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Chapter Five offered a description and analysis of the qualitative data. This included an analysis of the student biographical questionnaires and an analysis of selected students’ writing portfolios. The selection of the students for the case studies was born out of data from this chapter even though the presentation and analysis of this chapter is actually offered after the chapter incorporating the case studies. This chapter now moves away from an analysis of contextual factors and pays more attention to the numerical scores given to students’ written work. RtL makes use of very specific teaching strategies that are meant to assist students in the development of academic writing skills. Therefore, assignments set for this intervention naturally consist of multiple writing drafts. The assessment of these writing drafts was done according to a specially designed marking rubric. Although the use of marking rubrics is central to classroom assessment practices, if we used the South African curriculum specific marking rubrics, they would not have the necessary categories to assess specifically what RtL tried to address with regards to academic writing skills. For this reason, the rubric designed for RtL was done to ensure that what was being taught explicitly was being assessed. The analysis of students’ writing could have been done qualitatively but this would have been vastly different to other studies of RtL and would not have allowed for a comparison of findings which is an objective of this study.

This chapter reports the results and findings for the quantitative analysis of data in the form of various descriptive and test statistics for each piece of writing assessed for the narrative essay genre and the argumentative essay genre. These statistics were generated using PASW (SPSS) version 17.0. The reporting of the findings is not intended to be exhaustive in its scope, but aims largely to establish general patterns emerging from the data and possible implications for the RtL process. Furthermore, it is important to note that these findings are not necessarily intended to be externally valid (generalisable to all contexts), but are only valid for the grades, schools and contexts specific to this study. On the other hand, this is not to say that interesting theoretical propositions or empirical relationships cannot be gleaned

181 from studies of this nature: quite the opposite. Small-scale quantitative (and qualitative) studies are useful conduits through which to investigate various propositions or relationships in a deeper way, prior to possibly doing so in a larger-scale context, giving the emerging patterns a greater degree of external validity.

6.2 Descriptive Statistics

For the descriptive statistics which follow in Tables 6.1, 6.2 and 6.343, it is important to note that all written ‘literacy’ scores are out of a total possible score of 42 and hence, all descriptive statistics (except the measures of kurtosis and skewness) reported can be computed as percent scores quite easily by converting the raw scores. For example, a mean value for N0 of 19.24 (see Table 6.1) can be converted to a percent as follows: (19.24/42)*100 = 45.81%. Regarding the sample distributions N0, N1, N2, N3 and N4; A0, A1, A2, A3 and A4, graphical representations of the data distributions (histograms with normal distribution super-imposed) are given in Appendix Ten. In terms of ‘telling a story’, so to speak, regarding these various distributions, one can refer to the kurtosis and skewness statistics (see Tables 6.1, 6.2 & 6.3), in particular to confirm that, for the most part, all data

43 _{For the descriptive statistics reported in Tables 6.1, 6.2 & 6.3, the following notes have reference.}

N* and A* refer to the various assessed pieces of writing for the narrative essay genre and the argumentative essay genre, respectively. N0 and A0 refer to the baseline assessment for each genre, respectively. N1, N2 & N3 refer to the narrative pieces of assessment, and A1, A2 & A3 refer to the argumentative pieces of assessment throughout the scaffolded reading and writing (i.e. RtL) process. N4 and A4 refer to the final pieces of assessment of each essay genre.

Std Dev. refers to the standard deviation. For interest sake and to give an idea of distributional spread of the data points, according to the empirical rule, if the data are more-or-less normally distributed, then approximately 95% (99%) of the data points lie within 2 (3) standard deviations either side of the mean. However, for distributions which are not necessarily ‘bell-shaped’ or normally distributed, Chebyshev’s (Tchebycheff’s) Theorem offers a more conservative estimate in that approximately 75% (89%) of the data points lie within 2 (3) standard deviations either side of the mean.

IQR refers to the interquartile range, and is the difference between the values for the 75th and 25th percentiles. Kurtosis and Skewness refer to measures of shape. Kurtosis is a measure of peakedness of a data distribution, where a mesokurtic (normal) distribution has a value of 0. A negative value for kurtosis represents a platykurtic (too flat) distribution with too few data values in the tails. A positive value for kurtosis represents a leptokurtic (too peaked) distribution with too many data values in the tails. Skewness is a measure of symmetry of a data distribution, where a symmetrical distribution has a value of 0. A negative value for skewness represents a negatively skewed (or left-skewed) distribution with most of the data values located in the higher score range; one that has a longer tail of low values with the bulk of the distribution falling in the upper-range of values (i.e. mode > median > mean). A positive value for skewness represents a positively skewed (or right-skewed) distribution with most of the data values located in the lower score range; one that has a longer tail of high values with the bulk of the distribution falling in the lower-range of values (i.e. mode < median < mean) (see Field, 2009, p. 788; 794).

The n (Missing) and n (Valid) refer to sample size for those who did not submit a particular piece of written assessment and those who did, respectively.

182 distributions are generally not normally distributed therefore, confirming the use of nonparametric (distribution-free) techniques to analyse the data values. For example, in a large proportion of cases, the measure of skewness is negative, which implies the median is greater than the mean descriptive statistic (see Tables 6.1, 6.2 & 6.3 to confirm this result). More formal tests for distributional normality, such as the Kolmogorov-Smirnov test, were not used. However, simple graphical analysis (histograms) and descriptive statistics were used to inform the choice of test (i.e. Wilcoxon signed-rank test). Regardless, in small sample settings, such as those presented in this study, the aforementioned test is a preferred research method. The descriptive statistics reported in Tables 6.1, 6.2 and 6.3 are only part of the story, but to assess whether meaningful differences exists between these data distributions, a more formal testing procedure is needed (See sections 6.3).

Table 6.1: Descriptive Statistics for Class C

Narrative Essay Genre Argumentative Essay Genre

N0 N1 N2 N3 N4 A0 A1 A2 A3 A4 Mean 19.24 27.31 34.64 18.91 25.45 33.57 35.48 35.14 Std Dev. 4.321 4.262 4.980 2.821 4.684 3.989 4.324 2.973 Median 20 26 36 19 26 34 37 36 IQR 5 7 3 2.75 8.5 6 4.5 3.5 Min. 6 21 14 12 19 22 22 26 Max. 29 36 40 24 34 39 41 38 25th _{Percentile 17 24 34 17.25 21 31 34 34} 50th _{Percentile 20 26 36 19 26 34 37 36} 75th _{Percentile 22 31 37 20 29.5 37 38.5 37.5} Kurtosis 2.342 -0.570 10.098 0.556 -1.300 0.922 3.317 2.579 Skewness -0.788 0.623 -2.935 -0.533 0.207 -0.949 -1.669 -1.510 n (Missing) 2 1 3 4 3 6 3 7 n (Valid) 34 35 33 32 33 30 33 29

Table 6.1 presents the descriptive results for Class C. Note that written assessments N3 and N4 were not completed because of teaching and time constraints. For this reason, descriptive results (and pairwise comparisons) for these two pieces of assessment were excluded for the narrative essay genre. The most noticeable finding was the steady and marked improvement in the aggregate (median) writing scores across both essay genres (from 20/42 for N0 to 36/42 for N2; from 19/42 for A0 to 36/42 for A4), where students started from a similar, relatively lower (as compared to the Class A and B cohort of students) base of written ‘literacy’ skills with respect to both the narrative and argumentative essay genres. Said another way, these results represented substantial improvements for a cohort of students who generally tended to exhibit weaker performance at the start of each genre-specific

183 intervention, but were able to make great gains, which could be ascribed to intensive scaffolding.

Another interesting result, also somewhat exhibited by the results for the other two classes (See Tables 6.2 & 6.3) was the generally reduced variation around these median scores as shown by a progressively smaller interquartile range (IQR) from the second piece of assessed writing onwards – I use the median and IQR simply because of the general non-normality of the data distributions in question. Whether this was purely an artefact of more consistent marking practices or a genuine tighter clustering around the median performance (the centrally-located score) might be difficult to say with certainty. But, given that all pieces of written assessment were (i) marked by the same person, (ii) blind of what previous scores achieved by each student were, (iii) independent of any alphabetical ranking of students’ surnames, and (iv) using the same marking rubric for the entire data collection procedure (all mechanisms to ensure internal validity of the ‘literacy’ scores obtained), one might reasonably assume the latter. If the finding of more tightly clustered performances rather than consistent marking was indeed the case, this further affirms the RtL intervention as it implies that students were not only improving individually, but their respective performances were also tending to be more similar to one another. In other words, to exaggerate for the sake of making the aforementioned point more explicit, at the beginning of the RtL intervention, the tendency was for students to exhibit wildly divergent patterns of performance (the quality of their written submissions were very different). However, throughout the intervention (for both genres of writing), it was increasingly the case that patterns of performance were tending to be more consistent with one another (the quality of their written submissions were better, and increasingly similar to one another), in overall performance terms, not in content terms (i.e. improved performance was not observed to be because students were copying one another’s work).

184 Table 6.2: Descriptive Statistics for Class B

Narrative Essay Genre Argumentative Essay Genre

N0 N1 N2 N3 N4 A0 A1 A2 A3 A4 Mean 20.3 31.71 33.1 37.43 33.48 28.54 32.16 35.97 35.71 33.79 Std Dev. 3.871 4.362 4.221 2.233 4.582 2.546 5.298 3.431 4.428 4.350 Median 21 32.5 34.5 38 35 28 33 37 37 35 IQR 6 7 5.25 3 6 1.75 10 3 7 6 Min. 12 20 21 31 22 24 23 28 26 24 Max. 27 38 39 40 40 36 39 40 40 39 25th _{Percentile 18 28 30.75 36 31 27.25 27 35 32 31.5} 50th _{Percentile 21 32.5 34.5 38 35 28 33 37 37 35} 75th _{Percentile 24 35 36 39 37 29 37 38 39 37.5} Kurtosis -0.500 0.321 1.042 1.741 0.445 4.237 -1.431 0.413 -0.313 -0.330 Skewness -0.187 -0.893 -1.086 -1.114 -0.950 1.653 -0.274 -1.132 -0.958 -0.798 n (Missing) 8 7 5 12 4 7 3 3 1 2 n (Valid) 27 28 30 23 31 28 32 32 34 33

Tables 6.2 and 6.3 present the descriptive results for Class B (Grade 11A) and Class A (Grade 11E). Like Class C (see Table 6.1), there also tended to be a steady improvement in the (median) ‘literacy’ scores across both essay genres for both classes. Although for both classes A and B their pre-intervention scores for the narrative essay genre (21/42 and 26/42, respectively) were substantially lower than their pre-intervention scores for the argumentative essay genre (28/42 and 31/42, respectively), this may be more indicative of these two groups of students being better equipped to tackle an intervention focused on the argumentative essay genre as opposed to the narrative essay genre - the narrative being a genre of writing that students seemed to find a bit obscure and consequently, could have reduced their enthusiasm to participate. However, on aggregate a marked increase in the median scores pre- and post-intervention (albeit with less improvement across the argumentative genre versus the narrative genre), were similar to the patterns exhibited by the Class C. Once again, the smaller improvement (when comparing pre- and post-intervention writing scores) across the argumentative genre may have a lot to do with the fact that students from Class A and B were most likely already well-versed in tackling an essay task of this nature and hence, started from an already higher base of ‘literacy’ skill insofar as academic writing was concerned. On the whole, across all three cohorts of students (Class A, B and C) – representative of two very different socioeconomic and linguistic school contexts – a noticeable finding was the marked improvement in students’ demonstration of their written ‘literacy’ skills. This was evidenced by a marked increase in the median scores.