Title: A Pig Don't Get Fatter The More You Weigh It: Classrooms Assessments that Work
Editors: P. Jones, J. Carr, R. Ataya
Publisher: Teachers College Press
Apparently, data work and analogies go hand in hand. First, dancing. Now, pigs. I'll have to keep this in mind if I ever get around to writing a book. The author explains the title as an English phrase that refers to farmers repeatedly weighing their pigs "for indications of profit". I think the classroom equivalent would be "kids don't get smarter the more you test them." I apparently really liked this book. I count 9 red tags ("Wow, cool!") and 11 green tags (reference to read) and two big post-it notes to mark entire sections. I say apparently, because every time I look at the bright pink cover, I wonder how good a book can be that uses a picture of a pig in place of an apostrophe. (I'll let these guys articulate my issue with misplaced apostrophes)
Despite their disregard that the most noble of punctuation marks, the book is solid. First, I'd recommend it for anyone who works with classroom assessment, especially in diverse schools. I started to skim the chapter, "Can you listen faster?" on assessments for linguistically diverse learners (LDL) but went back and read it carefully, knowing I had never really read anything on the topic. I would like to talk to friends and colleagues that work with LDL as some of the assessment adoptions they recommend seem a little off, but I did learn a great deal from the chapter. I've read a lot on assessment for students with disabilities, but their chapter on inclusive assessment addresses the need for validity and respect for the learner through the use of portfolios that make a lot of sense. The concept might be overwhelming for a general education teacher with 25-30 students but for a resource room or consultant special ed teacher with a reasonable caseload, it is very doable. These chapter match nicely with Data-Driven Differentiation by Gregory and Kuzmich.
I didn't care much for the anecdotes they use to start each chapter but that's just personal preference. The section on learning communities covers most of the bases (they overlooked the learning community nearest and dearest to my heart) but has some good recommendations for creating and following through on assessment focused collaboration.
The section that was most heavily tagged was called "Performance Assessment in the Elementary Grades". I've been doing a great deal of work around standards alignment and moving from state assessment data to multiple measures and I've been playing around with data collection forms but wasn't happy with any of them. The authors went through the same struggles, I think, because their final product matches where I would have gotten in about three or four more rounds of fielding testing. Many thanks to them for saving me the time. Their form even matches with my color-coding system, so that makes me even happier to have found this book.
The information on rubrics leaves a little to be desired but it's not a book on rubrics, so I forgive them for that. All in all - a good solid book and a worthy addition to any professional library.
I'm now reading Using Data Analysis to Improve Student Learning by Wong - I see detailed steps on building pivot charts in Excel in a future chapter so I think I'm going to like this one, too. But really, think I'll ever meet a book on data or assesssment that I DON'T like?