"Bear in mind that the wonderful things you learn in your schools are the work of many generations, produced by enthusiastic effort and infinite labor in every country of the world. All this is put into your hands as your inheritance in order that you may receive it, honor it, add to it, and one day faithfully hand it to your children. Thus do we mortals achieve immortality in the permanent things which we create in common." - Albert Einstein

Thursday, August 27, 2015

Assessments Should Inform Instruction

Assessments in education provide the data on which decisions can be made. Data on learning can inform teaching. However, to make assessments helpful, it is important that conclusions are drawn correctly. How a teacher interprets the scores of students in an exam determines how such assessments can direct improvements in teaching and curriculum. Obviously, if scores in exam are taken by a teacher as mere reflections of a student's inherent characteristics then such assessments cannot shape instruction. In an ideal setting, assessments can help, but in the real world, it all depends on how a teacher makes sense of these assessments.

Bertrand and Marsh provide us a glimpse on how assessments are currently viewed in the real world. Unfortunately, it is not a pretty picture. In their paper published in the American Educational Research Journal, they find that a significant fraction of teachers attribute data on learning on supposedly "stable student characteristics". This is disconcerting as such attitude harms students that have been designated with labels such as "English language learners" or "special education".

In the paper, Bertrand and Marsh identify four different models:

Above copied from
Melanie Bertrand and Julie A. Marsh
Teachers’ Sensemaking of Data and Implications for Equity
American Educational Research Journal
0002831215599251, first published on August 24, 2015 as doi:10.3102/0002831215599251

And the sad part is shown in their results:

Above copied from 
Melanie Bertrand and Julie A. Marsh
Teachers’ Sensemaking of Data and Implications for Equity
American Educational Research Journal
0002831215599251, first published on August 24, 2015 as doi:10.3102/0002831215599251

To get a clearer idea of what these models really entail, below are examples provided by Bertrand and Marsh for each of the models:

Model 1
What . . . [one class] had a hard time [with] was actually taking the story and analyzing it . . . , and I think that was because I maybe didn’t give them specific examples. With my other group, I think I went into more detail. . . . So maybe that’s . . . why my students did, one group did better than the other.
Model 2
[On the benchmark] there was stuff for the kids . . . that was hard reading. For me, personally, how they ask the questions, the words they used to ask questions, tend to be difficult. So I use that as kind of test-taking skills rather than just standards, kind of teaching them what it means, what they are asking you. . . . [A] lot of times the kids, they can read, and they know what they are reading, but they don’t understand what they [the questions] are asking of them. They don’t understand the question. So lot of times, I’ll take those benchmark questions, and I’ll just put in the words if they can understand, kind of chart it up, so they’ll have it on the [wall in the] room, so they know.
Model 3
There was a question that 100 percent of the students got right, every single one. We looked at it . . . and we asked ourselves, ‘‘How was that useful? If everybody got it right, was it a good question? I mean, could we have done, how can [we] tweak it so it would be more useful and more information could be derived from it? Was it framed in . . . such a way that it was too easy?’’

Model 4
I have 14 to 16, I think it’s 16 now individuals with special needs [students in special education] and a lot of ELs [ELLs] in that classroom, so it’s a lower group, a lower abilities cohort. . . . I know that inferential things are difficult for that mindset, okay? They’re very linear in their thinking, so we should be able to forecast the problem areas. So areas that are more inferential, like, what was the climax and what was the resolution? I’ll make sure that I cover that [with] multiple exposures in this classroom in many different ways: in game format, in videos. I’ll throw in a lot of things . . . and trying to get them to understand that standard.

Nearly half (40 percent) attribute test scores to "student characteristics". The above data are not from schools where teachers are isolated and uninformed about assessments. The schools included in the study have either hired data or literary coaches, or even invested in professional learning communities.

In medicine, it is unimaginable for the field to ascribe the success or failure of a medical procedure or drug to patients' characteristics with such frequency. Sadly, this is the case in education.





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