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Extra resources for A branch-reduce-cut algorithm for the global optimization of probabilistically constrained linear programs

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Similarly, schools that have a high rate of pupil mobility might wish to use the value added lines to monitor the attainment and progress made by pupils who are with them for a whole key stage. Subject co-ordinators for core subject may wish to monitor pupils’ progress in the subject they manage. For example, they might wish to sample the progress that is being made by higher attaining, average and lower attaining groups of pupils in their school. This would help them to see whether all groups are making progress at a similar rate throughout a key stage.

The upper and lower quartiles are represented by the dotted lines. On this graph, the upper quartile is above the median and the lower quartile is below the median. The data on the horizontal axis represents a pupil’s average point scores at an earlier assessment point (Key Stage 1 1996), and the data on the vertical axis represents the marks available in the English, mathematics or science tests. A pupil can be plotted on to the value added graph using as co-ordinates, the pupil’s average points score from Key Stage 1 (horizontal co-ordinate) and their mark in the English, mathematics or science test (vertical co-ordinate).

1. 8. 5. 4 in Chapter 6. The main issues at Key Stage 2 emerging for the school at this point were: ● The results in English were above average. ● Results in mathematics and science were average. ● The results at Level 5 were average in all three subjects. ● As the school has only 7% eligible for free school meals, its results were below average in mathematics and science when compared with similar schools. Managing School Test and Assessment Data Manual by Theresa Mullane Published by Pearson Education © Pearson Education Limited 2002 21 Chapter 2 · Using information from data from local and national sources Action that the school took as a result of this analysis: 1 It was pleased with the improvements in the English results and could identify specific actions it had taken to raise standards.

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A branch-reduce-cut algorithm for the global optimization of probabilistically constrained linear programs by Cheon M.


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