Technical secondary students in Kenya: Origins, achievement and destinations

TRENDS AND CASES

Technical secondary stud " K ents In enya:

origins, achievement and destinations"

Jon Lauglo

Introductory observations

Vocational courses in secondary schools are attracting international interest, particularly in developing countries. Many governments and international agencies have in recent decades given high. priority to such courses. There is growingresearch interest in vocational and pre- vocational education as is shown in much recent writing (Dougherty, in press; Hukin, 1987; Lauglo and Lillis, 1988; Psacharopoulos and Lox!eY, 1985; Twining, I987). Two professional journals have also had recent special issues on vocational education: International Review of Education, Vol. 34, No. 2, 1988; and Inter- national Journal of Educational Development, Vol; 8, No. 3, 1988. It is widely recognized that school-based vocational courses are costly, that it is difficult to recruit and keep competent

Jon Laug lo (Norway). Director of Research, Pro- gramme of Research on Education, Norwegian Re- search Council for Science and the Humanities. Pre- viously at the Department of International and Com- parative Education, University of London Institute of Education. Working within a comparative perspective, has published on pre-vocational education and vocational training, the teaching professioi~, distribution of authority ~ in education systems and university policy.

teachers, and that they have demanding man- agement and logistics requirements (equipment, materials, maintenance). None the less, government policy often favours technical vocational courses in spite of acute shortages of funds. This is because vocational education is deemed to serve important policy goals.

In some countries, the aim is to meet man- power shortages, but in most cases the dominant goal is to reduce unemployment among secondary-school leavers. The premise is that technical courses will at least give a competitive advantage in depressed labour markets, or even reduce the scale of school-leaver unemployment. In either case, the hope is that such courses will in the long run play a part in improving productivity, Thus, the articulation between these courses and the labour market is important.

Lending policy on vocational training is currently under review at the World Bank. Mcan- while, the Bank's policy study on education in sub-Saharan Africa notes that it is unwise tO generalize across countries about the ap- propriateness of any given mode of vocational

* This article is the result of a joint project with Anders N ~ m a n at the University of Gothenburg, Sweden. It is based on a paper presented at the I988 conference in Norway of the Nordic A*sociation for the Study of Education in Developing Countries.

Prospects, Vol. XIX, No. 3, x989

4io Yon Lauglo

training. None the less, the policy Study (World Bank, 1988, pp. 63-4) raises

warnings that policymakers may prudently bear in mind when the introduction or expansion of [vocational training] programmes is being considered... there is scant evidence to suggest that training for a particular occupation will in and of itself predispose an individual to seek employment in that occupation... [and] the training provided in schools is generally less useful (that is, the market demand for it is less strong) than training provided on the job or ha specialized training centres.

Empirical research on the articulation of school- based training with the labour maket is still sparse. Important questions are: Do technical graduates gain access to occupations or further training in their speciality? In particular, is 'preparation for self-employment' mere policy rhetoric or is it reality? These questions are part of an important general issue in analysis of the relationship between schooling and the occupational structure: What gives advantage in access to jobs, school credentials or socio" economic background and associated personal connections? Or more generally, how important is the effect of schooling on occupational life chances?

It is sometimes argued that regardless of what the relationships may be in industrialized countries, school attainment and achievement in developing countries matter greatly for access to modem-sector jobs and associated earnings, though there is dispute about whether this association is due to the greater productivity of those with more schooling or to credentialism unwarranted by any productivity considerations (Oxenham, 1984). Thus, Heyneman 098o) con- dudes that passing exams and doing well at school makes a great difference for the future earnings of secondary-school students in Malawi. Schiefelbein and Farrell (1984), in their long- term Chilean tracer study, found that although there is a general effect of 'years of schooling', the quality of the school attended is an even more powerful predictor of occupational attainment in the first job. In a tracer study of students who attended Ugandan secondary schools in

the 195os and 6os, Currie (1977) concludes that t he re was a Cfar greater importance of academic performance than socio-economic status in predicting occupational placement among school graduates in one of the least industrialized countries in the world'.

I t is also recognized, however, that the role played by schooling in allocating occupational life chances is context bound. Currie (1977) speculates that the future influence of schooling may be more limited than what was found in Uganda in the I95OS and I96OS. I f schooling expands faster than modem sector jobs, and if private employment becomes more important within that sector, then such 'non-merit' considerations as family contacts may come to exert greater influence on the selection process. Oxenham (1984, p. 71) similarly observes, based on impressions from a number of countries, that ' the greater the competition for employment, the greater the importance of social connections in addition to social background and education'.

There is also the notion of labour-market segments with different selection criteria for jobs. Caillods and Briones (1981, pp. 7o--I), ina study from Colombia, point to the loose connection between technical training and labour'market destination. Although education is the prime criterion for recruitment of managerial staff, educational level and credentials seem to play a less important role in recruiting technicians and priority is not always given to graduates from technical schools. Further, education is clearly not the main criterion for skilled workers.

Closely related to the role of schooling in selection for occupations is the influence of family background on educational achievement and attainment. It is precisely when school achievement and attainment are strong deter- minants of occupational life chances, that inequalities among social groups in access to school and in achievement within school become politically important. At one extreme, there is the meritocratic model of these relationships: social origin is loosely related to educational achievement and attainment, bu t schooling strongly determines occupational life chances. At the other extreme, there is the Ceducation

Technical secondary students in Kenya: origins, achievement and destinations 4I I

as social reproduction' model: social origin strongly determines access to school and school performance, and schooling matters greatly for occupational destination and associated rewards. However, if schooling is but loosely related to occupational life chances, then social selection to school and in school performance cannot play an important part, either in social reproduction or in social mobility. The nature of these links between schooling and the occupational structure are thus of central concern to arguments about schooling's relationship with economic development and equity.

Some countries have selection policies which are intended to favour students from those groups or districts that lag behind in educational provisions and attendance rates, thus enabling such students to gain access to select secondary schools in spite of poor primary-school performance. Are these policies implemented and do disadvantaged students ca tchup with others during the secondary course?This issue is important for vocational secondary schools as well, especially when they are attractive to students with good primary- school credentials.

However, it is a widely shared impression that school-based vocational courses are the poor relations of purely academic courses: that technical students are academically inferior both at intake and in terms of performance during school, and that they tend to come from more humble origins than do students in purely academic courses. For example, a report from a recent Unesco (1984) symposium laments the stigma attached to vocational technical education. Jennings (I987) refers to the status problems afflicting technical-school courses in the Commonwealth Caribbean; and De Mourn Cas- tro (1988) argues that the status problems are especially great in training provisions which are integrated within mainstream secondary schools where'even students from manual worldng-dass backgrounds who enter secondary schools may become infected with the anti-manual virus'; and that such integrated provisions fail to develop the needed socialization to the values and tradition of workmanship and craft.

But there is a tendency to generalize inter- nationally on the basis of scattered and incomplete impressions. For example, Urevbu (I 988) claims that the ~African experience' is lack of demand for vocational courses, and that 'school- based vocational education is not likely to be successful because of the inherent contradiction between student preferences and the type of schooling offered'. But school-based vocational or pre-vocational courses are sometimes in high demand and offered in highly select secondary schools. Kaluba (1986) notes the select character of technical secondary schools in Zambia, and shows that practical industrial arts subjects are also popular with students when offered in academic secondary schools not designated as technical. Recent research on similar pre- vocational 'industrial education' subjects in Kenyan academic secondary schools (Lauglo and N~irman, 1987) shows high status for these subjects. Wright (I988) reports similar findings in Sierra Leone. In general, the attractiveness of vocational or pre-vocational subjects is likeiy to depend on a variety of factors--one of which is whether in a difficult labour market they are perceived by students and parents as a way of hedging bets on further academic education, by offering the hope of employable skills to fall back upon, while still holding open the possi- bility of further academic schooling. This is only possible if vocational or pre-vocational courses are taught as relatively minor elements in a secondary school course which is predomi- nantly academic. However, a risk associated with such provision is that it will give inadequate depth of ~employable skills'.

The general conclusion from international social research has been that school achievement, and especially school attainment (or level of schooling), are strongly influenced by a student's family background. But there is some research suggesting that this may not apply to some developing countries at the stage of Ccommencing the process of industrial strati- fication'--at least as far as achievement within a given stage of education is concerned (Hey- neman and Currie, 1979, on Uganda; and Heyneman, I98O, on Malawi). There are find-

412 yon Lauglo

ings showing negligible zero-order effects of socio-economic family background on student achievement in secondary schools. More gen, erally, Heyneman and Loxley (I989), in a re- analysis of data from the International Evalu- ation o f Educational Achievement in Science, conclude that there are stronger effects of the quality of individual schools in the 'poorer' countries, and that such effects o~/ershadow those of family background there. However, to assess the effect of family background on achievement within secondary schools, there is a need to take account also of scholastic ability at point of entry to such schools, since it is likely that socially advantaged children stand a better chance of gaining access to secondary schools in spite of poor primary- school credentials.

The foregoing discussion has shown the significance of these research questions for vocational secondary schools. How attractive are they to their clientele? Who gains admission? Are there powerful effects of 'school quality' and family background on achievement? How do these schools relate to the labour market for schooMeavers and to further training Oppor- tunities? Do they lead to related training and job opportunities? What is the role of school achievement as compared with family background in the quest for jobs, training, and further education? These issues will now be addressed by findings from survey research on Kenyan technical secondary schools. Some preliminary findings have been reported byN/irmam (r988g) and a report by Lauglo (I985a) has examined characteristics of the technical secondary schools and the role of Swedish assistance in their development.

Kenyan technical secondary schools

At the time of our initial fieldwork in Kenya (I985), technical secondary schools were really more academic than like 'technical' secondary schools in most countries. Their students could qualify for further study in the upper-secondary

academic A-level courses at the same time as they received a grounding in a technical:tiade. Academic subjects occupied two-thirds of the time-table in the four-year course leading to O-level examinations; the remainder was shared among technical drawing, technical theory and technical practice. The trades were: mechanical technology, automotive, electricity, welding and fabrication, agricultural mechanics, surveying, plumbing, masonry, carpentry and joinery. The schools Were intended as preparation for craft/ technical apprenticeships administered by the Directorate of Industrial Training, and for trainee programmes in parastatals and private industry. The fifteen government-maintained technical secondary schools constituted a very small part of secondary-school enr01ments in Kenya.

The schools studied were al!boarding schools. One might therefore expect them to exert more pervasive influence on students, compared with that athome, than day-schools.

The schools have changed since the time of our fieldwork. Since I986 they have been trans- formed into Technical Training Colleges within the new Kenyan 8-4-4 system of education and will have a dual post-primary and post-secondary function, in either Case with a curriculum that gives overwhelming emphasis to technical subjects and practical application.

The survey data ! I

The surveys were conducted in three stages: Stage z. A survey of some !,ooo students in

their final year (Form 4) at eight schools in the spring of I985 (Machakos', Kabete, Na- kuru, Rift Valley, Kitale, Sigalagala, Kisumu and Mawego). Data on social and geo- graphical origins, primary-school results, and occupational and educational aspirations/ expectations (conducted by Lauglo and N/it'man).

Stage z. These students' results on the Kenya Certificate of Education (KCE) examination (antumn r985) were obtained and added to Stage t records (conducted by Lauglo).

Technical secondary students in Kenya:origins, achievement and destinations 413

Stage 3. About 500 of the students (from five schools) were traced about one year after their KCE exam, partly by postal question- naire, partly by face-to-face interviews. Data were obtained on their present activities and location, reported technical skills usage, and some further attitude questions (conducted by N~rman).

Who goes to technical secondary school?

101

It should be noted that vocational secondary schools in Kenya are almost exclusively a male preserve: in our sample of 986 students there were only 18 females. These were all at Nakuru technical secondary school and were enrolled in automotive, electrical, and mechanical.

The recruitment pattern in Kenya for the class of 1985 contradicts the allegation that technical secondary schools suffer from low status. Already in I973 there were some 3o,ooo applicants for the 67o places then available. Our Stage z sample of 986 final-year students was asked: 'Was your first choice of secondary education a technical secondary school or an academic secondary school?' Fully 96 per cent said that their first choice had been a technical school.

In response to an open-ended question about reasons for their preference, the reasons given were a blend of declared liking for practical/ technical subjects and the hope that it would point towards related work or be of advantage in the search for a job.

Figure I shows the distribution of the class of z985 by their entry points from the Certificate of Primary Education (CPE). The points are based on marks in English, mathematics, and general knowledge. Three top marks (As) give the maximum possible 36 points. Information was obtained for 975 out of the 986 cases.

Clearly, these students were not academic rejects. With few exceptions they did extremely well in primary school: the mean is 32.8 points (an average of 33 corresponds to three As). As shown by an earlier report (Lauglo, 1985a),

18 I1 19 0 - 2012 21 12 22 113 23 12 24 | 3 25 ==7 26 ram9 27 ~ 23 28 ~ 23 29 ~ 45

31 ~ 5 7 32 114 33 II 127 34 L53 35 36 136

CPE points followed by histogram and frequencies

FIG. Z. Certificate of Primary Education points of Form 4 students i n eight technical secondary schools as of z985.

192

this intake (in-I982 ) has a better average than the t98o intake to the highly select academic secondary schools which were included in a separate study of Industrial Education Subjects (Lauglo, z985b). In no sense are the technical secondary schools as a group 'inferior' to good government-maintained academic schools.

But there are some students who get in with low marks. The lowest score of any student in this sample is z8, which corresponds to three Cs. The histogram in Figure i shows that those with CPE points 3t and below seemingly form a distinctly'lower' group. What kind of family background do those pupils have who get in with such qower' marks? To examine this and the wider question of social recruitment, Table z shows CEP mark categories by father's education.

Table z shows that 26 per cent of the fathers had no school at all, z6 per cent had incomplete primary, 27 per cent completed primary; 4 per cent had some secondary, 22 per cent completed secondary (at least O-levels) and 4per cent had

414 yonz Lauglo

TABLE I. Students' CPE points by father's education

Primary CPE points or below

Father,s education

Secondary University Total

% N 3: or less 23.1 143 32 or more 76.9 477

TOTAL Io0.o 62O

Horizontal percentages 69.4

% N 28.5 67 7x.5 x68

xoo.o 235

26.3

Missing observations = 93- P(chi-square = xo.48) = 0.005

% N % N

44.7 I7 25.4 227 55.3 21 74.6 666

ioo.o 38 ioo.o 893

4.3 ioo.o 893

university or equivalent. For comparison, according to the I979 census, about 5 ~ per cent of the male population above 2o years of age had no schooling at all,;and only 7 per cent had obtained anything beyond primary school. Thus, these students are disproportionately recruited from homes with relatively well-educated fathers. None the less, the recruitment of technical secondary students is strikingly more democratic than academic secondary schools with similar national catchment status, which recruit students with equally good primary- school pointsuschools investigated in the evaluation of practical subjects in academic secondary schools (N/irman et al., 1984, p. 9). It is likely that technical secondary schools are especially attractive to students from poorer backgrounds who do well in primary school since they hold out the prospect of a trade to fall back on, but it should be noted that these schools are in no way less select than top academic secondary schools in terms of primary-school achievement.

There is a relationship between the family- background classification and students' CPE points. With increased parental educational background, the more likely it is that the student got in with less than 31 points in the CPE. It is especially the small group of students with fathers with a university background who stand out in this respect.

It is not official policy in Kenya m offer easier access to children from highly educated families, but such children are disproportionately well represented among those with less than 31 CPE

intake points in the technical schools. In fact, the official policy is to compensate for disadvan, rage by offering easier admission to secondary schools with a national catchment (such as the technical ones) to pupils from educationally disadvantaged districts.

There are great differences between the districts in school-enrolment rates. It is known that admissions boards have for some years been using various quotas intended to boost the chances of applicants from districts with low rates. Is this policy of compensatory dis- crimination in fact implemented? Does it over- shadow the advantage that pupils from better educated homes seem to have? Is it easier to gain access with a low CPE if a student comes from a disadvantaged district?

To examine this, we produced three alterna- tive indicators of the educational development of Kenya's forty-one districts and cross- tabulated each against the CPE point categories of students. First, we used categories based on the percentage of the population aged 2o and above who according to the 1979 census had had no formal education. This indicator may be considered a quite valid criterion for assessing the general condition of districts as shaped by historical inequalities in access to schooling. Yet, no relationship was found with the CPE points of students admitted to these select technical secondary schools. Second, we categorized districts according to gross secondary-school enrolment ratios as of I979. Again, no relationship was found with the

Technical secondary students in Kenya: origins, achievement and destinations 415

CP E Points of the ted~nical secondary students. Finally, we classified the districts according to the 1981 gross enrolment rate for primary school as reported by the Central Bureau of Statistics (Kenya/UNICEF, 1984, p. 98).

Of the three indicators, the gross primary- school enrolment rate may be the crudest measure of educational disadvantage since a high repetition rate will boost the gross enrolment rate in a district. Even the national average is lO7 per cent of the relevant primary- school age-group. Nevertheless, using this indicator we did find a pattern of easier admission for students from disadvantaged districts. But the frequencies show that of the 25~ students who had been admitted with 31 points or less, only fifty-six came from districts with lower primary-school enrolment than the national average. Clearly, other factors than educational disadvantage of the district play an important part when students with relatively low CPE points are admitted. The front-door practice of compensatory quotas appears to be overshadowed by the back-door practice of admission through connections.

The eight schools studied are all national catchment schools. The original intent behind these schools was that each school should have a truly national catchment. In our sample however, more than half of the students come from Central and Nyanza Provinces. Further- more, there is a strong tendency for students at each school to come from the province in which the school is located, and with neigh- bouring provinces also over-represented. Thus, in allocating students to different national catchment schools, there is a tendency to take account of travelling distance. The schools seem to be more regional than truly national in character.

In view of the growing awareness inter- nationally of the importance that school quality has for student achievement and post-school opportunity, it is of interest to see whether these schools, which are all highly select national catchment schools and thus at the top of the Kenyan hierarchy of secondary schools, form their own hierarchy according to the quality of intake,

Although only I5.8 per cent of the Kabete

school students scored 3I CPE points or less at entry to secondary school, half of the Kitale students came from this low-score category. As a new school, Kitale had an unusual intake in that it received, at the time of opening, students transferring from other schools directly into the higher forms. Thus, the sending schools seemed to have used this occasion to shed some of their weaker students. The poor examination results at Kitale may also reflect this to some extent (see Table 3 below).

We also examined differences between the trade specialities as to CPE intake. A barely significant (P(chi-square)=o.o2) association was found which in view of the large number of cases indicates negligible differences. Elec- trical technology stood out as a trade that recruits with 'high entry' points, while there was clearly less select intake to agricultural mechanics which is only taught at Kitale. The schools differ in the trades taught. But these small differences between trades cannot explain the pecking order of schools.

The highly skewed nature of the CPE distribution makes it unsuitable for analysis of variance. But for what it is worth, two-way analysis of variance also showed school-effects independent of trade effects: Kabete and Nakuru stand out from the others as being more selective; while Kitale, Sigalagala and Mawego stand out as being less selective.

School achievement and ks correlations

Examination results were obtained for these students from the 1985 Kenyan Certificate of Education (KCE) (lower-secondary) examination. How well did they do in the different subjects? Table 2 shows the mean grade on a scale of I to 9 (where 1 is the top mark and 9 is a failure), for the different subjects that students entered for in the KCE examination. It also shows the percentage who passed in each subject and the product-moment correlations between marks in different subjects. It should be borne in mind that the technology

416 yon Lauglo

TABLg 2. Analysis of KCE exami~atio n results. Intercorrdations between marks in different subjects, and mean mark and percentage fail by subiectt

Imercorreladons

Tech- Techni- Tech- nology Number

Geogra- Physical cal nology appli- Mean % of �9 Subject English 'phy science Maths drawing theory cation mark fail cases

English 0.39 0.34 0.35 0.26 0.35 o.I6 6.40 i i . 6 975 Geography o.39 0.66 o.6I 0.47 0.56 0.22 4.92 o 7-5 975 Physical science o.34 0.66 0.76 o.60 0.63 0.24 6.05 16.6 975

Mathematics 0.35 o.61 0.76 0.59 0.54 0.27 4.95 11.5 974 Technical drawing 0.26 0.47 0.60 o.59 0.57 o-4o 5.7I I5.8 974

Technology theory 0.35 0.56 0.63 0.54 0.57 0.35 6.61 I4.4 974 Technology application o.x6 0.22 0.24 o,27 o.40 0.35 4.89 1.6 974

Mean correlation o.3I 0.49 0.54 0.52 0.48 0.50 0.27 - - - - - -

L For the intercorrelations numbers range between 975 or 974 to 875 (for correlations with physical science Which does not include students at Nakuru). With the high number of observations, even the lowest intercorrelations are statistically significant at the o.oox levels using one-tailed tests.

theory and applications marks in this table refer to different trades for different students, and that students also took other subjects in thek KCE examination. Thus, they usually take eight subjects, but since some vary between and within schools, 0nly those that are shared are included in this analysis. At one school, Nakttru, students did not take physical science but took separate exams in physics or chemistry. Marks in those subjects are excluded from Table 2, but other marks from Nakuru are included.

First of all, Table 2 shows that examination data were obtained for nearly all cases (975 out of the total sample of 986). This indicates minimal drop-out during Form 4, since the Stage I data were collected early in the school

.year. Second, the subjects in which students tend

to do best are technology application (which in each trade is based on marks given on a series of phased practical tests), physical science, and mathematics. They do most poorly in technology theory and English.

Third, Table 2 shows patterns in the intercorrelations between marks in these subjects, of a kind similar to those reported earlier for Kabete Technical Secondary School with regard

to 1984 exam results (Lauglo, i985 a, p. 18) There is a core of subjects with high intercorrelations: physical science, mathematics, technical drawing, technology theory, and geography. English and technology application are more weakly related to any of these subjects, and are hardly related to each other at all. One would expect that technology application would be reasonably strongly related to technology theory. After all, these are but two aspects of the same trade and are intended to be so taught that mastery of one would reinforce the other. But the correlation between theory and practice (application) is quite low (0.35) . In fact, technical theory marks (as well as technical drawing marks) are distinctly more strongly correlated with the core of academic subjects than with application. This, together with the overall poor results in technical theory, suggests that this subject may not be well taught.

It is reasonable to expect that an individual student's examination performance is influenced by a number of factors: that there are effects of earlier school achievement (as indicated by CPE points), of parental background, and of the quality of teaching in the school. Do such effects exist and how strong are they? We know that there are differences between the


schools. A significant correlation was also found between CPE points and KCE results. Those with better primary-school resuits tend to do better on the KCE secondary school examination (P(r=o.39)<o.oooo5). But this association accounts only for I5 per cent of the variance in the KCE mark score (the sum of the marks in a student's six best subjects). Never- theless, when school effects are adjusted for, we also find an association. Thus, in spite of the relatively narrow range of CPE results in this select group of students, there is a tendency for those who did better in primary school also to do better in the KCE exam, after adjusting for differences in school quality.

However, neither by cross classification with the examination division nor by one-way analysis of variance of KCE mark points, did we find any significant zero-order relationship between the father's education and the student's KCE performance. This finding parallels the conclusion reached in studies reviewed earlier, about no zero-order association between socio- economic background and student achievement in secondary schools in some other developing countries. But this does not necessarily mean that socio-economie background has no effect on school achievement, because it is insufficient to examine zero-order associations where, as in our case, there is a clear tendency for socially advantaged students to gain admission in spite of relatively poor primary-school results (see Table I).

To examine the effects of these variables in greater del~h, we performed a multiple classification analysis with total mark score on the t985 KCE examination as the dependent variable, and the student's CPE points from primary school, the father's education, and the student's school as predictor variables.

The CPE results were entered first as a predictor of KCE results. Then the student's school and father's education were entered simultaneously to estimate the effect of these two latter variables after first adjusting for effects of CPE points. This model will therefore only examine effects of the father's education in so far as it exerts an influence during the

secondary-school course above and beyond the effect it may have had on primary:school results.

The dependent variable is symmetrical and reasonably close to a normal distribution. Interaction effects are not included, since tests for interaction showed no significant effects. Most of the IO2 missing cases are due to the 83 cases for which no information was obtained on the father's education. Table 3 shows the results.

The findings show significant effects of both the father's education and the student's school, after controlling for CPE points. Given that a low score on the dependent variable means a good result (a negative deviation thus indicating a positive effect on performance)~ we see that Nakuru~ Mawego and Machakos continue to stand out as good schools in making the most out of their CPE intake, and that Kitale con- tinues to show poor results. But the sign for the small effects of Sigalagala and Kabete are inverted when effects of the other factors are adjusted for. Thus there are .genuine school quality effects which are independent of the quality of intake; but the school that has been most intensively supported by foreign aid, Kitale, stands out as being of relatively poor quality. Facilities, equipment and technical assistance from abroad are no guarantee of good school quality.

The father's education shows an interesting pattern. The deviations in the multiple classification analysis show a clear pattern whereby students from more 'educated' homes do better in converting their CPE results into performance on the KCE examination.

Another way that represents this relationship more concretely is to classify students into three groups as to whether they did clearly better or worse in the KCE exam than what their CPE results would indicate. This variable--'relative achievement--KCE compared to CPE'mis constructed as follows: 'Bloomers': students who obtained 31 points or

worse on their CPE (see Fig. t) but who nevertheless were among the best 33 per cent in our sample on the KCE scale (scores of 25 or less).

418 yon Lauglo

TAImE 3. Multiple classification analysis of KCE examination performance, with father's education, and student's school as predictors, adjusting for effects of CPE points

Analysis of variance

Degrees Sum of of Mean

Source of variation squares freedom square F-ratio Significance of F-ratio

Co-variate CPE points I3 252.88 I x 3 252.88 I8o.15

Main effects 6 355.30 9 7o6.I4 9.60 School 5 846.67 7 835.24 I1"35 Father's education 661.56 2 330.78 4.5 ~

Explained variation x9 6o8.x8 xo x 960.82 26.65

Residual 64 22L75 873 73-56

TOTAL 83 829.93 883 94.94

Missing observations ~ 1o2 cases.

<0.0oo 5 <0.0005 <0.0005 <O.OZI <o.ooo 5

Multiple classification analysis (after adjusting for primary-school points) Grand mean = 3x.ox; Standard deviation = 9.77; Standard error of mean = o.33

Unadjusted Variable +categories N deviations

Deviations adjusted for independents and co-varlate

Beta=weights adjusted for independents and co-variate

School

Machakos 130 -- 1.98 -- L65

Kabete 163 -- 0.48 0.36

Nakuru 87 - - 3-69 - - 2.74 Rift Valley zi6 0.29 0.58

Kitale 69 9.93 8.Ol Sigalagala 104 o. 18 - - o.7 i

Kisumu I 12 0.31 0.47 Mawego Io3 - - I . I4 - - 1.98

Father's education Primary or less 614 0.25 0.56 At least some secondary 232 - - 0.62 - - I.X3 University or equivalent 38 - - 0.22 - - 2.22

Multiple R squared Multiple R

0.234 0.484

0.27

0.09

'Wilters': students who obtained better than 3 I points in their CPE exam but who were in the poorest 24 per cent in terms of KCE results (scores 39 or worse).

All other students were classified as 'others'. Table 4 shows the relationship between

this variable and the father'S edtlcation and shows a statistically significant tendency for

[ rehtive achievemem and father's education

to be associated in such a way that those from better educated homes are more likely to catch up (bloom) and less likely to fall behind (wilt) than students from less educated homes. Thus, the education system helps in two ways to reproduce socio-economic advantage: by giving the sociallyadvantaged favour- able terms of admission (Table I ) ; and if they get in with low CPE points, enabling them more

Techn ica l s econdary s t uden t s in Kenya : or ig ins , a ch i evemen t a n d des t ina t ions 419

TABLE 4. Students ' relative achievement (KCE compared with CPE), by their father's level of education (percentages)

Father's education

At least University Relative Primary some or achievement or less secondary equivalent Total

'Bloomers' z.4 4.3 (]t3) 1 3.4 Others 83.7 84.I (Sz) 83.7 'Wilters ' ]t3,8 x z.6 (5) ]tz.9

TOTAL ]too ]too (roo) ]too

N 6]t4 23z 38 884

P(chi-square = ]t5.33) =0.oo4. Missing observations = ]toz eases.

I. Percentages in parentheses are based on a small number of cases.

often than others to catch up in their performance.

What about those who come from disadvantaged districts? No relationship at all was found between 'relative achievement' and any of the three district classifications. The probability that the chi-squares obtained could be due to chance alone ranged between o.5 and o.8 for the three tabulations examined. Thus, there is no tendency for those students who are admitted with relatively poor primary,school credentials from disadvantaged districts (and presumably poor-quality primary schools) to stand out by catching up during their secondary school course.

i i

Destinations after lower secondary school

Students at five schools (Kabete, Kisumu, Machakos, Sigalagala and Nakuru) were traced approximately one year after the KCE examination by N~irman and a team of his students from the University of Gothenburg. Preliminary findings of this part of the study have been published elsewhere (NLrman, I988a). Some further analysis will now be presented. Of a total target of 675 students, questionnaires

were received by 480 (a response rate of 7I per cent). There were no statistically significant differences between the target schools in the response rate. Compared with the sample analysed earlier in this article, the tracer study respondents do not differ significantly from others in terms of their fathers" education, but they did somewhat better on the KCE examination than students at schools not included in the tracing sample. At Kabete and Machakos those successfully traced also had somewhat better KCE results than those not reached. What were the ex-students doing one year after their junior secondary (KCE) examination? Table 5 shows the distribution of activity.

We note that 43 per cent are unemployed in the sense of not yet having succeeded in finding education, training or work; and that 39 per cent continue in school. The latter continue on to A-level courses in academic subjects since technical subjects are not offered in schools beyond the O-level exam. Since only one technical secondary school offers A-level courses, only thirteen of the students continue in the same school. Most go on to purely academic secondary schools of good repute. For

T~LE 5. Activity status of the students who were traced one year after their KCE examination

Activity % N

At school 39.4 x89 Training

Polytechnic 4.4 2x Institute of technology x.5 7 Water-board training 0.8 4 Training in industries o.8 4 Other technical/vocational training o.8 4 Other non-technical/vocational training x.7 8 (Sub-total, training) (zo.o) (48)

Working In trade of technical speciality z.5 7 I n other technical/practical work o.8 4 Agricniture 0.4 z Primary teacher, practical subject 2.3 zz Primary teacher L9 9 O ~ e r jobs z.z 6 (Sub-total0 working) (S.I) (39)

Looking for work/eduearJon/tralnlng 4z.5 204

TOTAL ZOO.O 480

420 Yon Lauglo

these students, their technical secondary-school background has been a stepping-stone to further academic education. Possibly, some will later gain entry to technical studies after their upper secondary course. But with purely academic schooling intervening, it is quite likely that relatively few of those who stay in school will find much direct use of the technical aspects of their lower: secondary-school background.

We further note that Io per cent have obtained some kind of training--nearly all of them in some technical/voeatioual field and about half in specialized training imti- tutions-'usually training requiring sponsorship by a firm. Bearing in mind that technical secondary schools were intended to prepare for apprenticeship training organized by the Di- rectorate of Industrial Training, it is striking that not a single ex-student indicated that he had obtained such an apprenticeship.

Only 8.1 per cent (thirty-nine ex-students) had found any iob at all. And of those who had found work, only seven Were employed in a job directly rdating to the technical trade they had been trained for at school. On the other hand, most of those employed were in a job which related to technical/practical skills (twenty fou r o u t of the thirty-nine) in a broader sense. But even so, it is at most only for these twenty-four plus those who gained access to further training--a total of I5 per cent--that the expensively provided technical aspect of their school background directly led to ~application of skills acquired, during ~ the fttst year after their KCE exam. As to self- e~ployment, we can with certainty only identify a single ex-student who within one year after leaving school was earning a living as self- employed.

In the severely depressed labour market for schO01-1eavers in Kenya, most ex-students face a protracted period of job search. One year's tracing is too short a period to examine adequately the eventual labour-market destinations ~0f ex-students in terms of their 'first job!. A~ ~hown by Niirman (z988b), in ~the case of the industrial education tracer study of ex-students from academic secondary Schools,

after three years as compared with one year's tracing, the percentage of students who still are in school/training declines while the percentage who have found work goes up though regrettably without much reduction in the percentage who are still unemployed (looking for work, training or education). However, N~man (t988b) concludes that after three years, there is a clearer tendency for students with exposure to a pre-vocational industrial education subject to nave found training or work that is of a technical/practical kind, though it may not be specifically related to the industrial education subject they studied at school. One might expect a stronger such longer-run tendency for the present sample because they have greater depth of training in a technical subject as compared with industrial education subjects.

The findings in Table 5 can be compared with those from the one-year tracer study of industrial education students (fifteen schools plus a control group of five purely academic

schools) (N~rman, I985). In that study it was found that in a total sample of x,oSo students, 45 per cent remained in school, 6 per cent were in some kind of training programme, 6 per cent had found a job, and 43 per cent were still looking for work/education. The overall pattern is quite similar to that in Table 5. The differences are small, but the present sample Shows somewhat lower percentage still in school (39 per cent), and slightly higher proportions working (Sper cent) or in training (io per Cent) with the same percentage still 'looking'.

What influences the destination of students? How important is school achievement as compared with social background? Table 6 shows both a cross-classification of their activity/ status by examination division, as well as the mean KCE mark scor e by activity category:

Not surprisingly, i t helps to do well in the examination if one wants to go on to the academic upper-secondary~course. The F-ratio for the analysis of variance is highly significant statistically. The percentage pattern in the

i left part Of Table 6 shows also that :'activity' clearly ~lepends on examination results, though there are too many cells in the table with an


TAm~ 6. Ex-students' activity one year after the KCE examination by their examination results

Percentages

Activity I I I I II IV Fail Total

Mean KCE mark scores lq

At school 75 42 I3 (11)1 i 39.3 Training 6 9 I6 (3) ~ 9.9 Working 3 8 13 (8) (33) 8.2 Looking 15 41 58 (79) (66) 42.6

TOTAL ZOO 1oo 1oo (100) (I0O) IO0.O

N 119 18o 136 38 3 476

Missing observations = 4 cases.

i. Percentages in parentheses ar e based on a small number of cases.

23.2 z87 3 x .4 r 47

33.4 39 33.9 203

29.4 476

P(F =67.4) < 0.00005

expected frequency of less than 5 for a chi- [ square test to be appropriate. At the same time, [ many do not stay in school even though their [ KCE results would have have secured a place ] for them, no doubt because they cannot afford [ the fees,

To address the question of whether good results help in the labour and training market, however, as distinct from being helpful for those wishing to go O n to A-level academic courses, we need to look separately at those who left secondary school. This is done in Table 7, where to make it possible to test the' statistical significance Of the cross'tabulation, we have combined some of the examination[ categories. [ I

Table 7 shows that there is abonta i5 per [ cent probability that the differences between [

the KCE means, or the pattern obtained in cross-tabulation, could have occurred by chance. The number of cases is sufficiently large for us to conclude that examination results are not an advantage to school-leavers in their quest for training or employment opportunities. This conclusion is in line with what also was found in the earlier industrial education study (Laugl0, i985b, p. ii5) , though it is entirely contrary to much writing about the importance of credentials in selection to work, whether as a screening device to enable employers to identify the more able or Socially 'acceptable' applicants, or because of the productive value

o f skills and attitudes supposedly acquired in School.

Finally, we shall examine whether a student% socio-economic fami ly background, here in-

TABLE 7. Those who do not stay on in school: Ex-students' activity one year after the KCE examination by their exariiination results

Percentages

Activity I and I I III IV and faiI Total

�84 KCE mark SCOreS N

T~ining 18 19 (3) x 16.3 Working 13 14 ( I I ) 13.5 Looking 69 67 (87) 7o.2

.TOTAL I00 1OO (100) xO0

N 134: x18 37 289

P (chi-square = 6.71) = o.15.

z. Percentages in parentheses are based on a small number of cases.

31.4 47 33.4 39 33.9 203

33-4 289

P(F= 1.98) =o.14

422 yon Lauglo

dicated by 'father's education' as a rough indication, is of any help in the quest for opportunity after the KCE examination. Since there is no significant zero-order association between KCE performance and father's education, we need not control for KCE perform- auce when assessing the relationship between father's education and the ex-student's activity. Table 8 shows the relationship for the entire traced sample. There is a clear pattern: it helps to have a better educated father if one wants to continue to upper secondary school or if one seeks access to training. Again, we need to re- member that students in the different 'father's education' categories were not significantly different as to KCE examination rcsults by any zcro-ordcr association. There is therefore no need to adjust for exam results in this analysis.

If wc excluded from the tabulation all those who stayed on in school, and thus looked only at those who can bc said to have cntcrcd the labour and training market for school-lcavcrs, wc would again find that it helps to have a better educated father. Three-quarters of those whose fathers had 'at most primary education' remained unemployed (looking), as compared with two-thirds of those whose fathers had 'at least some secondary education', and only one (out of six) of those whose fathers had university education or equivalent. Ability to pay school fees i s one factor behind these patterns (particularly for access to upper secondary school),

but it is also overwhelmingly likely that the superior connections with institutions and places of employment, which better educated families have, play an important part.

Concluding comments

The findings show that there is no inter- nationally valid 'iron law' by which school- based vocational training is inferior to purely academic secondary education in terms of quality of intake or exam results. Kenyan technical secondary schools as of I985 were highly select institutions and a first choice rather than a reluctantly accepted second choice for entering students. There are nevertheless differences between the schools as to quality of intake, as indicated by the primary-school points of entering students. There was but a hint of a pecking order of trade specialities within the schools: electrical technology stands out above other trades in attracting students with the best primary-school results.

As to quality of intake, the schools compare favourably with academic secondary schools of good reputation when the present findings are compared with earlier studies. They do tend to recruit students from relatively well-educated homes, but interestingly less so than equally reputable academic schools. It is likely that the technical schools have a special appeal to less

TABLE 8. Ex-students, activlty/status one year after the KCE (lower secondary) examination by their fathers' education

Father's education

Activity Primary or less Secondary University Total

% N % N % N

At school 34.2 IO3 51.3 6I (60) 1 9 Training 7.0 2I ii .8 !4 (33) 5 Working 9-3 z8 5.9 7 - - o Looking 49.5 I49 3 I . I 37 (7) I

TOTAL Io0 3OI Ioo I I 9 (Io0) 15

% N

39.8 x73 9.z 4o 8.0 35

43.0 I87

zoo 435

Missing observations =45- P(chl-square =33.78) <: 0.ooo05 but x7% of cells (z out of iz) have an expected frequency

of tess than 5.

1. Percentages in parentheses are based on very few cases,


educated parents whose children did very well in primary school, in that the technical schools seem to hold up the hope of an employable skill to fall back upon, after lower secondary school, if for lack of fees or achievement their child c~nnot continue in school. This would echo findings from industrialized countries too, that students from lower socio-economic origins are more attracted to educational variants with connotations of direct occupational utility.

In spite of a policy of offering easier admission to applicants from disadvantaged districts, in so far as such policy has any effect at all, it is overshadowed by even easier admission for students from well-educated and presumably well-connected homes.

Although the students are a select group to begin with, recruited from a top and restricted range of primary-school results, there is still a correlation between the primary-school scores and examination results.

Some schools are more effective than others in making the most out of their students' primary-school points, in terms of exam results at the end of the course. Thus in keeping with other recent writing stressing the importance of school quality for the performance of students in developing countries, and in spite of the restricted range of quaIity in these schools which are aU highly reputable in the Kenyan context, we find effects of school quality.

Like some other studies we find no zero- order effects of home background on achievement within these schools, but this is because it is easier for students from well-educated homes to gain admission in spite of mediocre primary-school credentials. When primary- school scores are taken into account, students from better educated homes do better than others. Performance in different subjects is correlated, but the association between theory and practical application marks in the same trade is strikingly weak, suggesting that these two aspects of technology subjects are not taught i n such a way that they successfully reinforce each other.

A key set of questions concerns what hap-

pens to students after school. Did these schools really serve as preparation for in-depth training in the student's trade? Within one year after the completion of the technical secondary course, this had failed to happen for the vast majority of ex-students. About four out of ten went on to upper secondary courses in purely academic subjects. Another four out of ten were still looking for education, training, or work with as yet no success. Those who had gained access to training did tend to continue in some vocational/technical speciality. Most of those who had found work, similarly were in a technical/practical job, but few in the specific trade they had taken at school. Thus, in the short run at least, it is only for a rather small minority (about 15 per cent) that the technical skills aspects of their training leads to related subsequent work or training, and it is then usually not specifically related to their trade of specialization. We found only a single case of self-employment. Longer-term tracing is needed, especially for those who are still unemployed (or looking) to show the full extent of these links.

There has been some recent research in Kenya on vocational-training programmes for school-leavers. Kukler (I987) reports preliminary findings from a tracer study of the trades- training courses (of varying duration) in the Kenya National Youth Service, saying that 53 per cent of the men and 43 per cent of the women did find employment in the trades for which they were trained. Yambo (I986), in a tracer study of leavers of Harambee Institutes of Technology (post-secondary) and Youth Polytechnics (post-primary) with samples of uncertain representativeness and time lapsed since training, claims that some 9o per cent were in gainful employment though the skill utilization in the work role varied. These findings are also not comparable with our survey because the time lapsed since training is not specified in these other studies. But the rate of labour-force absorption may well be higher in the skills-training courses for school- leavers. It is interesting that Yambo also found a strong tendency for youth polytechnic leavers

42.4 Jon Lauglo

to end up in employment rather than self- employment. Extremely low rates of self- employment are also reported by Niirman et al. (1988) in a tracer study in Botswana of leavers from the Botswana brigades, in spite of the emphasis on self-employment in the ideas behind these brigades.

Kenyan policy is currently based on the assumption that training in greater depth results in better labour-market absorption. Since the time of our fieldwork, the technical secondary schools have changed into technical training colleges with greatly increased time for: the technical subjects in the time-table. One would expect that attractiveness to the clientele would suffer as students no longer will be able to combine technical subjects with a sufficient range of academic subjects to hold open the prospect of further academic study. But the hope is that the articulation with related training and work will be enhanced. It can be expected, however, that any form of training which is pre,employment and without placement in industry during the training period is likely to be poorly connected with subsequent work under the kinds0flab0ur- market conditions which Prevail in Kenya. It is of Vital importance, in Kenya and in other countries, that tracer studies be designed to monitor the effectiveness of existing training and the effects Of shifts in provisions. At the same time, there is also need for studies which Show the routes Of access to skilled jobs and the criteria used in hiring.

For technical' secondary students, access to upper I secondary academic courses depends both On the students' examination results and on their social .background as indicated b y father's education. However, for those who enter t h e highly competitive labour/training fnarket for school-leavers; examination results ~ppear to' offerno advantage---but family back- grouhddoes ~ matter.

Thns~ famil]t ~ background, even though if is but crtldely measured in this study, gives advantage at po!nt Of entry, further during I technical secondary scho01,1 and i n the �9 for fu~her schooling, t ~ n g and jobs after

school. These findings do not accord with a meritocratic relationship between schooling and the occupational status structure. But neither do they accord with the view that schooling reproduces sociat advantage. There is a certain reproduction of social advantage, but it does not seem to be strongly mediated by schooling. Access and school achievement (even in these boarding schools) are certainly influenced by family background; but school-leavers seem tO gain little advantage from exams in the quest for work or training.

On the whole, the findings are broadly comparable with earlier research on more mildly pre-vocational (industrial education) curricula in Kenya, indicating the extreme looseness of any link between the specific practical/technical subjects studied and the student's subsequent destination; and also high- lighting the striking unimportance of school credentials for access to any other future ac, tivity than schooling itself. The industrial edu- Cation sample has now been further analysed after three years' tracing, again showing that in the quest for jobs, school-leavers gain no advantage from the quality of their examination performance unless they had obtained the very top mark of Division I (N~man, I988b~.

In keeping with the argument that conditions have Changed from an earlier situation where examination performatice did matter in the quest for employment, the findings from our studies Contrast with those reported by Ki- nyanjui (1974)from a Kenyan national sample of lower-secondary school, leavers in 1968. At that time, the weakest students Were distinctly most likeiy to remain unemploye d one year after leaving School. Since that time, i the competition for jobs: between school-leavers has become very much sharper in Kenya and the unemployment rate �9 has greatly increased. Ki- nyanjui reports only'I4per cent unemployment after one year for the class of 1968, as compared with a ra te0f about 4o per cent in our~ recent

i studies, and there is~reason to "expect the rate to be even higher in teSs select secondary �9

than those included in the industrial education and technical~ seconda~i school investigations.


Thus the present study and the industrial education study both suggest that in extremely depressed labour markets for schooMeavers, the role of school credentials becomes atten- uated as the role of family connections comes more forcefully into play in selection for jobs and training. �9

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Documents

Technical secondary students in Kenya: Origins, achievement and destinations