How is the PSLE aggregate score used in the posting exercise?
As an example, let's compare two children, child A and child B who both applied to the same desired school with a limited vacancy. Assume child B has a higher aggregate. Then, two considerations come into play:
- Since child B has a higher aggregate, he is ranked higher meaning his posting preferences would be considered *first* ie before child A is considered.
- According to the MOE posting process, child B will be considered first for each of his choices over child A.
- Child B would thus get his desired school...but always provided there is a vacancy.
To summarise: Your child's posting to the schools of his choice would depend on whether there is still a vacancy, after the posting exercise has attended to students who ranked higher than your child and who also chose the same school.
T-score table based on 2008 PSLE aggregate scores
For the 2008-09 admission exercise to admit the January 2009 secondary 1 cohort, check out the list of secondary schools arranged according to their admission T-score range and also by alphabetical order (click on the relevant icon below):
T-score range:
Alphabetical order:
These tables serve as a historical reference point, to help us appreciate the most recent secondary 1 admission exercise held in the 2008-09 period. The tables and the suggestions below could then help to add value to your own process to shortlist desired choices for your primary 6 child's secondary school options.
Secondary school selection considerations
Based on the academic performance (meaning T-scores), you could consider:
- schools with cut-off aggregate scores that reflect your child’s performance. These cut-off scores can vary depending on the performance of the year's cohort, and the popularity of the school.
- selecting from a choice of schools that fall within a reasonable spread or range of cut-off aggregate T-scores:
- slightly higher than your child’s academic standard,
- that matches your child’s PSLE performance, and
- slightly lower than your child’s academic level.
As implied, you can use the historical data of the previous year's (in this case, the 2008 reference data tabulated in this article) as a guide to draw up a shortlist, and then confirming with the shortlisted schools directly for the latest 2009 PSLE data to revise and finalise your choices.
- the value-added options including co-curricular activities (CCAs) offered by the schools in your drawn-up list. These might vary from time to time so it would be best to call the schools in your shortlist for the latest information. For general appreciation, check out also MOE's CCA guidelines for secondary schools.
Finally, you may also want to consider how far the school is away from home, though in the interest of getting into a good school, you might be willing to make sacrifices in ensuring he gets to and from school in good shape!
IMPORTANT NOTE:
- The data referred to in this article is sourced from the Singapore Ministry of Education. Please note that the tabulated information is for historical reference only and serves only as a guide to appreciating the most recent (January 2009) admission exercise.
- Keep in mind that secondary schools can vary their PSLE aggregate admission criteria from year to year depending on each school's popularity and available vacancy for the year.
- Before making any final decision, always check with the school of your choice or the Ministry of Education directly for the latest information.
Related articles
School selection criteria - an educator's perspective
Schools with areas of excellence under MOE's Niche Programme
Please enlighten how the T-score is being calculated ?
Thanks
WS Chick
The national context is factored in by considering two key statistics:
- national average performance for the subject considering all children who took the subject examination. This refers to the average mark or mean.
- spread of marks obtained by all children around the average or mean. This refers to the statistical term called standard deviation (SD). This value is ascertained via statistical analysis of all the raw scores.
Using the above ie raw score, mean and SD:
T-score --> 50 + {[10 x (raw score - mean)] / SD}
Example (to one decimal place):
Child A's subject raw score --> 90
National average or mean for the subject --> 70
Spread of all raw scores about the average --> 15
Child A's T-score for the subject:
T-score --> 50 + {[10 x (90 - 70)] / 15]}
= 50 + {[10 x 20] / 15}
= 50 + {200 / 15}
= 50 + 13.3
= 63.3
Essentially, the 50 in the formula serves to re-centre the national average about a mid-point between 0 and 100. So you would note that if child A's raw score equals the national average, his T-score equals 50.
Currently, the MOE site does not have data for the 09/10 exercise.
