Thinking about NCLB – again

I have to admit I have been ignoring NCLB – perhaps hoping it would go away. I guess now I must accept that this will not be the case. We do need to pay attention to how well each student is achieving and be concerned when progress is lacking. It is the “accountability” thing that bothers me. While I am a researcher, I also live in the world of real schools, real teachers, real neighborhoods, real tests and real instructional resources. I also understand that there is money to be made and jobs to be protected. I am not optimistic that the “problem” of poor achievement is simple or that some of the proposed consequences (allowing students to transfer from poorly performing schools resulting in lower levels of resources and probably the removal of some of the more motivated students) are meaningful solutions. Simple solutions and implied blame work well in the political arena, but such practices are more useful for generating votes than improving achievement.

So here is the deal. The Department of Ed has commissioned some “quality” research that will evaluate the potential benefits of a set of carefully selected reading and math software on standard measures of achievement. Companies were encouraged to propose the use of products in these areas and provide evidence of prior evaluation. The “winners” are listed on the Ed.gov web site. The focus will be on low-income schools. The studies will be conducted in schools that have not used this software but are interested. The research will be based on a control/treatment design model (I would guess this means that classes will be assigned at random to the no technology / technology conditions). The research will be considered “successful” if the treatment generates an effect size of .35.

Don’t get me wrong – I think this will be interesting. It may establish that some companies have created bodies of instructional materials that are effective. This will at least be a starting place.

Will this type of research tell us what software schools should purchase? I assume any company that has a product on this list and generates an effect size greater than .35 may think so. It will not be possible to determine why any given product is effective and hence it will not be possible to determine if similar products might be useful or how products might be improved.

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