SCHOOL’S GRADE 9 LEARNERS’ EXAMINATION RESULTS FOR THE PERIOD 2011-2013
Kelleher (2003: 752) stresses that the evaluation of the effectiveness of a PD programme should be based on the effect of the teachers’ professional development on learners’ learning. Hence, the participating teachers’ learners’ results were analysed to assess the possible effect of the teachers’ involvement in the PD programme on their learners’ performance.
Thus, the 2010-2013 grade 12 results of School B, School C and School D, as well as the 2011-2013 grade 9 results of School A’ were analysed. The aim of this analysis was to investigate whether the teachers’ involvement in the Mathematics PD programme had an effect on the results of the learners. It suffices to observe that many countries conduct PD programmes as a way of enhancing learner outcomes (King, 2014: 89), based on the view that “the only way to improve outcomes is to improve instruction” (McKinsey & Company, 2007: 26). In the South African context, grade 9 and grade 12 represent exit levels for the Senior Phase and the FET Phase, respectively, although learners only write national examinations in grade 12. These grades are therefore important in the lives of learners and have implications for the rating of schools. Thus the decision to use the grade 12 results of School B, School C and School D as well as the grade 9 results of School A which did not have grade 12 learners at the time.
164 Results per school
The tables and graphs below present the results of the four schools. The different schools were given pseudonyms, namely, School A, School B, School C, and School D, respectively. The tables and bar charts presenting the data were compiled or drawn – as a means to analyse the data – by comparing the different years. The details on each school are provided below.
School A’s Mathematics results 2011-2013
School A did not have grade12 learners for the 2010-2013 period. Consequently, its grade 9 end-of-year examination results were used, since grade 9 signals the end of the Senior Phase in South Africa. It must be noted that grade 9 learners also write the Annual National Assessments (ANA) which could also have been used. However, only the 2012 and 2013 results were available; hence, the researcher decided to only use the-end-of-year results of three consecutive years as these were available and ready for comparison. Nevertheless, it must be noted that only the 2011-2013 results of School A could be obtained, its 2010 results were not included, unlike the other schools. The grade 9 results of School A – for the 2011-2013 period – were as follows:
Table 5.6: School A’s Mathematics results 2011 - 2013
2011 2012 2013 0 – 29 7 = 53.8% 5 = 41.7% 0 30 – 39 1 = 7.7% 6 = 50.0% 4 = 50.0% 40 – 49 4 = 30.8% 1 = 8.3% 3 = 37.5% 50 – 59 1 = 7.7% 0 1 = 12.5% Total 13 12 8
165 Figure 5.1: Graph of School A’s Mathematics results 2011 - 2013
The number of grade 9 learners in School A between 2011 and 2013 was generally small, with 2013 registering the lowest number – eight – of learners writing the examination. Nonetheless, there seems to be an improvement in School A’s grade 9 results between 2011 and 2013. However, in 2012, no learner got a score above 50%, which was an indication that the learners in that year were quite weak. In none of the years did any learner obtain a score within and above the 60% range. Overall, it seems that 2013 was the best year for School A in terms of its grade 9 learners’ results. 0 10 20 30 40 50 60 0 - 29 30 – 39 40 – 49 50 – 59 60 – 69 70 – 79 80 – 89 2011 2012 2013
166 School B’s Mathematics results 2010-2013
Table 5.7: School B’s Mathematics results 2010 - 2013
Figure 5.2: Graph of School B’s Mathematics results 2010 - 2013
0 10 20 30 40 50 60 0 - 29 30 – 39 40 – 49 50 – 59 60 – 69 70 – 79 80 - 89 2010 2011 2012 2013 2010 2011 2012 2013 0 – 29 5 = 29.4% 1 = 16.7% 3 = 21.4% 4 = 40% 30 – 39 7 = 41.2% 2 = 33.3% 4 = 28.6% 3 = 30% 40 – 49 3 = 17.6% 3 = 50.0% 1 = 7.1% 1 = 10% 50 – 59 0 0 0 1 = 10% 60 – 69 1 = 5.9% 0 3 = 21.4% 1 = 10% 70 – 79 1 = 5.9% 0 1 = 7.1% 0 80 – 89 0 0 2 = 14.3% 0 Total 17 6 14 10
167 The number of learners who wrote grade 12 Mathematics examinations in School B was fairly small, with 2011 having the lowest count – six learners. There seems to be an improvement in the grade 12 examination results of School B between 2010 and 2012. Nonetheless, the 2011 results reveal that no learner obtained marks above 50%, which indicates poorer results compared to those registered in 2010, 2012, and 2013. In 2010, one learner obtained a mark within the range of 60% and another within the 70% range. In 2012, 57.1% of the learners scored below 50%, and two learners obtained distinctions (above 80%). This is a significant improvement, given that the total number of learners in 2012 was higher than that of 2011. In 2013, 80% of the learners obtained marks below 50%, and only 2 learners obtained results above 50% but not exceeding 70%. This was School B’s worse performing year, compared to 2012. Overall, it seems that 2012 was the best year for School B, although more or less half of its learners performed below the 50% mark and the other half above. The grade 12 results of School B fluctuated from year to year.
School C’s Mathematics results 2010-2013
2010 2011 2012 2013 0 – 29 15 = 62.5% 26 = 74.3% 4 = 26.7% 16 = 80% 30 – 39 5 = 20.8% 6 = 17.1% 6 = 40.0% 0 40 – 49 4 = 16.7% 1 = 2.9% 2 = 13.3% 2 = 10% 50 – 59 0 1 = 2.9% 1 = 6.7% 2 = 10% 60 – 69 0 1 = 2.9% 1 = 6.7% 0 70 – 79 0 0 0 0 80 – 89 0 0 1 = 6.7% 0 Total 24 35 15 20
168 Figure 5.3: Graph of School C’s Mathematics results 2010 - 2013
The number of learners who wrote the grade 12 Mathematics examination in School C was slightly higher than that of School B. In 2010, none of the learners obtained marks above 50%, and 62.5% of the learners’ marks were below 30%. In 2011, (the following year) 74.3% of the learners obtained marks below 30%. This is higher than the previous year. In contrast, only one learner got within the 60% and 70% range. In 2012, the number of learners with marks below 30% decreased to 26.7%, which is significant improvement, compared to the previous two years. However, 80% of School C’s learners obtained marks below 50%. This was also the only year, in the period considered, that one learner from this school obtained a distinction in Mathematics. This is an exploit, considering that no learner from School C has ever achieved a mark within the 70% band. However, in 2013, the grade 12 marks of School C dropped significantly, as 80% of its learners’ scores fell in the below 30% band. Only two learners (10%) obtained marks above 50%.
0 10 20 30 40 50 60 70 80 90 0 - 29 30 – 39 40 – 49 50 – 59 60 – 69 70 – 79 80 – 89 2010 2011 2012 2013
169 School D’s Mathematics results 2010-2013
2010 2011 2012 2013 0 – 29 10 = 45.5% 2 = 25.0% 5 = 38.4% 11 = 61.1% 30 – 39 7 = 31.8% 1 = 12.5% 5 = 38.4% 2 = 11.1% 40 – 49 4 = 18.1% 2 = 25% 2 = 15.4% 3 = 16.6 % 50 – 59 1 = 4.5% 1 = 12.5% 1 = 7.7% 1 = 5.6% 60 – 69 0 1 = 12.5% 0 1 = 5.6% 70 – 79 0 1 = 12.5% 0 0 80 – 89 0 0 0 0 Total 22 8 13 18
Table 5.9: School D’s Mathematics results 2010 - 2013
Figure 5.4: Graph of School D’s Mathematics results 2010 - 2013
0 10 20 30 40 50 60 70 0 - 29 30 – 39 40 – 49 50 – 59 60 – 69 70 – 79 80 – 89 2010 2011 2012 2013
170 The number of learners in School D who wrote Mathematics in grade 12 in the 2010- 2013 period fluctuated significantly, with 2010 having the most grade 12 learners. Interestingly, 2010 was the year with the second highest percentage of learners (45.5%) who scored below 30% in the examination. Only one learner obtained marks above 50%, leaving 95.5% of the other leaners with marks below 50%. In 2011, the spread of marks was relatively even. Indeed, this year registered the smallest number of learners with marks in the lowest band. Just more than half of the learners obtained marks below 50%, while only one learner’s marks were in the 50%, 60%, and 70% bands. Thus, 2011 can be regarded as the year with the best results, compared to the other three years. The analysis of the 2012 results reveals that a significant number of learners scored in the lowest band (38.4% of the learners). Only one learner obtained a mark above 50% in the examination. The Mathematics results of 61.1% of the 2013 cohort of School D learners were clustered in the lowest band. This is the year with the most learners in the lowest band. Indeed, 88.8% of the learners obtained marks below 50% in that year, leaving only two of the 18 learners (11.2%) above the 50% mark.
The results were analysed using the SPSS, in particular the Friedman Test. This test was used because it is appropriate when analysing data derived from the same sample cases which are measured at three or more points in time, or under three different conditions (Pallant, 2007: 228). As the data were collected over three years (for School A) and four years (for the other schools) and suited other descriptions, it was appropriate to use this test. If there were significant positive or negative changes to the learners’ performance, the tests’ significance levels (Sig. level) would have been less than 0.005 (Pallant, 2007: 230). The significance levels for the different schools were as follows:
171 Schools Significance levels
School A Between 2011 & 2012 0.574 Between 2011 & 2013 0.104 Between 2012 & 2013 0.001
School B 0.746 School C 0.484 School D 0.504
Table 5.10 Significance levels of learners’ results per schools
These results indicate the lack of significant differences in the learners’ results in the period 2010-2013 for School B, School C and School D, since their significance levels were above 0.005. It could also be noted that these significance levels were far above the threshold figure of 0.005. This implied that there was no improvement in the learners’ performance at the mentioned schools where the PD programme was rolled out. However, in the case of school A, the analysis of grade 9 results showed a significant change in the learners’ performance in the period 2012-2013, as the significance level was 0.001, which was less than 0.005. Although a significant change was evident, its scale was small scale in terms of the significance level’s magnitude. However, the small numbers of the schools’ cohorts could have had a negative influence on the test. Nonetheless, it can be concluded that the PD programme did not achieve its goal of improving the learners’ results. This answered research question 3.
It suffices to reiterate that learners’ performance is directly related to their teachers’ competence and performance. The researcher agreed with Adler and Davis (2006: 279) that, due to limited human resources, the competing goals of reforming could account for the fact that these learners’ results did not improve in the timespan under investigation. The majority of the participants had very heavy teaching loads, as described in section 5.6; this resulted in limited time for professional development initiatives to be reflected upon. A significant amount of PD interventions was spent on improving the participants’ content knowledge, especially in the workshops.
172 However, in the mentoring sessions, the mentor claimed that the focus was on the areas of the lesson that could be improved, the choice of examples used in the lesson, and whether learners’ books were monitored by the teacher. This signified that participants were exposed to sessions where they had more practice on content issues, but did not get much support on their pedagogy and innovative practices. So it is unlikely that these teachers’ classroom practice improved, despite the fact that it is an important aspect of the effort to improve learners’ performance. The fact that the participating teachers had a limited initial content knowledge, as reflected in the pre-test results, limited the development of their competence and performance in areas others than understanding the content of sections mentioned in 5.3. It also became evident that teachers only started working on improving their written lesson preparations in the last year of the programme (2012). This indicated that for the better part of the programme, the participants did not focus on lesson preparation. This is in line with Killen’s (2010: 84) claim that one “cannot expect individual lessons to be successful if they have not been planned thoroughly and integrated carefully into medium and long term plans”. Clearly, the classroom practices might not have been adequately planned for the majority of the programme’s duration; as a result, they might not have been effective. This could explain the lack of improvement in learners’ performance.
The next chapter focuses on the analysis of the primary data sources, namely, the interviews that the researcher conducted with the participants, the mentor and the programme executive manager, as well as the lesson observations done by the researcher.
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CHAPTER 6
ANALYSIS OF PRIMARY DOCUMENTS
6.1 INTRODUCTION
This chapter analyses and discusses the primary data pertaining to the Mathematics PD programme under investigation. The data sources included the interviews with the teachers, the programme executive manager and the first mentor, as well as the lesson observations done by the researcher. This data analysis sought to obtain answers to the first and second research questions.
6.2 INTERVIEWS WITH THE PARTICIPANTS, THE FIRST MENTOR, AND