The Interactive Whiteboards, Pedagogy and Pupil Performance ...

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Table 5 sets out the same type of regression for the same schools over Key Stage 4. Here some small, yet significant, estimates of the effect of IWBs on department performance are found. We find a negative effect for Maths and Science and a positive effect for English. Table 5: School Fixed Effects – Key Stage 3 to Key Stage 4 (GCSE) Maths Maths English English Science Science Fixed effects Random effects Fixed effects Random effects Fixed effects Random effects IWB treatment **-0.017 (0.007) *** -0.018 (0.006) ** 0.014 (0.007) ** -0.015 (0.007) *** -0.019 (0.006) Time dummy 0.032 (0.007) 0.050 (0.037) ***-0.112 (0.043) 0.023 (0.043) 0.021 (0.041) School level peer YES YES YES YES YES controls Pupil controls, incl. YES YES YES YES YES KS3 score R-sq within groups 68% 68% 53% 63% 63% R-sq overall 69% 74% 27% 57% 69% Obs 9,189 9,189 8,980 9,174 9,174 Number of groups 30 30 30 30 30 Hausman p>chi-sq 0.12 0 - Fails 0.88 Note: ***=significant at 1% level; **=significant at 5% level; *=significant at 10% level. Explaining the coefficients on the GCSE models The school fixed effect regressions reported in Table 5 show a negative relationship between pupil GCSE grades and the installation of IWBs in Science and Maths. It is possible that this is a genuine causal relationship, meaning that the installation of IWBs in these departments has, because of the disruption to teaching methods, reduced pupil performance in GCSEs. However, this seems unlikely so several possible alternative explanations are discussed here: Type II statistical error. Coefficients are generally reported as significant at the 5% level, giving a 95% level of confidence that the relationship is genuine. However, this means that in 1 in 20 cases, an absence of a causal relationship between two variables produces a statistically significant coefficient by chance. Because of this, we should only consider relationships between IWB installation and pupil performance to be causal if they are robust across all the model specifications reported in this paper. Non-random deployment decision. We know little about why schools installed their additional IWBs in one department rather than another, but it is likely that the decision was not entirely random. So, for example, if schools systematically tended to deploy IWBs in English departments that were improving in their effectiveness over time (for other reasons), this would result in a positive coefficient on our treatment variable for reasons unrelated to the IWB installation. It is impossible to test fully whether this was taking place, but one reason why departments will tend to improve or decline in effectiveness from one year to the next is just simple reversion to the mean; i.e. a department with a high ‘value-added’ score in 2004 would be more likely to have a fall in value-added between 2004 and 2005. 66
This mean reversion leads to a negative correlation (ρ = 0.45) between a department’s performance in 2004 and the change in their performance between 2004 and 2005. Figure 9 shows the association between a department’s GCSE performance in 2004 and the change in effectiveness between 2004 and 2005, with both measured (as a z-score) via the mean pupil performance in the department, having adjusted fully for the prior attainment and socio-economic characteristics of the intake. Figure 9: Possible Mean Reversion of Departmental Effectiveness changemean -1 -.5 0 .5 1 -1 -.5 0 .5 1 1.5 mean2004 Assuming mean reversion explains a significant part of the change in a department’s ‘effectiveness’, if the mean score in 2004 is positively correlated with the increase in IWB installations, this would explain the negative coefficients for Maths and Science. However, the correlation between changes in IWB levels and 2004 effectiveness for Maths is actually negative and the correlation for Science is positive, but small (ρ = 0.05), so this does not seem a likely explanation for our negative treatment coefficients. Censoring on the distribution of GCSE scores. If the increase in right-hand censoring of Maths and Science GCSE scores in departments where the IWBs were installed was more serious than for those departments where few or no extra IWB were installed, this would explain the negative coefficients on the Maths and Science estimates. This censoring occurs because there is a maximum high score of an A* for students, and results where a student who achieves an A* might have achieved a higher grade were one available. There is some evidence that censoring of the GCSE scores affects the schools that had a greatest installation of IWBs between Oct 2003 and 2004 the most. The correlation between the change in incidence of A* grades in the department (indicating increasing risk of censoring) and the change in IWB installations is ρ=0.17 in Maths. However, there is also a significant correlation of a similar magnitude in English, yet the coefficient on IWB installation is positive in this case. Furthermore, there is no significant correlation in Science departments. Therefore, overall it is 67
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RESEARCH The Interactive Whiteboard
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CONTENTS EXECUTIVE SUMMARY ……
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EXECUTIVE SUMMARY AIMS AND METHODS
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substantially enhance the use of IW
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Observations for this project sugge
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1. THE STRUCTURE OF THIS REPORT Thi
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2003). Whilst many of the factors t
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A range of data was collected in ea
Page 18 and 19: 3.2.4 Pupil Focus Groups Focus grou
Page 20 and 21: 3.5 Statistical Analysis of Pupil A
Page 22 and 23: • Reasons given for the choice of
Page 24 and 25: 5. FINDINGS: THE IMPACT OF THE INTR
Page 26 and 27: colleagues or using commercial soft
Page 28 and 29: textbooks or worksheets. This is tr
Page 30 and 31: 5.3 How the Available Resources Sha
Page 32 and 33: Illustrative Case Study. Example: T
Page 34 and 35: Illustrative Case Study. Example: U
Page 36 and 37: Illustrative Case Study. Example A
Page 38 and 39: Illustrative Case study. Example B
Page 40 and 41: Illustrative Case Study. Example C
Page 42 and 43: • Familiarise themselves with the
Page 44 and 45: were aware of this dimension and ha
Page 46 and 47: is not good, if the students aren
Page 48 and 49: 5.9.2 Teachers’ use of Multi-Medi
Page 50 and 51: Figure 8: Frequency of using IWB by
Page 52 and 53: Science classroom that map onto exi
Page 54 and 55: long run. Few teachers however curr
Page 56 and 57: On the negative side, a sizable min
Page 58 and 59: These kinds of difficulties can be
Page 60 and 61: change in their own setting. Others
Page 62 and 63: a number of schools is for us a sec
Page 64 and 65: Table 1: Key School-Level Statistic
Page 66 and 67: 8.1.2. Difference-in-Differences (S
Page 70 and 71: unlikely that right-hand censoring
Page 72 and 73: 8.1.4 Difference-in-Differences (Be
Page 74 and 75: 8.1.5 Discussion Overall, this stat
Page 76 and 77: figure; the mean percentages of pup
Page 78 and 79: Conclusion The larger scale survey
Page 80 and 81: Smith, H.J., Higgins, S., Wall, K.,
Page 82 and 83: schools. These were combined with p
Page 84 and 85: elevant hard and software and the r
Page 86 and 87: Within government generally, where
Page 88 and 89: Yet if there is little doubt in pol
Page 90 and 91: overhead projector (OHPs) (Though,
Page 92 and 93: intention to equip all children wit
Page 94 and 95: technology in much the same terms (
Page 96 and 97: In some lessons with IWBs these tec
Page 98 and 99: use shows considerable variation in
Page 100 and 101: Glover, D. & Miller, D. (2001) "Run
Page 102 and 103: Annex C Analysis of the IWB Baselin
Page 104 and 105: Table 7: Number of IWBs by Departme
Page 106 and 107: Figure 3: Funding source by subject
Page 108 and 109: Figure 7: Sources of funding after
Page 110 and 111: Are perceptions of ICT consistent w
Page 112 and 113: Table 8: Allocation of LC funding t
Page 114 and 115: Can perceptions of ICT resources in
Page 116 and 117: Figure 16: Number of IWBs in Maths
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schools have done this) and 100 mea
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Use of IWBs in Science Departments
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department feels all six areas are
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Use of IWBs in English Departments
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The training needs of English depar
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Annex D Analysis of the IWB Teacher
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Figure 3: Type of interactive white
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Reported Frequency of IWB Use by Te
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Figure 8: Frequency of using IWB by
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How are Teachers using their IWB? A
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Figure 14: Ease of finding suitable
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What type of IWB training have teac
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investment of time to integrate int
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Many of the newer teachers do not a
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Figure 25: Statements which the hig
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eport IWBs are used hardly ever or
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Table 2: Positive Statements: Perce
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2. 3.3 Response to technology. Tabl
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Annex F: Survey Instruments 1. The
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PERFORMANCE: AN EVALUATION Baseline
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Room Subject Source of funding Date
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INTERACTIVE WHITEBOARDS, PEDAGOGY A
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2. The pupil survey INTERACTIVE WHI
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