Ten years of democracy: translating policy into practice in mathematics and science education Kgabo Masehela Human Sciences Research Council Email: kmasehela@hsrc.ac.za Background This paper provides a 10-year (1994 – 2004) review of the state of mathematics and physical science education (SME) in South Africa with respect to participation and performance, and its relationship with policy implementation. The framework for this paper is guided by two broad questions: • Which key policy initiatives were conceptualised, developed and disseminated in the last ten years? • How has the system performed in respect to the participation and performance rate in mathematics and science education since 1994? Through interviews, we also provide an overview of the voices of stakeholders (subject advisors, teachers and senior officials). The interviews were conducted in order to illuminate the challenges in translating policy to practice. Any adjudication of government policies in respect to physical science, mathematics and technology education (SMTE) should be read within the assumption that within ten years (1994 –2004) there would have been less dramatic changes in the performance of what was one of the most divided education systems in the world. In this paper, the ten-year period is divided into two periods, 1994 –1999, and 1999 – 2004. The period between 1994 – 1999 is described by policy analysts as the policy formulation era. This is a period that was marked by the establishment of a unified, democratic and accountable system of government. The second period (1999 – 2004), described as the policy implementation era, is marked by dissemination of government policies. The era of policy design and development 1994 – 1999 South Africa has produced formal policies and legislation as part of education reform. These include: White Papers (DoE 1995), National Education Policy Act (DoE, 1996a), South African Schools Act and National Norms and Standards for School Funding (DoE, 1996b), Employment of Educator Act (RSA, 1998), Language Policy and Admission Policy (1996), as well as the Human Resource Development Strategy (DoL, 2001b). The Reconstruction and Development Programme (RDP) document laid a firm foundation for the design of all these policies. Its goals with respect to SME were: • An appropriate mathematics, science and technology education that is essential to stem the waste of talent. • Rewriting the schooling curriculum and raising the quality of learning and teaching through in-service education of teachers (INSET) and upgrading the professional competence of teachers. Following the RDP document, the White Paper on Education and Training (DoE, 1995) outlined ‘the most direct way’ of redressing the imbalances of the past around issues of SME. These papers indicated that special initiatives were needed to prepare learners for subjects in short supply and noted the following, • Only one in five black learners choose physical science and mathematics in standard 8 (grade 10), and the trend of performance in the senior certificate examinations has been low overall, with a particularly dismal matriculation exemption rate among learners taking these subjects at higher grade. • Fewer black learners with science and mathematics qualify for normal entry to higher education. South African policies aim to bring equity and redress in education. However, under South African contextual conditions and reality, to what extent could these policies be implemented? Are there some doubts whether these policies are achieving their intended objectives? Have these policies increased the participation and performance rate in mathematics and science? To what extend have they increased? This will be revisited later in the paper. Pythagoras 61, June, 2005, pp. 21-30 21 Ten years of democracy: translating policy into practice in mathematics and science education The era of policy implementation 1999 – 2004 Curriculum innovations and development The introduction of Curriculum 2005 in February 1997 marked a major school reform initiative in education. This new curriculum, based on a constructivist epistemology, initiates learners into what Stenhouse (1976) calls ‘worthwhile activities’ ranging from hands-on activities, group discussions, project work, etc. While the conceptual design of C2005 seemed plausible, the implementation proved to be a challenging exercise. The first problem in implementation was the failure to estimate the extent to which resources would be a constraining factor. The second shortcoming was the impracticality of providing in-service training to all teachers in the General Education and Training (GET) phase of schooling. A review of the curriculum acknowledged deficiencies in design and content. This resulted in a streamlined curriculum in terms of learning areas that also reduced use of complicated terminology. In a sense, the Revised National Curriculum Statements (RNCS) overcame the fundamental flaws of C2005. Human Resource Development Strategy Initiatives in mathematics and science were initially set out by the RDP document and White Paper on Education and Training (1995). South Africa’s president reiterated the centrality of these subjects in two State of the Nation addresses (2000 and 2001). Following this, the ministers of labour and education jointly launched the Human Resource Development (HRD) Strategy for South Africa in June 2001. A practical initiative coming from the strategy was the creation of the 102 Dinaledi Schools (‘Creating Tomorrow’s Stars’), established as an attempt to increase the participation rate. In line with the redress agenda, resources were concentrated on a set of schools – rather than all the schools – that would become quality sites of science and mathematics teaching (Kahn, 2003). The HRD Strategy, which also has its origins in the RDP, is an attempt to operationalise President Mbeki’s ideas made in his 2000 and 2001 State of the Nation addresses. In terms of the HRD Strategy Indicator Five: Mathematics and Science Results (DoL, 2001b: 25) ‘the problem in mathematics and science has not to do with numbers who passed on higher grade or who obtained university exemptions’. The strategy notes that ‘generally, mathematical and science literacy are extremely poor in the entire schooling system’. In order to arrest the chronic situation the former minister of education, Prof. Kader Asmal, tasked his deputy minister, Mr. Mosibudi Mangena, with a clear utilitarian prescription – amongst others – to increase the rate of participation of black learners, especially females. Following the Department of Education’s strategy to improve mathematics and science, the deputy minister released the names of 102 dedicated mathematics and science high schools as part of a national strategy to improve mathematics and science in schools (Bot and Masehela, 2003). Provincial departments were requested to draw their own strategic plans for mathematics, science and technology education for the next six years (2003 – 2008). The provincial plans had to include their vision, mission and commitment to restructuring GET and Further Education and Training (FET) in terms of professional development, provision of resources, new curriculum implementation, delivery, admini- strative and community support. All these had to be designed in line with the national HRD Strategy for mathematics and science. The Department of Education earmarked more than R400-million for the promotion of science and mathematics (Mega boost for maths and science, 2001). This financial injection allowed the project to supply schools with resources such as books, satellite television and laboratory equipment, and mathematics and science educators were offered special training sessions. An audit of the 102 Dinaledi Project Schools indicates that from a total of 307 mathematics and science teachers, 188 (64.6%) have obtained a grade 12 qualification and 177 (56.7%) a diploma as a professional qualification. A few teachers have obtained honours (17, or 5.6%) and the Eastern Cape has the highest number of educators (5) with masters degrees. It is in the light of this background that we can see the growing demand being made on teachers and learners for significant change in the teaching and learning of mathematics, science and technology. Participation and performance rate It is now critical to take stock of how these policies were translated into practice in terms of participation, performance and quality higher grade (HG) passes by examining trends since 1996. Participation in this paper refers to learners enrolling for matric while performance refers to the quality of passes, particularly in HG. South Africa has in the last years witnessed a drop in the number of grade 12 candidates. Table 1 22 Kgabo Masehela provides a picture of the enrolment trends since 1996. Table 1 shows a decrease in enrolment data between 1996 and 2003. Although the number of candidates passing has been on the increase, it is worrying that the number of candidates enrolling for grade 12 has decreased significantly by approximately 80 000. According to Van der Berg (2004), to judge matriculation results in context we should not only look at those who write the matriculation examination, but also those who should have been in matric. If we consider the 18- year-old or matric aged cohort in 2003, 985.000 learners should have written the matric examination. Instead 440.267 sat for the examination and 322,492 passed. 58% of African candidates do not reach matric, and only 5.2% of African candidates achieved results that should have given them university entry. The decrease noted in the table is what Kozol (1996) calls the ‘human wastage’ and this is a challenge to South Africa. For example, 330.717 passed the examination from a total of 467 985 in 2004 and 137.268 learners failed. Given this data, where do failing learners go? What is government doing to absorb these learners into formal employment? Will these learners be allowed to repeat if most of them are not over age? Will they enrol for Adult Basic Education and Training (ABET) programmes, or will they undertake supplementary examinations? These issues require further investigation. Table 2 shows that the total enrolment of mathematics and science learners increased between 1996 and 2004 from 218.225 to 276 094 in mathematics and from 122.278 to 161.214 in physical science. The total number of candidates who passed mathematics also increased from 108.910 in 1996 to 156.795 in 2004. Similarly, physical science increased from 74.110 to 119.543. The increases in the matric pass rate between 2000 and 2004 has been linked to falling candidate numbers (cf. Table 1) and weaker candidates or ‘at risk’ grade 11 learners being filtered to grade 12 therefore leaving a pool of generally stronger candidates, a greater proportion of learners with the potential to pass (De Souza, 2003). Of particular significance (cf. Table 2) is the fact that between 1997 and 2004, candidates writing mathematics HG dropped from 68.451 to 39.939. Similarly, physical science had a drop from 76.086 to 55.969. However, the overall pass rate increased as from 2000. In mathematics the pass rate rose from 45% in 2000 to 59% in 2003 while it rose from 69% to 80% in physical science. With respect to standard grade (SG), on the other hand, the number of candidates who registered for mathematics and science increased especially in 2000 (cf. Table 3). Table 1. Enrolment trends and Pass and Failure Rate 1996 – 2003. Year Candidates (N) % increase / decrease Candidates passing (%) Candidates passing with exemption (%) 1996 518 032 278 958 (53.8) 79 768 1997 556 246 7.4 261 400 (47.0) 69 007 1998 552 384 -0.4 273 118 (49.3) 69 891 1999 511 474 -7.7 249 831 (48.8) 63 715 2000 489 941 -4.2 283 294 (57.8) 68 626 2001 449 371 -8.3 277 206 (61.7) 67 707 2002 443 821 -1.2 305 774 (68.9) 75 048 2003 440 267 -0.8 322 492 (73.3) 82 010 2004 467 985 6.3 330 717 (70.7) 85 117 Sources: DoE 2004; Edusource DataNews 2001/2002 23 Ten years of democracy: translating policy into practice in mathematics and science education Table 3 indicates a decrease in the number of learners writing mathematics and science SG. As the number of learners writing mathematics increased from 149 510 in 1996 to 236 155 in 2004, the number of passes increased from 89.896 to 109.446. Similarly, learners writing physical science increased from 52.252 to 105.245 and the passes increased from 30.306 (58%) to 78.025 (74%). Due to structural changes brought about by formal economies changing, with less reliance on industries based on mining and agriculture to reliance on jobs in the financial sector, there is a need for candidates with quality higher grade passes in mathematics and science (National Skills Development Strategy, 2001). The National Strategy for Science, Mathematics and Technology Education and the subsequent establishment of the 102 Focus Schools attempts to increase the number of HG passes and eventually respond to the question of supply and demand in the economic sector. If the declining trend of learners writing mathematics and science is not arrested, how will this affect the South African economy? According to the National Skills Development Strategy (DoL, 2001a) high skilled jobs increased by 20% between 1970 and 1998. The United Nations Development Programme (UNDP, 2001: 28) indicates that science and technology activities require a skilled workforce and human resources development is therefore important. The South African White Paper on Science and Technology (DACST, 1996), on the other hand, indicates that any national system of innovation requires an Table 2. Mathematics and Science participation and performance 1996 – 2004. Mathe- matics HG Year Total Enrolment Total Passed (SG/HG) % Pass Wrote HG Males Passed Females Passed Total Passed HG candidates 1996 218 225 108 910 49.9 65 223 12 817 9 599 22 416 1997 252 617 116 836 46.3 68 451 12829 9969 22 798 1998 298 195 124 005 41.6 63 899 11579 9581 21 160 1999 281 304 122 225 43.4 50 105 10660 9194 19 854 2000 284 017 128 142 45.1 38 520 10207 9120 19 327 2001 263 945 123 149 46.7 34 870 10084 9420 19 504 2002 260 989 146 446 56.1 35 465 10804 9724 20 528 2003 258 323 151 905 58.8 35 956 12564 10848 23 412 2004 276 094 156 795 56.8 39 939 13325 10818 24 143 Physical Science HG Year Total Enrolment Total Passed (SG/HG) % Pass Wrote HG Males Passed Females Passed Total Passed HG candidates 1996 122 278 74 110 60.6 70 269 15 140 10 322 25 462 1997 141 278 91 538 64.8 76 086 15925 11 046 26 971 1998 168 632 108 896 64.6 79 019 16443 11 651 28 094 1999 160 949 102 896 63.9 66 486 13818 10 373 24 191 2000 163 185 112 164 68.7 55 699 13135 10 209 23 344 2001 153 847 105 552 68.6 48 996 13609 10 671 24 280 2002 153 855 117 529 76.4 50 992 13979 10 909 24 888 2003 151 791 121 947 80.3 52 080 14935 11 132 26 067 2004 161 214 119 543 74.2 55 969 15447 11 528 26 975 Source: own calculations based on Department of Education 2004, SCE database 24 Kgabo Masehela enabling framework for socio-economic development in the country. The figures as illustrated in the tables are a challenge to the attainment of the white paper’s enabling framework. This is because, despite substantial increments in school resources and a more equitable allocation of resources in mathematics and science, the overall output of candidates has not kept pace with the input. If the above policy pronouncements are not fulfilled, there is a need for structural reconfigurations. Implementation of these reconfigurations and changes will also require urgent attention. Performance by province Table 4 provides provincial data in terms of participation and performance trends in mathematics and science between 1996 and 2004. With the exception of North West, all provinces experienced an increase in the number of candidates passing the matric examination. The table shows that the number of learners passing with endorsement has on average largely remained the same in many provinces. Gauteng and Limpopo experienced a significant increase in the number of endorsements between 1996 and 2004 and, on the contrary, Eastern Cape and North West experienced a decrease. Gauteng, Kwazulu Natal, Limpopo, Mpumalanga and North West experienced a drop in the number of learners enrolling for mathematics HG. Similarly, with the exception of Free State, all provinces experienced an increase in learners enrolling for science HG. Given the data in Table 4, ‘what is the performance of African candidates in senior certificate examinations for mathematics and physical science?’ Table 5 presents provincial results using the Language Proxy Method (Kahn, 2003). Kahn (ibid.) provides data (Table 5) for a number of African learners who passed with mathematics HG. These results respond to questions raised in parliament in 2000 namely, is it true that only 3 000 African learners obtain a mathematics HG pass? Kahn (ibid.) provides an analysis of provincial results using what he terms Table 3. Mathematics and Science HG/SG Mathe- matics SG Failed Passed Pass % Pass over previous year 1996 149 510 89 896 59614 39.9% 1997 184 166 98 818 85348 46.3% 43.17% 1998 234 296 140 467 93829 40.1% 9.94% 1999 231 199 136 161 95038 41.1% 1.29% 2000 245 497 142 232 103265 42.1% 8.66% 2001 229 075 131 310 97765 42.7% -5.33% 2002 225 524 104 593 120931 53.6% 23.70% 2003 222 367 99 155 123212 55.4% 1.89% 2004 236 155 109 446 126709 53.7% 2.84% Physical Science HG SG Failed Passed Pass % Pass over previous year 1996 52 252 21 946 30306 58.0% 1997 65 192 18 610 46582 71.5% 53.71% 1998 89 613 27 188 62425 69.7% 34.01% 1999 94 463 32 095 62368 66.0% -0.09% 2000 107 486 31 605 75881 70.6% 21.67% 2001 104 851 34 753 70098 66.9% -7.62% 2002 102 863 24 244 78619 76.4% 12.16% 2003 99 711 17 768 81943 82.2% 4.23% 2004 105 245 27 220 78025 74.1% -4.78% Source: own calculations based on Department of Education 2004, SCE database 25 Ten years of democracy: translating policy into practice in mathematics and science education 26 the Language Proxy Method that he developed to identify African candidates taking mathematics and science. Such candidates were identified only by their having taken an African language among their Senior Certificate examination subjects. There might have been African candidates who did not study an African language, but it was argued that they could not number more than 5%. Following the proxy method, Table 5 provides the disaggregated data by province in 2002. It may be observed from the table that Limpopo had the highest number of learners taking mathematics and science compared with Gauteng and Western Cape, for example, because proportionally Limpopo has the highest African population of these provinces. The results presented here respond to the questions raised in parliament in 2000. Performance by Gender The Education White Paper 2 (1995) recommends that females take these subjects (mathematics and science), which are critical for the further development and growth of our nation. It proposes ‘to increase the number of girls in science streams’ through the equitable-school based funding formula. The period 1996 – 2002 has seen the female performance in mathematics improving substantially, with both the number of female candidates participating growing at a faster rate than male candidates and the gender gap in pass rates decreasing. The percentage of female candidates passing higher grade mathematics was higher in 2002 than that of male candidates. Table 4: Performance by Province. Dept Yr Candidates who wrote Candidates who passed Candidates who gained endorsement M Cand M HG M HG Pass S Cand S HG Cand S HG Pass 1996 66809 32639 7061 24567 3118 1031 15402 6249 1552 2000 74563 37118 5332 42747 1440 1085 25989 2251 993 Eastern Cape 2004 63426 33915 5564 39958 2392 1535 23941 2431 1487 1996 35554 18153 4208 15050 2761 1165 9400 3939 1811 2000 29477 15538 3697 16888 1685 1109 10305 3799 2149 Free State 2004 24731 19459 5480 12423 1768 1346 7937 2960 1681 1996 72959 42142 13810 38635 11355 5932 25298 13692 7010 2000 68202 46056 12896 44799 7332 5577 28964 8835 6180 Gauteng 2004 71382 54808 15780 44821 9062 6710 28660 10852 6889 1996 86608 53397 20040 40832 16677 6978 19613 13261 6186 2000 96423 55128 15655 64075 11325 4709 32775 13208 5869 KwaZulu/ Natal 2004 110635 81830 20950 74932 9230 5356 39051 13516 6221 1996 126081 47569 9351 40800 18505 1517 20069 15942 2202 2000 95191 48886 11100 46651 8389 1452 24719 13592 2041 Limpopo 2004 77774 54897 16273 39228 7647 2046 21733 13757 3337 1996 41731 19739 4332 15654 4534 1220 9947 5855 1194 2000 41115 21694 4762 21369 2446 894 13342 4866 1207 Mpuma- langa 2004 37091 22913 4640 19334 2186 1283 13159 3809 1436 1996 46349 32185 7611 18272 4466 1430 10727 6453 1982 2000 40098 23366 5057 22595 1880 1041 13220 4886 1200 North West 2004 37327 24221 4647 20822 1853 1314 12993 3255 1601 1996 7111 5194 1225 2606 484 279 1574 511 333 2000 7054 5019 892 2910 330 298 1705 354 256 N Cape 2004 6723 5609 1259 2767 459 382 1616 505 386 1996 34830 17940 12130 18317 3323 2864 10491 3958 3192 2000 37818 30489 9235 21983 3693 3162 12168 3910 3449 Western Cape 2004 38896 33065 10524 22023 5093 4268 12124 4884 3937 Source: Own calculations from Department of Education 1996, 2001, 2004 Reports Kgabo Masehela Table 6 shows that the number of female candidates that enrol for mathematics is higher than those of males. In fact the number of females is much higher than the number of males in SG mathematics. However, as is shown in Table 2, the male pass rate in both mathematics and physical science HG has become increasingly higher than that of females between 1996 and 2002. According to Van der Berg (2004) and Perry (2003), 13.7% of females, as opposed to 10% of their male counterparts, failed the 2003 matric examinations. The above trend suggests that there are more females participating in mathematics and science, and whether these females come from African schools or former Model C schools is a point that requires further research. It could be discerned from that the above data that if mathematics and science are about participation and performance, males will continue to have access to power, as they will enrol at tertiary institutions in fields such as engineering. And males will resultantly occupy positions and benefits that come with the subjects. Table 5: Performance by Province (following the proxy method). Math HG Math SG Phys Sci HG Phy Sci SG Proxy Entry Proxy Entry Proxy Entry Proxy Entry 2002 172 246 3865 5189 207 285 1975 2782 WC 28 57 424 688 22 45 263 397 NC 380 493 9758 10137 1607 1736 4836 6393 FS 599 833 33131 34674 704 972 19608 20471 EC 4560 5029 45724 48159 6838 7332 19147 19670 KZN 861 999 15537 16445 2487 2703 8199 8757 MP 5546 5779 27670 28266 10784 11101 7744 8003 LP 1568 2451 17876 22972 2339 3498 9385 12276 GP 731 832 16686 17054 2212 2358 8017 8244 NW Totals 14445 16719 170671 183584 27200 30030 79174 86993 Source: Kahn 2003 Table 6: Number of Mathematics Candidates and Passes, Average Annual Growth and Pass Rates by Gender, 1996 and 2002. Subject Gender 1996 2002 Average annual % Pass Pass growth rate rate 1996 2002 Male 103056 122902 3.0% Maths candidates Female 111677 138087 3.6% Male 48701 63299 4.5% 47.30% 51.50% Maths passes Female 42625 58518 5.4% 38.20% 42.40% Male 34577 18867 -9.6% Maths HG candidates Female 30646 16598 -9.7% Male 12817 10804 -2.8% 37.10% 57.30% Maths HG passes Female 9599 9724 0.2% 31.30% 58.60% Male 5497 2831 -10.5% Maths HG conversion SG Female 3799 2156 -9.0% Male 68479 104035 7.2% Maths SG candidates Female 81031 121489 7.0% Male 30387 49664 8.5% 44.40% 47.70% Maths SG passes Female 29227 46638 8.1% 36.10% 38.40% Source: EduSource 2002 27 Ten years of democracy: translating policy into practice in mathematics and science education Translating policy to practice: the voices of teachers, subject advisors and senior officials The last section of this paper illuminates the impediments towards increasing the participation and performance rate in mathematics and science. Subject advisors and district officials from Gauteng were interviewed following Meulenberg- Buskens’ Free Attitude Interview Technique (1997). The technique involves asking one question to the interviewees in a focus group and then allowing respondents to unpack, debate, discuss, and (dis)agree on why South Africa is unable to increase the participation rate of black, and in particular female students. As the interviewer, I merely asked clarifying questions to keep the conversation on track and at various phases of the interviews provided a reflective summary to focus their minds on the main question. Telephonic interviews were also conducted with mathematics and science educators from Free State and Limpopo. The input from this group of educators was solicited because of their contact with the reality of the situation on the ground. Five key themes emerged from an analysis of the interview data. These were: • Resourcing – The environment at school level is not conducive to increasing the participation rate, and township schools especially lack resources. To this effect a typical response was ‘there is a lack of media centres, laboratories, and current, relevant books in schools’. • Support of teachers at the classroom level – Learning Area Specialists have to undertake regular classroom visits to support teachers in planning their lessons and teaching process. However, as data from the interview indicates, there is little support from Learning Area Specialists at District Level because ‘districts are understaffed, under qualified, or have people with no qualifications at all. • Qualifications – Learning Area Specialists and teachers (including primary school teachers) have to improve their qualifications in order to increase the performance rate in mathematics and science. District officials are increasingly faced with new developments, including the implementation of the Revised National Curriculum Statement (RNCS), and are therefore not able to deal with the professional demands at hand. • Discouraging learners to continue with the subject – As prescribed by the Mathematical Literacy, Mathematics and Mathematical Sciences (MLMMS) requirements, teachers confirm that ‘learners cannot be encouraged to enrol for mathematics in grade 10, especially if they have failed (obtained less than 33.3%) grade 9’. Secondly, teachers discourage learners from taking mathematics and science from grade 11 onwards if they have obtained less than 40% at HG in grade 10. ‘If learners obtain between 33.3% and 40%, they can still study at SG’. According to district officials ‘teachers are worried that a school’s performance will drop’ and eventually affect the ‘school image’. There is, therefore, a tight selection of learners, and this eventually contributes to learners’ repetition of the same grade, to eventually dropping out (cf. Table 1). • Intervention Programmes – There are a number of mathematics and science intervention programmes that have been implemented, and as district officials indicate ‘an impact evaluation study is yet to take place’. For example, ‘Saturday classes require learners to perform at a certain level, and lessons are often taught at a higher level’. There is, therefore, a mismatch between intervention programmes and the cognitive level of learners attending the programmes. Furthermore, ‘there is no remedial programme in place to support learners in need of individual attention, especially learners in overcrowded classrooms’.1 Conclusion This paper has outlined key policy and legislative initiatives designed and implemented during the two ministerial terms of 1994 – 1999 and 1999 – 2004. This paper has attempted to examine the extent to which these policies have been translated into practice with respect to increasing the participation and performance rate in mathematics and science. Although the policy encourages learners to enrol for mathematics and science HG, 1 The recommended number of learners per class at secondary school is 35 (SASA, 1996), but many township classes have an average of 46. 28 Kgabo Masehela data indicates that the majority of learners enrol for these subjects at SG level. For example, 30.086 learners passed mathematics HG and 126.709 passed at SG in 2004. This reflects a number of issues, amongst them are: • A lack of confidence in the quality of mathematics and science education by both education administrators and policy makers. The system is not ready in terms of teacher qualifications and resources to enrol more learners in HG and learners are not confident of passing at this grade level. • Misinterpretation of policies at school level by pushing more learners into SG. • Policies have as yet not filtered down to classroom levels hence learners increasingly take these subjects at SG. Although the government laid the groundwork for improvements in the education system in terms of policies, the number of learners passing mathematics and science higher grade has not increased. It could be deduced that results in the first ten years of democracy have not been gratifying. However, it may be too soon to make a judgment compared to what was produced before 1994. However, there is a need to set some short- term goals by considering targets on year-to-year increments. The analysis appears to show that while a lot has been done in terms of policy designs and implementation, a lot more remains unachieved. However, an understanding is slowly but surely emerging that policies have been taken seriously and will yield better results in the near future. For now we may feel dissatisfied with the numbers but the context and where we come from should be important. Following Jansen and Sayed’s (2001) argument, it is plausible to study these policies in the context of the government having laid the groundwork for long-term and sustainable improvements in education. Finally, the Dinaledi schools project presents just one case of government initiative in terms of operationalising government policies with respect to the HRD Strategy. We recommend that these schools should not be pressurised to produce immediate results. In as much as it takes time for a plant to grow, it takes time for policies to produce immediate results. References BOT, M. & MASEHELA, K., 2003, “Provincialisation of Education, a Review. 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IJRTA%20Chapter%202%202004.pdf Pointless Quest A needle in a haystack may be difficult to find. Your chance of ever finding one is small Especially with haystacks of the ordinary kind, which don’t have any needles in at all. Piet Hein