"Maybe one of the most cost-effective interventions ever studied"

In this month's TES column (I'm calling it a column, it sounds better than a blog), I call parent-teacher meetings in Bangladesh "maybe one of the most cost-effective interventions ever studied". Here's the maths behind that claim. 

First, the intervention found 0.377 standard deviation effect on Grade 5 scores and 0.141 standard deviation (not statistically significant) effect on Grade 3 scores. If we take the average of those, that is 0.259. That's equivalent to around 1.7 extra years of school (based on Evans & Yuan's estimate that 1 standard deviation ~ 6.5 years of school).

The cost was $3 per student over the two years. The author Asad Islam does the conversion using only the 0.377 effect size for Grade 5, writing "Thus, the cost per average 0.1 SD increase in test scores per student is $0.66 or $1.58 for the full program over 2 years."

J-Pal put together a list of the cost-effectiveness of different interventions on their website, now gone, but replicated by Romero, Sandholtz, & Sandefur in the Liberia Partnerships Schools paper (copied below). Islam's $1.58 per 0.1 SD increase is equivalent to 6.3 standard deviations per $100. If we use the more conservative estimate of 0.259 SD (averaging across Grade 5 and Grade 3 results) that still works out at 4.3 SD per $100 spent. That lower estimate still puts this intervention at third place in the ranking, so there you go: "maybe one of the most cost-effective interventions ever studied".

Testing, testing: the 123's of testing

Here's my summary of the new Annika Bergbauer, Eric Hanushek, and Ludger Woessmann working paper for CFEE.

"teachers tend to oppose standardised tests, partly because they perceive them to narrow the curriculum and crowd out wider learning. However, it is intuitive that the effects of testing could vary dramatically by context. Indeed, the impact may very well follow a so-called “Laffer curve”. At low levels of testing, an increase may lead to better performance as it provides relevant information and incentives to actors in the education system. Yet if there are already high levels of testing, further increases may very well decrease performance, due to stress, for example, or the effects of an overly-narrowed curriculum. If so, we should expect the impact of testing to follow an inverted U-curve – or at the very least display diminishing returns. Furthermore, the impact of tests is also likely to depend on exactly how they are used in the education system. 

This paper provides perhaps the first systematic evidence on these issues"

Read the rest here.