4.5.2.1 Introduction
As stipulated in Chapter 3, there were two groups in my research, namely the control group and the target group (See 3.1). The learners in the control group were Dan, John, Rudolph and Bart; and the learners in the
percentages of each learner’s pre
inserted into a spreadsheet on Excel. From there I used the “average” function to calculate each learner’s averages of all six assessments at each assessment time. These averages were then inserted into figure-
average percentages achieved and the x achieved, either at pre-, mid-
Figure 4.1
As hypothesised, all learners’ average test scores increased from the pre
Figure 4.1). Peter and Mia both started at a much lower level than Marc and Suzy in the low-progress group and made a steep incline towards the post
39%) whereas John and Bart, who did not participate in the research interv
groups) completed six assessments for analysis, both qualitative (see above) and
titative. Each assessment was marked according to the guidelines set in Clay’s (2002)
An Observation Survey of Early Literacy Achievement. Each assessment provided scores that could be processed into percentages as data for possible quantitative analysis.
comparison between all eight learners
As stipulated in Chapter 3, there were two groups in my research, namely the control group group (See 3.1). The learners in the control group were Dan, John, Rudolph t; and the learners in the target group were Mia, Marc, Peter and Suzy. The
percentages of each learner’s pre-, mid- and post-test assessments were calculated and inserted into a spreadsheet on Excel. From there I used the “average” function to calculate
ach learner’s averages of all six assessments at each assessment time. These averages -form, and are given in Figure 4.1. The y-axis represents the average percentages achieved and the x-axis indicates the time at which each a
or post-test.
1: Learner Progress from Pre-test to Post-test
As hypothesised, all learners’ average test scores increased from the pre-
Peter and Mia both started at a much lower level than Marc and Suzy in the progress group and made a steep incline towards the post-test (Peter by 50%; Suzy by 39%) whereas John and Bart, who did not participate in the research interv
groups) completed six assessments for analysis, both qualitative (see above) and
titative. Each assessment was marked according to the guidelines set in Clay’s (2002) provided scores that could be processed into percentages as data for possible quantitative analysis.
As stipulated in Chapter 3, there were two groups in my research, namely the control group group (See 3.1). The learners in the control group were Dan, John, Rudolph
group were Mia, Marc, Peter and Suzy. The test assessments were calculated and inserted into a spreadsheet on Excel. From there I used the “average” function to calculate
ach learner’s averages of all six assessments at each assessment time. These averages axis represents the axis indicates the time at which each average was
- to the post-test (in Peter and Mia both started at a much lower level than Marc and Suzy in the
test (Peter by 50%; Suzy by 39%) whereas John and Bart, who did not participate in the research intervention lessons,
displayed a gradual increase towards the post-test (John by 25%; Bart by 24%). The cluster of Dan, John, Rudolph and Bart represents what the class average would be for this group of Grade ones. Mia and Marc did not reach this average grade level, but a sharp increase in scores proved their progress (Mia by 40%; Marc by 32%). Therefore all four learners in the target group, Mia, Marc, Peter and Suzy, increased their test scores from the pre-test to the post-test with the knowledge that they gained from the research-based lessons and also the knowledge each learner gained in the classroom.
These results have further implications. Consider, for example, the sharp increase in the scores of the target group after the mid-test. A reason for this increase could be that the learners were not used to the approach I took to teaching literacy. Therefore the four low- progress learners used the time from the pre-test to the mid-test to grow accustomed to the new approach. After the mid-test, they were used to my research-based approach, and they were able to use the familiarity with my approach to support their learning. It is thus possible for learners to adjust their learning to the research-based approach that I used.
A second implication of these percentages concerns accelerated progress (See 2.6.1). Every learner in the target group’s average at the pre-test was lower than all the control group’s learners. However, by the post-test, some of the low-progress learners had caught up with the average-progress learners, as indicated by the cluster at the post-test. This means that the low-progress learners were able to accelerate their learning over the same period of time during which the average-progress learners’ learning maintained only a gradual increase. This is illustrated in the percentage increase of the low-progress learners in comparison to the average-progress learners. The low-progress learners made an improvement of 35% and above from pre-test to post-test, with Peter achieving an increase of 51%. The average-progress learners only made an increase of 29% and below from pre- test to post-test, with Rudolph making the highest increase of 29%. Therefore, in answer to my first research sub-question (See 3.3.2.1), the individualised contingent literacy
programme was successful in increasing the average assessment scores of each learner in light of a quantitative perspective. Research-based literacy lessons were thus successful in the context of my research.
The third implication concerns the improvement of even the lowest progressing learners. Although Mia was still well below the average-progress group by post-test, she made a great increase in her own average scores during the research, i.e. 10.3% at pre-test, 27% at mid- test and 50% at post-test. This shows that any learner is ready to learn and improve their literacy skills, given the opportunity and proper research-informed teaching.
Although all eight learners’ reading rate was calculated according to a percentage and considered in the average of their performance in Figure 4.1, each learner’s level of reading by pre-test and post-test will also be represented as the following:
Table 4.7: Reading Recovery® Book Levels at the End of the Research
LEARNER READING RECOVERY® BOOK LEVEL BY PRE-TEST READING RECOVERY® BOOK LEVEL BY POST- TEST Ta rg et gr ou p/ Lo w pr og re ss le ar ne rs Mia* 0 1 Marc* 0 2 Peter* 1 4 Suzy* 1 5 C on tr ol gr ou p/ A ve ra ge pr og re ss le ar ne rs Dan* 4 6 John* 2 5 Rudolph* 2 4 Bart* 2 3
*All names are pseudonyms
It is evident that Mia and Marc were still well below the average-progress learners’ level, but Peter and Suzy were well within the expected average reading levels. Bart, an average progress learner, had quite a low reading level and, given the opportunity, could have shown the same results as Peter and Suzy with research-based lessons. In the control group, John advanced the most with three levels, and in the target group Suzy advanced the most with four levels and caught up with John. This mirrors the accelerated learning seen and
discussed in Figure 4.1. Once again, the importance of a range of levelled books made this acceleration possible, and stresses the need for supportive material (See 4.4.2.5).