Dewey et al. (2000) found that the increase of school expenditures can do improve stu-

dents’ academic performance.  

Why did research on the relationship between school expenditure and academic 

performance not reach a consistent conclusion? The reasons are as follows: First, differ-

S 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 147 

ent scholars use different variables, and the second, statistical methods are also diverse. 

In addition, students’ academic performance may be affected by factors such as family 

background, in addition to the influence of school resource allocation. If ignore these 

variables, the final result will be biased. At the same time, few people have conducted 

research and analysis on the relationship between different aspects of school expendi-

ture and students’ academic performance. The goal of this paper is to analyze the ex-

penditure on school level and to explore the relationship between different aspects of 

school expenditure and students’ academic performance. The rest of this paper is orga-

nized as follows. The next section of the paper describes our sample selection, data, and 

empirical methods. The third section presents the results. The final section discusses 

and concludes. 

Method 

Sampling 

The data were collected from the project “Survey on Basic Situation of Primary Schools 

in Poor Rural Areas” conducted by the Center for Experimental Economics in Educa-

tion of Shaanxi Normal University. The project was carried out in May, 2015, and im-

plemented among the rural schools in the four provinces of Q, N, G and S in northwest 

China.  

Stratified random sampling is used to select a total of 94 rural schools among 

38 poverty-stricken counties of four provinces. There are 46 schools from G province, 

16 from N, 14 from Q and 18 from S. A total of 6,497 students are randomly selected 

from 1-2 classes in the fourth and fifth grades of each school. In the survey, half of the 

students in each class are randomly selected to take standardized math test, and the oth-

er half take standardized Chinese test. The distribution of the sample in each province is 

shown in Table 1. The sample size was large and the coverage was wide. Therefore, the 

data obtained were representative. 

Table 1. Distribution of Study Sample. 

  # of Schools # of Students 
# of Students 

Taking Chinese Test 

# of Students 

Taking Math Test 

 Total 94 6,497 3,278 3,219 

Province 

G 46 2,366 1,204 1,162 

N 16 1,955 977 978 

Q 14 1,230 622 608 

S 18 946 475 471 

Gender 
Male - 3,295 1,642 1,653 

Female - 3,202 1,636 1,566 

Grade 
4th Grade - 3,136 1,587 1,549 

5th Grade - 3,361 1,691 1,670 

Data Source: Authors’ survey (2015) 

 

 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 148 

Data Collection  

The survey was consisted of three parts: the expenditures at school level; basic infor-

mation of schools, teachers, students, and parents; students’ mathematics and Chinese 

standardization tests. This corresponds to the independent variables, control variables 

and dependent variables in this study, which are described in three parts as follows. 

 

Expenditures at School Level (Independent Variable) 

In the questionnaire of schools’ basic information, we interviewed the principals to-

wards 10 expenditure items at school level, including: public utilities expenditure, of-

fice supplies expenditure, teaching supplies expenditure, teacher welfare expenditure, 

teacher training expenditure and canteen worker salary expenditure, non-teacher staff 

salary expenditure, student learning materials expenditure, student scholarship expendi-

ture and the expenditure on school maintenance. On the basis of the expenditure items, 

we divided it into four aspects: “Expenditure on students”, “Expenditure on teachers”, 

“Expenditure on schools (administrative affairs)” and “Other Expenditure”. Among 

them, “student learning material expenditure” and “student scholarship expenditure” are 

classified as “Expenditure on students”; “expenditure on teacher training” and “ex-

penditure on teacher welfare” are categorized as Expenditure on teachers; “Public utili-

ties expenditure” “office supplies expenditure” “school maintenance expenditure” and 

“teaching supplies expenditure” are classified as Expenditure on schools (administrative 

affairs); “canteen worker salary expenditure” and “non-teacher staff salary expenditure” 

are classified as Other expenditures (see Table 2). At the same time, the expenditures 

on students and teachers are regarded as the expenditures on “software” of schools in 

this paper, and the expenditures on school (administrative affairs) as the expenditures 

on the “hardware” of schools.  

Table 2. Items and Aspects of Expenditure at School Level. 

 
Expenditure Aspect Expenditure Item 

Expenditures at School Level 

Expenditure on students 
Student learning material expenditure 

Student scholarship expenditure 

Expenditure on teachers 
Expenditures on teacher training 

Expenditures on teacher welfare 

Expenditure on schools 

Public utility expenditure 

Office supplies expenditure 

School maintenance expenditure 

Teaching supplies expenditure 

Other expenditure 
Canteen worker salary expenditure 

Non-teacher staff salary expenditure 

Data Source: Authors’ survey (2015) 

 

 

 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 149 

Data on Schools, Teachers, Students and Parents (Control Variables) 

In the questionnaire, we also collected the data at the levels of schools and teachers. The 

school level variables mainly include: the number of students in the school, the student-

teacher ratio, and the service time of the school to the farthest village; Variables at the 

teacher level mainly include: gender of teacher, whether the first degree is college, 

teaching age, and whether they are working at a public school, including Chinese teach-

er and math teacher. A large number of studies have shown that the variables selected 

above about school and teacher has impact on students’ academic performance (Todd & 

Wolpin, 2007; Sun et al., 2009; Xue and Wang, 2009).  

In the questionnaire of basic information of students and their parents, we col-

lected variables that are at student level, including age, gender, ethnicity, grade and 

boarding status. At the same time, the socioeconomic characteristic variables of the par-

ents are also collected, including: their education, whether they are migrant workers, 

household assets. It is found that the socioeconomic characteristics variables of individ-

uals and families selected above have great impact on students’ academic performance 

(Fryer & Levitt, 2004).  

 

Standardized Math and Chinese Tests (Dependent Variables) 

Data on the standardized math/Chinese scores were collected from math/Chinese tests 

administered as part of the survey. Each student in the sample took a standardized math 

or Chinese test. We selected a set of standardized Chinese and math test for students to 

measure their academic performance. Standardized Chinese and math tests are designed 

to be consistent with the syllabus and have been tested for several times so as to better 

gauge Chinese students’ academic performance.  

In this study, the scores of Chinese and math are used as dependent variables; 

in general, the score is well represented. Because of the different subjects tested and the 

difficulty of the questions between different grades, the measurement methods com-

monly used in previous studies, such as “parents’ evaluation of children’s academic 

performance” (Xue, 2014) and the grades reported by students themselves (Dang, 2007), 

may cause biased.  

Standard Chinese or math scores are the result of standardizing the raw scores 

of Chinese or math test. This comparison is performed in two grades, making the score 

comparable across grades. If the standard score is higher than 0, it means that the stu-

dent’s Chinese or math score is higher than the average score of the student. 

 

Sample Characteristics 

The descriptive statistical results of sample are shown in Table 3. 

 

Model 

 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 150 

 

Table 3. Variable Description and Descriptive Statistics. 

Variable level Variable  Variable description Mean SD 

Student and Par-
ent Level 

Age Year 11.5 1.09 

Gender 1 = Female; 0 = Male  0.49 0.50 

Ethnicity 1 = Han; 0 = Minorities 0.66 0.47 

Grade 1 = 5th grade; 0 = 4th grade 0.51 0.50 

Boarding status 
1 = Board at school; 0 = Not board 
at school 

0.24 0.43 

Education of father 
1 = Junior high school and above; 0 
= Below junior high school 

0.45 0.50 

Education of mother 
1 = Junior high school and above; 0 
= Below junior high school 

0.28 0.45 

Father migrated  1 = Yes; 0 = No 0.54 0.50 

Mother migrated  1 =Yes; 0 = No 0.28 0.45 

Household assets Standardized household assets 0.04 1.10 

Chinese Teacher-
Level 

Gender 1 = Male; 0 = Female 0.42 0.49 

First degree is college 1 = Yes; 0 = No 0.64 0.47 

Teaching age 1 ≥ 10 yrs; 0 < 10 yrs  0.50 0.50 

Work at a public school  1 = Yes; 0 = No 0.87 0.34 

Mathematics 
Teacher-Level 

Gender 1 = Male; 0 = Female 0.58 0.49 

First degree is college 1 = Yes; 0 = No 0.56 0.50 

Teaching age 1 ≥ 10 yrs; 0 < 10 yrs  0.52 0.50 

Work at a public school  1 = Yes; 0 = No 0.89 0.31 

School-Level 

Number of students in 
school 

Unit 401 424 

Student-teacher ratio % 17.0 20.0 

The time from school to 
the farthest village 

Minutes 60.3 36.8 

Data Source: Authors’ survey (2015) 

 

 

Based on the above analysis, the econometric model to analyze the impact of different 

aspects of school expenditure on students’ academic performance is as follows: 

Yis = βo + β1 Expends + γ Xi + η Ss + α Ts + εi 

Where Yis is the standardized math or Chinese score of student i at school s, Expends 

refers to the variable of expenditures in different aspects at school level, which repre-

sents the expenditures on students, teachers and school (administrative affairs) and oth-

er aspects, respectively. Xi represents the variables of student and family, including the 

age, gender, ethnicity, grade, boarding status, education level of parents, whether par-

ents are migrated and family assets. Ts represents the variables at school level, including 

the number of students in the school, the ratio of students to teachers, and the service 

time from the school to the farthest village. Ss refers to the variables at the teacher level, 

including the gender of the Chinese or math teacher, whether the first degree is college, 

teaching age and whether they are working at a public school. 

Holding student/household/teacher/school characteristics constant and control-

ling for county fixed effect, β1 represents the effect of expenditures in different aspects 

on students’ academic performance (indicating that if the expenditure in a certain aspect 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 151 

increases from 0 to 1, the student’s Chinese or math score will change by the standard 

deviations of β1). 

Results 

The Proportion of Expenditure in Each Aspect at School Level 

In the survey, the research team carefully recorded the expenditure amount of each 

aspect at school level. Based on the expenditure amount of each aspect and the 

amount of total expenditure, the proportion of each aspect and its expenditure is 

obtained by calculating. Among the expenditures of each aspect, the ratio of ex-

penditure on students is the lowest, 4%; the ratio of expenditure on schools (admin-

istration) is up to 72%; the ratio of expenditure on teachers is 8%, and other ex-

penditure is 15%. It can be seen that expenditure on students and teachers is very 

low, but expenditure on school hardware (school administration) is very high. 

 

The Relationship between Expenditures of Each Aspect at School Level 

and Students’ Chinese Academic Performance   

As shown in Table 4, holding student/household/teacher/school characteristics constant 

and controlling for county fixed effect, there is a positive correlation between the ex-

penditures on students and teachers and students’ standardized Chinese scores. While 

the expenditures on school (administrative affairs) are negatively correlated with stu-

dents’ Chinese standardization scores; other expenditures have nothing to do with stu-

dents’ standardized Chinese scores. 

Table 4.  The Correlation between Expenditures in Each Aspect at 
School Level and Students’ Chinese Academic Performance. 

 Standardized Chinese Score 

 (1) (2) (3) (4) 

Expenditures on Students 1.34***(0.42)    

Expenditures on Teachers  0.83**( 0.34)   

Expenditures on Schools   -0.34***(0.16)  

Other Expenditures    -0.12(0.22) 

Controlling for Child and Parent 
Characteristics 

Yes Yes Yes Yes 

Controlling for Chinese Teach-
er Characteristics 

Yes Yes Yes Yes 

Controlling for School Charac-
teristics 

Yes Yes Yes Yes 

County Fixed Effects Yes Yes Yes Yes 

N 3,278 3,278 3,278 3,278 

R
2
 0.27 0.27 0.27 0.27 

Notes: Robust standard error adjusted for clustering at the school level are reported in parentheses *Significant at 
10%; **Significant at 5%; ***Significant at 1% 

Data Source: Authors’ survey (2015) 

 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 152 

Specifically speaking, if the expenditure on students increases from 0 to 1, the 

students’ Chinese scores will be increased by 1.34 standard deviations, it can also be 

said that if the expenditure on students increases by 1 percentage point, the students’ 

Chinese scores will be increased by 0.0134 standard deviations, the increase of scores is 

statistically significant at the 1% level. If the expenditure on teachers increases from 0 

to 1, students’ Chinese scores will be increased by 0.83 standard deviations (if the ex-

penditure on teachers increases 1 percentage, it will lead to an increase of 0.0083 stand-

ard deviations on students’ Chinese scores), the increase in scores is statistically signifi-

cant at the 5%; If the expenditure on school increases from 0 to 1, the students’ Chinese 

scores will be decreased by 0.34 standard deviations (if the expenditures on school in-

creases by 1 percentage point, it will cause a decrease of 0.0034 standard deviations on 

students’ Chinese scores), the reduction of score is statistically significant at the 1% 

level; Other expenditure have nothing to do with students’ Chinese scores. 

 

The Relationship between Expenditures of Each Aspect at School Level 

and Students’ Math Academic Performance  

As shown in Table 5, holding student/household/teacher/school characteristics constant 

and controlling for county fixed effect, expenditures on students and on other aspects 

are positively correlated with student’s standardized math scores; expenditures on 

school (administrative affairs) are negatively correlated with the student’s standardized 

math scores; the expenditures on teachers have nothing to do with the student’s stand-

ardized math scores. 

Table 5. The Correlation between Expenditures in Each Aspect at 
School Level and Students’ Math Academic Performance. 

 Standardized Math Score 

 (1) (2) (3) (4) 

Expenditures on Students 2.00***( 0.47)    

Expenditures on 
Teachers 

 0.46( 0.36)   

Expenditures on Schools   -0.57***(0.17)  

Other Expenditures    0.39*(0.23) 

Controlling for Child and 
Parent Characteristics  

Yes Yes Yes Yes 

Controlling for Math 
Teacher Characteristics  

Yes Yes Yes Yes 

Controlling for School  
Characteristics 

Yes Yes Yes Yes 

County Fixed Effects  Yes Yes Yes Yes 

N 3,219 3,219 3,219 3,219 

R
2
 0.20 0.20 0.20 0.20 

Notes: Robust standard error adjusted for clustering at the school level are reported in parentheses *Significant at 
10%; **Significant at 5%; ***Significant at 1% 

Data Source: Authors’ survey (2015) 

 

 

 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 153 

Specifically, if expenditure on students increases from 0 to 1, the student’s 

math score will increase by 2 standard deviations. It can also be said that if expenditure 

on students increases by 1 percentage point, the student’s math score increases by 0.02 

standard deviations, the increase of scores is statistically significant at the 1% level; if 

the other expenditures increase from 0 to 1, the student’s math score will increase by 

0.39 standard deviations (if other expenditure increases 1 percentage, it will lead to an 

increase of 0.0039 standard deviations on students’ math scores), the increase in scores 

is statistically significant at the 10%; If the expenditure on school increases from 0 to 1, 

the students’ math scores will be decreased by 0.57 standard deviations (if the expendi-

tures on school increases by 1 percentage point, it will cause a decrease of 0.0057 

standard deviations on students’ math scores), the reduction of score is statistically sig-

nificant at the 1% level; expenditure on teachers have nothing to do with students’ math 

scores. 

 

The Relationship between the Expenditures on Software and Hardware 

and Students’ Academic Performance 

Taking the expenditures on students and teachers as the expenditure on “software” and 

the expenditure on school (administrative affairs) as the expenditure on “hardware”, we 

make a further analysis of the relationship between the expenditures on “software” and 

“hardware” and students’ Chinese and math academic performance. The results show 

that, as shown in Table 6. Expenditures on “software” has a significant positive impact 

on students’ Chinese and math scores, while the expenditures on “hardware” has a huge 

negative impact on that. Among them, if the expenditure on “software” increases from 0 

to 1, students’ Chinese score will be increased by 1 standard deviation, and students’ 

math score will be increased by 0.91 standard deviations, the increase of scores is statis-

tically significant at the 1% level. If expenditure on “hardware” increases from 0 to 1, 

students’ Chinese and math scores will be decreased by 0.34 standard deviations and 

0.57 standard deviations respectively, the reduction of scores is statistically significant 

at the 1% -5% levels. 

Conclusions and Suggestions 

This study used representative data to explore the current state of expenditure on school 

level in poor rural primary schools and correlation to students’ academic performance. 

According to results, primary schools in poor rural areas are over-emphasizing the ex-

penditure on school administration (“hardware”), up to 72%, while expenditure on stu-

dents and teachers (“software”) accounted for only 12%. The results showed that in 

terms of expenditures on “software”, both expenditures on students and teachers are 

significantly positively correlated with students’ Chinese and mathematics performance, 

but the “hardware” expenditures of school administration are significantly negatively 

correlated with students’ Chinese and mathematics performance. Based on the results, 

we propose corresponding countermeasures and recommendations. 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 154 

 

Table 6. The Correlation between Expenditures on Schools’ Software 
and Hardware and Students’ Academic Performance. 

 Standardized 

Chinese Score 

Standardized 

Math Score 

 (1) (2) (1) (2) 

Expenditures on Software 1.00***(0.26)  0.91***(0.27)  

Expenditures on Hardware  -0.34**(0.16)  -0.57*** (0.17) 

Controlling for Child And Parent Char-
acteristics  

Yes Yes Yes Yes 

Controlling for Chinese/Math Teacher 
Characteristics 

Yes Yes Yes Yes 

Controlling for School Characteristics Yes Yes Yes Yes 

County Fixed Effects  Yes Yes Yes Yes 

N 3,278 3,278 3,219 3,219 

R
2
 0.27 0.27 0.20 0.20 

Notes: Robust standard error adjusted for clustering at the school level are reported in parentheses *Significant at 
10%; **Significant at 5%; ***Significant at 1% 

Data Source: Authors’ survey (2015) 

 

To Improve and Optimize the School Expenditure and Increase the Ex-

penditures on Students and Teachers 

At present, the expenditure structure at school is of “material-oriented” model, that 

means investment in schools’ “hardware” is higher, and investment in school’s “soft-

ware” is lower. However, there is a positive correlation between the expenditure of the 

school “software” and students’ academic performance. In terms of this, we need to 

change the existing expenditure of “material-oriented” model, and increase the propor-

tion of expenditures on students and teachers, which is to make the transformation of 

the investment mode of “material-oriented” to “people-oriented” so as to stimulate the 

creativity of students and teachers, and jointly improve the creative vitality of talents. 

 

Targeted Measures Should Be Taken in the Process of Education Pov-

erty Alleviation  

In the process of implementing the strategy of targeted education poverty alleviation, 

attention should be paid to the “precision” and “accuracy” of fiscal policies. In order to 

achieve targeted poverty alleviation via education, on the one hand, the object should be 

targeted, and the resources of education poverty alleviation should be effectively allo-

cated to the people who have urgent needs: the investment of software supporting ser-

vice for students and teachers should be improved to maximize the efficiency of re-

source allocation. On the other hand, the measures should be taken precisely: improve 

the teaching ability of teachers in poor areas through a variety of ways to promote the 

professional development of teachers; the financial aid to students is transformed from 



Li, et al., Expenditure on School Level and Students’ Academic Performance 

Vol.2, No. 1, 2019 155 

indemnificatory to all-round pattern, so that students and teachers in poor areas can be 

assisted in the aspects of ideology, abilities and growth (Liu & Liu, 2018). 

 

 

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Received: 10 April 2019 

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Accepted: 05 May 2019 

 

 
The Chinese version of this article has been published in J East Chin Normal Univ (Edu Sci) 

2018; 36(6):100-106,158. The English version has been authorized for being publication in 

BECE by the author(s) and the Chinese journal. 

李莉莉, 关宏宇, 罗斯高. 学校层面的支出和学生学业表现的相关关系—基于西部贫困农村

地区的实证研究. 华东师范大学学报(教育科学版) 2018; 36 (6):100-106, 158. 


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