General or vocational? The tough choice in the Chinese education policy

Int. J. Educational Development, Vol. 18, No. 4, pp. 289–304, 1998  1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0738-0593/98 $19.00 ⫹ 0.00

Pergamon

PII: S0738-0593(98)00026-1

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY JIN YANG School of Education, Bolton Institute, Bolton BL2 1JW, UK Abstract — China has made great efforts to vocationalise its senior secondary education in the belief that vocational education better than general education can prepare young people with the skills needed for employment in industry. This runs against a large empirical literature from the last few decades arguing strongly against vocational education on employment opportunity and cost-effectiveness grounds. This paper examines the relationship between employees’ educational (and other) backgrounds and their performance in the workplace, as well as their income, based on a survey of 1433 employees in two cities in China. It concludes that pre-employment education gives better work performance, but that vocational education does not lead to better performance than general education.  1998 Elsevier Science Ltd. All rights reserved

INTRODUCTION Empirical studies from the last few decades argue strongly against vocational schooling because it does not improve employment opportunities and is not cost-effective. Foster’s (Foster, 1965) seminal study on the ‘vocational school fallacy’ was one of the first to point out the second-best nature of vocational training as a way of increasing the relevance of schooling to occupational futures. Metcalf (1985) has reviewed studies that examine whether vocational and technical schools are a costeffective approach to investing in human resources. In general, Metcalf’s review concludes that rates of return are usually sufficiently positive to justify training. However, short rather than long courses tend to be more costeffective and informal and work-based training tends to be more cost-effective than formal, external training in vocational and technical schools separated from productive organisations. Between 1966 and 1988, more than 20 studies examining the effectiveness of technical and vocational education have been identified (Haddad et al., 1990). Some of them compare academic and technical and vocational education. They reinforce the view that short courses have higher rates of return than longer ones. However, there is a wide variation in the findings relating to different systems. In some

cases productivity gains can be identified (Fuller, 1976), higher rates of return than with academic schooling are evident (Chung, 1987; Ziderman, 1988), and graduates of technical and vocational training are more valued in the labour market (Chin-Aleong, 1988). In others there is little labour market advantage for technical and vocational graduates (Psacharopoulos and Loxley, 1985; Moock and Bellow, 1988), suggesting that the benefits of training are not always reflected in labour market signals. Some recent studies have shown that when employment opportunities are available or growing, and a match is made between training and available jobs, vocational schooling has produced higher wages (in Brazil and Hong Kong), and better returns on investment (in Israel) than general education does (Arriagada and Ziderman, 1992; Chung, 1990; Neuman and Ziderman, 1991, respectively). The social rate of return (computed on the basis of one’s monetary earnings associated with a given type of education and the total unit cost of that type of education) for secondary vocational education in Thailand, on average and across disciplines, exceeds that of general education, with 11.4% for the former compared with 6.7% for the latter (World Bank, 1990). More frequently, however, favourable conditions, such as a match between training and available jobs, are not present, and net returns to vocational schooling are comparatively low (Middleton et al., 1993).

289

290

JIN YANG

In the arena of dramatically changing Russia, general education that employees had acquired was more appropriate than their vocational training for the demands of production due to general education’s provision of foreign languages and computer literacy. Hence it is clear that not only vocational but also general education are factors which improve the worker’s competitiveness (Schachimanyan, 1994). Secondary technical and vocational education, in Singapore and Hong Kong, has grown rapidly since the mid-1970s but remains a relatively small sector in the overall education system (Morris, 1996). The vast majority of pupils follow a general/academic secondary school curriculum. In addition, much of the technical and vocational education has been provided by an agency (the Economic Development Board in Singapore and the Vocational Training Council in Hong Kong) outside the school system with close links to local industries. In contrast, in South Korea and Taiwan the provision of large-scale programmes of technical and vocational education has been a central element in long-term planning in the period following early industrialisation. This resulted in a heavy investment in, and channelling of pupils into, technical and vocational education in an attempt to provide for the future needs of the economy. It is also evident, however, that despite the promotion of technical/vocational schooling by authorities of South Korea and Taiwan, this sector continued to be considered a second-best alternative by pupils, parents and teachers. China has made great efforts to vocationalise its senior secondary education since 1978. Policy-makers believe that vocational education better than general education can provide young people with the skills needed for employment in industry. Vocational education is thus seen as a strategy that contributes to increased efficiency in educational investment. Industries and government agencies have appealed for more senior secondary vocational–technical schools, and the speed of vocationalisation of senior secondary education in China has been tremendous (Yang, 1996). The ratio of the enrolment of vocational education to that of general academic education at the senior secondary level of education rose from 19 : 81 in 1980 to 57 : 43 in 1995 (State Education Commission, 1996). However, the effectiveness of vocational edu-

cation in China is yet to be recognised. In China, no substantial empirical study has tested the validity of the assumption that vocational and technical education graduates are better equipped than academic school graduates in meeting employment demands. Only one recent Englishlanguage study tests this assumption with regard to the workplace in China. Min and Tsang (1990) compare the performance of vocational and technical school graduates and general education school graduates in a vehicle-manufacturing plant. They conclude that graduates of company-affiliated secondary vocational schools, holding jobs closely related to their training, are more satisfied and also more productive (in terms of work efficiency) as factory workers than graduates of secondary academic education. The explanation is that vocational school graduates are better prepared for their jobs. The expectations and skills they acquire in vocational schools match better the job characteristics of factory work in China. The establishment of the socialist market economy (SME) has radically changed the nature of the labour market and employment practices in the 1990s China. Under the SME, the allocation of resources is no longer controlled primarily by the government, and is no longer based on rigid distribution plans. Enterprises and individuals have more power to make decisions, to allocate resources according to market supply and demand, and to adjust prices for maximum economic returns. Some important development trends, such as diversified ownership, rapid technological change in the workplace, contracted rather than permanent employment, and increased labour force mobility, are emerging. Both employers and employees have more freedom to choose. The employment context of the labour force has changed dramatically (Yang, 1996). Employees with different education and training backgrounds might perform differently in the new context. The above review could suggest that there is a distinct lack of international consensus on the effectiveness of technical and vocational education. It is hoped that this paper would produce new evidence to the lasting academic debate. HYPOTHESES Since the early 1980s, it has been generally assumed by educational policy-makers in China

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY

that vocational education makes a more direct and greater contribution to the quality and productivity of the labour force than does general education and higher education (Meng et al., 1993). This assumption has been used to justify the further vocationalisation of senior secondary education to meet the needs of the SME (State Council, 1994). This paper examines the relationship between employees’ educational (and other) backgrounds and their performance in the workplace, as well as their income. If this assumption can be supported by empirical evidence, the current implementation of vocationalisation of senior secondary education could be in line with the implementation of the SME in China. The specific hypotheses to be tested are: 1. (a) From the perspective of employers, the higher the level of employees’ pre-employment education (that is, a sub-degree university/college education compared with a senior secondary level of education and compared with a junior secondary level of education), the better their perceived performance; (b) the higher the level of employees’ pre-employment education, the higher their income. 2. (a) From the perspective of employers, among employees who completed their senior secondary education, those who went through the vocational track perform better than those who went through the academic track; (b) among employees who completed their senior secondary education, those who went through the vocational track have a higher income than those who went through the academic track. 3. (a) From the perspective of employers, employees with an in-service education/ training perform better than those without; (b) employees with an in-service education/ training have a higher income than those without. DATA COLLECTION To collect data to test these hypotheses, a survey questionnaire was designed, and consisted of two parts. The first part collected information about employees’ record of both pre-employment and post-employment education and training; employment experience; current employ-

291

ment position and incomes. The second part collected employers’ opinions of employees’ performance via five independent variables: attitude to work; competence in current work; efficiency at work; co-operation with employers and other employees; and enthusiasm for knowledge and skill enhancement. Considering the disparity between provinces which are at different stages of economic development, and after consulting with colleagues in the State Education Commission of China, the author chose Changzhou City (near Shanghai) and Shijiazhuang City (near Beijing) for the survey. In Changzhou, the city’s Education Commission and Labour Department undertook the sampling for the survey and the distribution of the survey questionnaires. For the distribution of survey questionnaires, the Labour Department convened a meeting of the representatives of 29 sampled employers (with a total of 45,917 employees) to explain the purpose and procedures of the survey, and requested them to organise the survey. In Shijiazhuang, the city’s Education Commission, the Economy and Trade Commission and the Education Commission of Hebei Province undertook the sampling for the survey and the distribution of the survey questionnaires. For the distribution of the survey questionnaires, the city’s Economy and Trade Commission sampled nine enterprises (with a total employment of 14,247) and distributed the questionnaire to them. In summary, the survey included a total of 38 enterprises (with a total employment of 60,164). In terms of ownership, 23 enterprises were state owned, five collectively owned and 10 were foreign invested, joint stock and private enterprises. In terms of sectors of production, 26 enterprises were in manufacturing, seven in the retail and commercial services, and five in textile and chemical industries. The questionnaire was distributed to a total of 2000 employees, of which 1433 returned the questionnaire (a response rate 71.7%). Of the 1433 employees, 874 were male and 559 were female. Their last stage pre-employment education is provided in Table 1. Postemployment education/training of the 1433 employees included 812 cases (or 56.7%) of

292

JIN YANG Table 1. Last stage of the employees’ pre-employment education

Last-stage of preemployment educationa A: Sub-degree university/collegeb B: SSS which enrols GSSS graduates C: SSS which enrols GJSS graduates D: GSSS with a short period of training E: VSSS F: SWS G: GSSS H: GJSS with a short period of training I: GJSS Otherc

Level of education

Track of education at post and senior secondary level

Higher

No. of responses (n = 1433) 203

Post secondary

Vocational

82

Senior secondary

Vocational

92

Senior secondary

Academic

135

Senior secondary Senior secondary Senior secondary Junior secondary

Vocational Vocational Academic

119 268 203 136

Junior secondary

138 57

a SSS: specialised secondary school; GSSS: general senior secondary school; GJSS: general junior secondary school; VSSS: vocational senior secondary school; SWS: skilled workers’ school. b Can be considered as equivalent to HND in the U.K. c Those who did not supply the information or have various other types of education background such as university education leading to bachelor’s degree or even master’s degree.

various in-service education/training, while 621 (or 43.2%) had not participated in in-service education/training. The number of years of employment ranged from 0 to 22 years with a mean of 7.12 years, a median of 6.00 and a standard deviation of 4.67. As this study is only concerned with the performance of employees who have secondary and sub-degree higher education backgrounds, the last 57 cases (‘Other’ in Table 1) were excluded from the subsequent regression analysis. A further four questionnaires with incomplete answers about years of employment were also excluded from the analysis. In the case of the analysis relating to income, 46 cases (for total income) and 55 cases (for basic income) with incomplete questionnaires were also excluded. DATA ANALYSIS Standard multiple regression analysis has been used to investigate the relationships between employees’ educational, and other, backgrounds (as independent variables) and each of the five aspects of the employers’ assessments of their employees’ performance as well as employees’ income (as dependent variables). To use the multiple regression technique, the nominal variables were transformed into dummy coding. In addition, t-tests (for

independent samples) have been used to test the significance of the differences between the average perceived performances and between the average incomes of employees who have different educational, and other, backgrounds. Table 2 presents the results of the regression analysis, which include the standardised regression coefficients (beta), t-values, R, R2, F ratio, constant score, numbers of cases and significance levels. All values of the multiple correlation coefficient (R) for regression were significantly different from zero. Considering that this study concerns the relationships between level of employees’ preemployment education and their performance, and between the type of employees’ preemployment education and their performance, the nine types of pre-employment education have been reduced to the following four types in Tables 3 and 4 in order to simplify the analysis. 1. Higher education: A: sub-degree university/college course. 2. Vocational senior secondary level of education which prepares junior secondary school leavers for employment, includes: C: specialised technical secondary school (SSS) which enrols general junior secondary school (GJSS) graduates; E: vocational senior secondary school (VSSS); and

0.036 (1.32) 0.022 (0.82) 0.035 (1.16)

0.051 (1.88)

0.008 (0.31)

0.020 (0.67)

0.284 0.081 7.926** 3.389 1372

0.092 (3.17)**

0.108 (3.74)**

0.303 0.092 9.114** 3.674 1372

0.093 (3.24)**

0.169 (5.54)**

0.083 (2.91)**

0.089 (2.93)**

(3.32)** (2.03)* (3.23)** (0.14)

0.165 (4.64)**

0.170 (4.82)** 0.116 0.084 0.126 0.005

0.085 (2.53)*

0.090 (2.68)**

(2.85)** (1.63) (4.72)** (⫺0.25)

0.096 (2.92)**

0.100 (3.03)**

0.099 0.067 0.183 ⫺0.009

0.179 (4.63)**

0.035 (1.30)

Competence

0.230 (5.99)**

0.007 (0.28)

Attitude

(1.75) (0.90) (2.70)** (⫺0.10)

0.273 0.075 7.285** 3.459 1372

0.070 (2.34)*

0.014 (0.52)

0.045 (1.66)

0.124 (4.28)**

0.144 (4.97)**

0.107 (3.50)**

0.061 0.037 0.106 ⫺0.004

0.108 (3.04)**

0.021 (0.63)

0.071 (2.14)*

(2.57)* (0.90) (4.41)** (⫺0.15)

0.281 0.079 7.751** 3.648 1372

0.064 (2.12)*

0.014 (0.52)

0.057 (2.09)*

0.087 (3.01)**

0.064 (2.23)*

0.101 (3.29)**

0.090 0.037 0.172 ⫺0.006

0.152 (4.29)**

0.109 (3.23)**

0.062 (1.88)

0.158 (4.06)**

⫺0.066 (⫺2.46)*

⫺0.004 (⫺0.13)

0.149 (3.84)**

Co-operation

Efficiency

*p ⬍ 0.05; **p ⬍ 0.01; numbers in parentheses are the t-values for the beta weights.

R R2 F Constant N

Q7D: In-service education/training Q7D.A: Completed adult higher education Q7D.B: Undertaking adult higher education Q7D.C: Completed adult SSS Q7D.D: Undertaking adult SSS Q7D.E: Other type of inservice training

Q5.1: Years of employment

Q4D: Last stage of preemployment education Q4D.A: Sub-degree university/college Q4D.B: SSS which enrols GSSS graduates Q4D.C: SSS which enrols GJSS graduates Q4D.D: GSSS with a short period of training Q4D.E: VSSS Q4D.F: SWS Q4D.G: GSSS Q4D.H: GJSS with a short period of training

Q2D: Gender

Independent variables

Dependent variables

(3.40)** (2.37)* (3.82)** (0.02)

0.375 0.141 14.819** 3.252 1372

0.118 (4.07)**

0.032 (1.22)

0.087 (3.34)**

0.212 (7.57)**

0.168 (6.02)**

⫺0.004 (⫺0.15)

0.114 0.095 0.144 0.001

0.161 (4.70)**

0.125 (3.82)**

0.175 (5.51)**

0.277 (7.40)**

0.020 (0.79)

Enthusiasm

(2.32)* (5.00)** (3.54)** (6.71)**

(1.65) (5.08)** (3.68)** (6.28)**

⫺0.031 (⫺1.17) ⫺0.013 (⫺0.48)

⫺0.055 (⫺2.08)* ⫺0.024 (⫺0.93)

0.407 0.166 17.355** 353.7 1326

0.404 0.163 16.885** 222.9 1317

0.070 (2.40)*

0.015 (0.52)

⫺0.015 (⫺0.53)

0.063 (2.16)*

0.014 (0.49)

0.309 (10.41)**

0.056 0.206 0.140 0.224

0.110 (3.18)**

0.144 (4.40)**

0.195 (6.06)**

0.268 (7.09)**

0.109 (4.18)**

Basic income

0.011 (0.38)

0.292 (9.83)**

0.078 0.199 0.134 0.237

0.148 (4.37)**

0.119 (3.64)**

0.162 (5.09)**

0.174 (4.67)**

0.175 (6.74)**

Total income

Table 2. Results of the multiple regression analysis (the values in the main body of the table are standardised Beta weights, unless stated otherwise)

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY 293

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JIN YANG

Table 3. The mean values, and their standard deviations (in parentheses), of employees’ perceived performance by type and level of pre-employment education and category of years of employment Type and level of pre-employment education

Years of No. of cases employment

Attitude

Competence

Efficiency

Co-operation Enthusiasm

1. Sub-degree higher education

0–4 5–8 9–12 13–16

84 75 28 16

4.11 4.27 4.32 4.31

(0.56) (0.64) (0.55) (0.60)

3.76 4.10 4.18 4.06

(0.70) (0.65) (0.55) (0.57)

3.78 4.03 4.00 4.13

(0.66) (0.64) (0.54) (0.62)

3.94 4.09 4.07 4.19

(0.63) (0.66) (0.47) (0.54)

4.00 4.08 4.14 3.88

(0.64) (0.69) (0.52) (0.81)

2. Vocational postsecondary education

0–4 5–8 9–12 13–16

28 26 16 11

4.04 4.08 4.25 4.36

(0.43) (0.39) (0.45) (0.67)

3.79 4.08 4.00 4.09

(0.63) (0.56) (0.37) (0.70)

3.79 4.04 3.94 4.00

(0.57) (0.45) (0.57) (0.63)

3.86 4.04 4.00 4.00

(0.65) (0.60) (0.52) (0.89)

4.07 4.12 4.31 4.00

(0.72) (0.43) (0.60) (0.89)

3. Vocational senior secondary education

0–4 5–8 9–12 13–16

235 149 75 20

3.97 3.87 4.02 4.20

(0.64) (0.61) (0.59) (0.62)

3.71 3.82 3.95 4.00

(0.67) (0.59) (0.61) (0.65)

3.67 3.71 3.79 3.85

(0.72) (0.63) (0.66) (0.75)

3.92 3.75 3.91 4.25

(0.65) (0.65) (0.66) (0.72)

3.76 3.62 3.64 3.65

(0.74) (0.74) (0.82) (0.81)

4. Academic senior secondary education

0–4 5–8 9–12 13–16

69 60 77 116

4.36 4.02 4.09 4.25

(0.66) (0.54) (0.52) (0.69)

4.12 3.77 3.95 4.15

(0.83) (0.59) (0.56) (0.64)

4.07 3.77 3.75 4.09

(0.77) (0.59) (0.61) (0.61)

4.25 3.87 4.01 4.27

(0.67) (0.60) (0.66) (0.62)

4.06 3.73 3.62 3.90

(0.78) (0.63) (0.83) (0.92)

0–4 5–8 9–12 13–16

304 209 152 136

4.06 3.91 4.06 4.24

(0.66) (0.59) (0.55) (0.59)

3.81 3.80 3.95 4.13

(0.73) (0.59) (0.58) (0.64)

3.76 3.73 3.77 4.05

(0.75) (0.62) (0.64) (0.64)

3.99 3.78 3.96 4.26

(0.67) (0.63) (0.66) (0.64)

3.82 3.65 3.63 3.86

(0.76) (0.71) (0.82) (0.90)

0–4 5–8 9–12 13–16

75 84 66 37

3.72 3.70 3.79 4.02

(0.71) (0.53) (0.54) (0.64)

3.55 3.52 3.83 3.78

(0.62) (0.61) (0.67) (0.63)

3.53 3.52 3.79 3.78

(0.60) (0.57) (0.69) (0.63)

3.67 3.71 3.72 3.95

(0.58) (0.55) (0.62) (0.66)

3.39 3.37 3.32 3.49

(0.75) (0.60) (0.71) (0.73)

3 and 4. On average (senior secondary education on average) 5. Junior secondary education

Total

1347

4.03 (0.62)

F: skilled workers’ school (SWS). 3. Academic senior secondary level of education which prepares junior secondary school leavers for higher education, includes: D: GSSS with a short period of training; and G: GSSS. 4. Junior secondary level of education, includes: H: GJSS with a short period of training; and I: GJSS. To make the analysis more explicit, in addition to the result of the regression analysis, the means for dependent variables are provided. Tables 3 and 4 show the means for the dependent variables and types of pre-employment education with years of employment subdivided into four categories: 0–4 years, 5–8 years, 9–12 years and 13–16 years (only 25 cases had 17– 22 years of employment and these were excluded from these tables).

3.86 (0.66)

3.80 (0.67)

3.94 (0.65)

3.74 (0.78)

The results of the multiple regression analysis as well as the means of dependent variables were used to test the hypotheses devised in Section 3 of this paper. RESULTS AND DISCUSSION The Perceived Performance: Testing Hypotheses A sub-degree university/college education is clearly the most important type of pre-employment last-stage education. In four (attitude, competence, efficiency and enthusiasm) of the five aspects of employees’ performance, subdegree university/college has the greatest coefficients (0.230, 0.179, 0.149, and 0.277 respectively) (see Table 2), and in the other aspect (co-operation) it has the second greatest coefficient (0.158). Senior secondary level school (including vocational senior secondary

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY

295

Table 4. The mean values, and their standard deviations (in parentheses), of employees’ incomes by type and level of preemployment education and category of years of employment Type and level of pre-employment education

Years of employment

1. Sub-degree higher education

0–4

80

474.7 (125.3)

79

353.7 (102.1)

5–8 9–12 13–16 0–4

71 25 16 28

528.7 602.5 605.4 460.2

(121.4) (145.2) (171.3) (149.0)

74 25 16 28

421.3 474.0 464.9 357.5

(120.9) (128.4) (163.2) (111.4)

5–8 9–12 13–16 0–4

25 15 10 226

573.4 621.5 656.4 463.3

(145.3) (142.3) (185.6) (143.2)

26 14 10 223

404.9 483.1 520.3 316.0

(146.3) (165.9) (135.4) (116.7)

5–8 9–12 13–16 0–4

147 71 20 63

513.6 527.8 605.3 445.5

(132.0) (100.8) (194.2) (167.1)

146 72 20 67

361.7 398.0 447.6 282.1

(113.9) (101.8) (157.2) (147.1)

5–8 9–12 13–16 0–4

59 76 112 289

578.2 525.1 572.1 459.4

(164.6) (107.6) (122.8) (148.6)

59 76 107 290

425.2 398.4 406.3 308.2

(148.2) (111.4) (126.7) (124.9)

5–8 9–12 13–16 0–4

206 147 132 75

532.1 (144.7) 526.4 (104.0) 577.1 (135.6) 492.0 (129.9)

205 148 127 75

380.0 389.2 412.8 336.7

(127.6) (106.5) (132.1) (136.0)

5–8 9–12 13–16

83 65 34

550.8 (142.9) 528.5 (134.5) 570.6 (209.3)

81 62 32

399.9 (133.2) 361.8 (107.8) 416.2 (148.0)

1301

519.3 (146.3)

1292

373.8 (132.6)

2. Vocational postsecondary education

3. Vocational senior secondary education

4. Academic senior secondary education

3 and 4. On average (senior secondary education on average)

5. Junior secondary education

Total a

No. of cases in total income

Total income (RMB yuana per month)

No. of cases in basic income

Basic income (RMB yuan per month)

1 U.K pound = 12.9 RMB yuan (July 1996).

and academic senior secondary) education also shows a substantial relationship with employees’ performance (0.183 for GSSS in attitude, 0.165, 0.108 and 0.161 for GSSS with a short period of training in competence, efficiency and enthusiasm respectively, and 0.172 for GSSS in co-operation), albeit less so than it is with sub-degree higher education except in one of the five aspects of employees’ performance (co-operation). At the junior secondary level of education, GJSS with a short-

period training has no significant relationship with any of the five aspects of employees’ performance. Taking into account that the constant values of the equations embody the scores of employees with a GJSS education, the above evidence suggests that from the employers’ perspective the higher the level of pre-employment education, the better the employees’ perceived performance. This finding is endorsed by the means for each of the dependent variables concerning employees’ performance. Table 3 shows that

296

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• in all of the five aspects of employees’ performance and, in all of the four categories of years of employment, employees with a junior secondary level of education always have the smallest means for performance; • in all of the five aspects of employees’ performance and in most of the four categories of years of employment, employees with a higher education have the greatest means for performance; and • the means for performance of employees with a senior secondary level of education (vocational senior secondary and academic senior secondary on average) lie between those for higher education and those for junior secondary education. The result of t-tests of these differences (shown in Table 5) confirms that • employees with a sub-degree higher education had significantly greater means in three of the five aspects of employees’ performance (attitude, efficiency and enthusiasm) than did employees with a senior secondary education; • employees with a senior secondary education had significantly greater means in all the five aspects of employees’ performance than did employees with a junior secondary education. This evidence supports hypothesis 1(a) that the higher the level of employees’ pre-employment education, the better their performance. At the senior secondary level, a vocational track of education (which includes SSS which enrols GJSS graduates, SWS and VSSS) does not have stronger relationships with employees’ performance than an academic track education (which includes GSSS with a short-period training and just GSSS), since in all of the five regression equations relating to employees’ performance, the two categories of the academic track education have greater coefficients than any of the three categories of the vocational track (Table 2). The results of the t-test for the difference between the average performance (Table 6) of the employees with a vocational track education and that of the employees with an academic track educations, for each aspect of performance, endorses this finding. In the first category of years of employment (0–4), employees with an academic senior secondary education have significantly greater means for performance than did those with a vocational senior secondary education. In the other three

categories of years of employment, there are no significant differences between the means for performance of the two types of employees. In most of the cases the means for performance of employees with an academic senior secondary education are, however, marginally greater than that of those with a vocational senior secondary education. Employees with a technical and vocational education at the senior secondary level of education, at least as that education was recently conceived, do not seem from the employers’ perspectives to have performed better at the workplace than employees with an academic education at the senior secondary level of education. This result does not support hypothesis 2(a) that, from the employers perspective, among employees who completed their senior secondary education, those who went through the vocational track performed better than those who went through the academic track. In-service higher education shows significant relationships with each of the five aspects of employees’ performance. Other types of in-service education and training, including adult specialised secondary school and in-service training, seem to have limited relationships with any aspect of performance. For example, completed adult specialised secondary education shows moderate relationship with two of the five aspects of employees’ performance (cooperation and enhancement) and the other type of in-service training shows moderate relationships with three of the five aspects of performance (efficiency, co-operation and enhancement). As can be seen in Table 7, taking the five categories of in-service education/training as a whole, in each of the five aspects of performance, the mean for the performance of employees with an in-service education/training is greater than that for the performance of those without. The result of a ttest shows that the difference between the means for performance of employees with an in-service education/training and the means for performance of those without is significant in each of the five aspects of employees’ performance (also in Table 7). This result supports hypothesis 3(a) that, from the employers’ perspective, employees with an in-service education/training performed better than those without.

203

817

262

Higher education

Senior sec. education

Junior sec. education

3.77

4.06

4.21

Mean

0.61

0.62

0.60

6.11**

3.19**

Attitude S.D.a t-value

a

Standard deviation; *p ⬍ 0.05; **p ⬍ 0.01.

No. of cases

Level of education

3.65

3.89

3.97

Mean

0.64

0.66

0.67

5.05**

1.50

Competence S.D. t-value

3.63

3.81

3.93

Mean

0.63

0.69

0.64

3.57**

2.37*

Efficiency S.D. t-value

3.74

3.99

4.03

Mean

0.60

0.67

0.62

5.41**

0.85

Co-operation S.D. t-value

3.38

3.75

4.04

Mean

0.69

0.79

0.66

6.42**

5.30**

Enthusiasm S.D. t-value

Table 5. Means, standard deviations, and t-values for the differences between the means, of performance scores for each level of employees’ education

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY 297

3.87

Vocational 149

4.03

Vocational 75

116

a

4.25

4.20

Vocational 20

Academic

4.09

77

Academic

4.02

60

Academic

4.36

69

Academic

0.59

0.62

0.52

0.59

0.54

0.61

0.66

− 0.35

− 0.71

− 1.77

− 4.36**

4.15

4.00

3.95

3.95

3.77

3.82

4.11

3.71

0.62

Vocational 235

3.97

Mean

Attitude Type of No. of Mean S.D.a t-value education cases

Standard deviation; **p ⬍ 0.01.

13–16

9–12

5–8

0–4

Category of years of employment

0.64

0.65

0.56

0.61

0.59

0.59

0.83

0.67

− 0.95

− 0.01

0.57

− 3.67**

Competence S.D. t-value

4.09

3.85

3.75

3.79

3.77

3.71

4.07

3.67

Mean

0.61

0.75

0.61

0.66

0.59

0.63

0.77

0.72

− 1.54

0.32

− 0.58

− 4.02**

Efficiency S.D. t-value

4.27

4.25

4.01

3.91

3.87

3.75

4.25

3.92

0.62

0.72

0.66

0.66

0.60

0.65

0.67

0.65

− 0.11

0.99

− 1.19

− 3.58**

Co-operation Mean S.D. t-value

3.90

3.65

3.62

3.64

3.73

3.62

4.06

3.76

Mean

0.92

0.82

0.83

0.82

0.63

0.74

0.78

0.74

− 1.13

0.12

− 1.14

− 2.83**

Enthusiasm S.D. t-value

Table 6. The means, standard deviations, and t-values for the differences between means, of performance of employees with a vocational senior secondary education and of those with an academic senior secondary education

298 JIN YANG

587

Without

a

Standard deviations; **p ⬍ 0.01.

785

No. of cases

With

In-service education/training

3.97

4.09

Mean

0.65

0.60 3.52**

Attitude S.D.a t-value

3.78

3.92

Mean

0.69

0.64 3.79**

Competence S.D. t-value

3.69

3.88

Mean

0.69

0.64 5.24**

Efficiency S.D. t-value

3.87

4.01

0.64

0.67 4.04**

Co-operation Mean S.D. t-value

3.56

3.89

Mean

0.78

0.74 7.91**

Enthusiasm S.D. t-value

Table 7. The means, standard deviations and t-values for the difference between the means, for the performance of employees with an in-service education/training and of those without

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY 299

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Incomes: Testing Hypothesis All types of pre-employment education show a significant relationship with total income, and all types of pre-employment education except vocational senior secondary education show a significant relationship with basic income (Table 2). A sub-degree university/college education has the largest coefficient for basic income (0.268) and the third largest coefficient for total income (0.174), whereas a general junior secondary education with a short period of training has the largest coefficient for total income (0.237) and the second largest coefficient for basic income (0.224), yet the latter type of education has the smallest coefficients in all aspects of employees’ performance ( ⫺ 0.009, ⫺ 0.005, ⫺ 0.004, ⫺ 0.006 and 0.001) (Table 2). When looking further into the means for total and basic income of employees with different levels of education, employees with a subdegree higher education have both a higher total income (522.2) and a higher basic income (404.2) than employees with a senior secondary level of education (512.7 and 362.4 respectively), but the result of a t-test shows that only in basic income is the difference significant (t ⫽ 4.02, p ⬍ 0.01). Employees with a senior secondary education do not have a higher total income or a higher basic income than employees with a junior secondary education at all (530.6 and 373.6 respectively). These results do not in general support hypothesis 1(b) that the higher the level of employees’ pre-employment education, the higher their incomes. Comparing the average incomes of employees who received a vocational education with the average incomes of employees who received an academic education at the senior secondary level of education (Table 4): • among those who had been in employment for four years or less, employees with a vocational education had a higher total income (463.3 compared with 445.5) and a higher basic income (316.0 compared with 282.1); • among those who had been in employment for five to eight years, employees with a vocational education had a lower total income (513.6 compared with 578.2) and a lower basic income (361.7 compared with 425.2); • among employees who had been in employ-

ment for 9–12 years, the gaps in incomes between the two types of employees were very small in both total income (527.8 compared with 526.4) and basic income (398.4 compared with 389.2); and • among those who had been in employment for 13–16 years, employees with a vocational education had a higher total income (605.3 compared with 572.1) and a higher basic income (447.6 compared with 406.3). However, only for those who had been in employment for five to eight years is the difference in average incomes between employees who received a vocational education and employees who received an academic education, respectively, statistically significant, and this is the case for both total income (t ⫽ ⫺ 2.95, p ⬍ 0.01) and basic income (t ⫽ ⫺ 2.95, p ⬍ 0.01). In summary, these results seem to imply that employees who received a vocational senior secondary education did not earn more than employees who received an academic senior secondary education. This finding does not support hypothesis 2(b) that among employees who completed their senior secondary education, those who went through the vocational track had a better income than those who went through the academic track. Where in-service education and training is concerned, the most startling point is the lack of any substantial relationship between in-service higher or specialised secondary education and income, although in-service higher education relates significantly to each of the five aspects of employee performance (Table 2). The reasons could be, firstly, that in-service adult education is not fully recognised because it is seen as inferior to pre-employment education, and secondly, employers may lack the commitment to employees’ in-service adult higher and specialised secondary education (Yang, 1996). On the other hand, however, other types of inservice training do have a moderate relationship with both the total income (0.063) and the basic income (0.070) (Table 2). Taking the five categories of in-service education/training as a whole, the means of incomes of those with an in-service education/training are significantly higher than that of those without (528.5 compared with 506.6 for total income; t ⫽ 2.75, p ⬍ 0.01, and 384.1 compared with 359.4 for basic income; t ⫽ 3.39, p ⬍ 0.01).

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY

LIMITATIONS The results of this study can only be tentative for several reasons, some of them relating to the limitations in the present study and others relating to social and educational factors, all of which merit suggestions for further work. First, the study of employees’ performance has relied on employers’ subjective assessments of employees’ performance. Hence, the result of the assessment might not be employees’ actual performance. Further study should use direct measurements to assess performance. Second, as surveys of this kind have to be carried out on samples, questions about generalisation of the findings inevitably arise. It is very important to distinguish between a statistical generalisation from a sample to a population and theoretical generalisation (Yin, 1984). Given the diverse nature and very large size of a country such as China, care must be exercised in any attempt to generalise to other locations. The two cases in this study are located in the coastal areas of China and the economic level of the two cases is above the national average; consequently the results of the study may not reflect the problems associated with inland and less developed areas. Moreover, the data of the two cases in this study have been aggregated and not analysed with regard to inter-regional differences. Future studies should focus on other areas and on inter-regional differences. Third, the analysis in this paper has focused on the performance and economic related returns for different categories of pre-employment and in-service education and training. However, education reform and development have broad social and political aims as well. The vocationalisation of senior secondary education in China has been used to reduce the social pressure for higher education (Yang, 1996). Furthermore, as the average work experience in employment of employees in this study is about seven years, the finding in this study may not reflect the performance of graduates of the current education and training system. Given the government’s commitment in the last few years to improve the quality of vocational education, the performance of graduates of vocational education may have improved. Further study of new graduates from the education and training system is needed in order to produce fresh evidence. Moreover, in the multiple regression

301

analysis the values of R2 are low. R2 is a measure of the percentage of variance in the dependent variable which can be explained by (or is associated with) the cluster of independent variables used in the regression equation. For example, the largest value of R2 for the dependent variables of employers’ perception of employees’ performance is 0.141 (in the aspect of enthusiasm); that is to say, 14.1% of the variance in that aspect of employers’ perception of employees’ performance is associated with their education and training, gender and experience. In the case of employees’ income, the figure is 16.6%. These figures are low because there are clearly other independent variables which contribute to the relationship. Identification of these other variables was not the purpose of this study but this could form the basis of further research work; for example, political, economic, social or psychological factors could be correlates of employees’ performance and income. Fourth, it must be considered that the Chinese labour market still to a large extent is fragmented, and that the sample is mainly taken from the formal section of the labour market. It is likely that the correlation between educational level and income indicators is different if other labour segments were included in the analysis. Although employment under the socialist market economy is freer, many structures from planned economy have been carried over into the present labour regulations. The measures of basic and total income only reflect the direct money income and do not include the high level of non-monetary subsidies and benefits related to employment. Due to these systemic issues, the findings must be regarded with a caveat. Fifth, given that technical and vocational schools in China admit students with poor learning and examination results while general academic schools admit students with good results, the intellectual resources of students of technical and vocational schools could be weaker than their counterparts of general academic schools (Yang, 1996). This study could not be comparing only the differences in school systems but also the nature of their intakes. The result of the current study might demonstrate that technical and vocational education is not able to overcome the different nature of its intakes relative to general academic education. Furthermore, since many vocational schools were transformed from general secondary schools with poor con-

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ditions, in terms of both physical conditions and the quality of teachers, and many of them still lack financial resources, equipment and specialist teachers, they could provide similar curricula to general academic schools, although the government requires that vocational schools should devote at least half of their teaching time to vocational knowledge and skill practices. The difference between what students learned in vocational school and in general academic school is not as significant as the type of school indicates. Future studies need to take the nature of the intakes and actual curricula of different type of schools into consideration. Sixth, the socialist market economy in China is a new endeavour, and as time goes by its long-term impacts on the social and economic development of China need investigation, including a longitudinal study to monitor change. CONCLUSION AND IMPLICATIONS In spite of the limitations analysed above, the results of this study suggest that • the employees with a higher level of preemployment education were perceived to have performed better at the workplace by their bosses than those with a lower level of pre-employment education; • employees with a vocational track of education at the senior secondary level of education were not perceived to have performed any better than employees with an academic track of education at the same level of education; • employees with an in-service education/training were perceived to have performed better than employees without an in-service education/training. In addition, this study found that • employees with a higher level of education did not earn more than those with a lower level of education; • employees with a vocational track of education at the senior secondary level of education did not earn more than employees with an academic track of education at the same level of education; • employees with an in-service education/training earned more than those without an inservice education/training.

The present analysis provides some issues which can help frame general policy-making on education and training in China. It is obvious that a general rise in the educational level of the labour force will have a strong impact on productivity. The above analysis has shown that higher education gives a better work performance, but that vocational education is not better than general academic education. The overall budgetary implications of this choice are very important given the limited resources China can afford to spend on educational development. An important factor is that vocational education overall is more expensive than general academic education by a factor 1.6 (Qian et al., 1995). Bearing this in mind, it may be possible to increase efficiency of educational investment by shifting the resources from vocational education to general academic education. This, however, is not a plausible solution to the dilemma. First, the intellectual resource base for education (that is, the relative achievements of the students) is not homogeneous, and vocational schools in China generally enrol intellectually poorer students than general academic education. This has to do with the fact that general education has a higher social status and reputation than vocational schools, and that the benefits associated with vocational schools, from the students and their parents’ point of view, are very restricted. As most parents now have only a single child, the popularity of vocational schools which do not offer the prospect of higher education declines. Second, the main issue of the socialist market economy is the fast development in technology, administrative structures and the economic structure of enterprises. This calls for a dual emphasis, both on general abilities and on core vocational skills which can develop with technological and societal change. It is particularly difficult to forecast these changes. If the traditional distinction between general academic education and vocational education is upheld, neither general academic education nor vocational education will provide for future demands. The conclusion that vocational education does not provide higher efficiency than general academic education, therefore, may be too narrow in the context of future education policy; general academic education which does not provide jobrelevant skills places the burden of in-service training on the employers. In addition, it also is

GENERAL OR VOCATIONAL? THE TOUGH CHOICE IN THE CHINESE EDUCATION POLICY

unlikely to provide forward-looking adaptability, but rather — in the context of a rapidly developing economy — prove too retrograde and traditionalist. The solution may lie in various forms of integration between general academic education and vocational education. In-service training, in the analysis, has a strong position in terms of employees’ performance. This does not, of course, indicate that inservice training is a panacea for the skills deficit in the Chinese workforce. It needs to be integrated with the pre-employment education and training of workers, and to be transferable within the increasingly mobile labour market. The formal sectors of the Chinese labour market in the socialist market economy, especially the state-owned enterprises, may provide excellent environments for such training, but the structure of the labour market will prevent these enterprises from reaping the fruit of their training provision. The workers will easily move into less formal, but higher-earning sectors of the labour market. The policy regarding in-service training, therefore, must be devised in such a way that it can overcome these imbalances in the labour market. Provisions must be available for all sectors of the labour market, and the incentives must link increased work performance with remuneration and career development. The findings that there is no clear causal relationship between the basic and total incomes of workers and their work performance constitutes a serious problem. The way in which the formal Chinese labour market is organised means that • the monetary incomes are only a fraction of the total incomes in terms of benefits and job security (even though this is gradually changing in the 1990s); • change of work is normally not an option for the workers, except if they are willing to leave the formal sector of the labour market and thus incur high social costs and relative job insecurity; • levels of income, be it in terms of basic and total monetary income or in terms of incomes including subsidies and benefits in kind, are therefore not regulated by ‘normal’ market mechanisms but by administrative measures and by the relative wealth of the employing work unit. The result of this is that education is not obvi-

303

ously rewarded. In the 1990s, Chinese education (at all levels higher than the nine years compulsory education) has increasingly become based on student fees. When students consider the direction of their studies, it will be difficult for them to have a clear cost–benefit incentive in their minds. Acknowledgements — The author would like to thank Dr G. Tabbron of Bolton Institute, Dr Y. Benett of the University of Huddersfield, Dr D. Taylor of the University of Manchester and Dr Q. Tang of UNESCO in Paris for their helpful comments. The author is indebted to the Department of Vocational and Technical Education of the State Education Commission of the People’s Republic of China for assisting with the arrangements for the fieldwork in China.

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