Of course, the truth behind the expression is that if something is starting to seem too complicated, there's probably an easier way. Great teaching, great writing, even great science and great math aren't really about being complicated, they're about making super-complicated things...much simpler. Steven Hawking is famous not only for his ideas, but his attempts to make them (at least somewhat) understandable to the average person. Apple computers aren't the most technically powerful machines, but they do allow normal people the most amount of leverage in solving problems and putting together complex tasks. The surest sign of the best solution is simplicity.
And then, of course, there's the PA Teacher Effectiveness Chart. Starting next year, all teachers will be evaluated on four major categories including your personal observations (50%), and school data (15%) which is taken from Keystone tests, graduation rates, AP scores, and other factors. The remaining 35% of your annual score (0-3 scale) is split from your specific student data (Keystone scores, IEP performance, etc). and "elective data". Many teachers (a large majority) don't have any officially tested students so most teachers rely heavily on "elective data" as the second largest portion of their annual score.
We've heard about this model for the past four years and until today, we had no idea what "elective data" means. In fact, even though today is over, we still have no idea what it is. From the looks of it, elective data involves teachers in any given course (Honors 11th grade English for example) sitting around together, selecting up to five common assignments that are aligned to state standards, and setting goals for student performance on each one. Perhaps the teachers will decide "at least 70% of my students will get at least 70% on the project". By meeting this goal, those teachers will "earn" their remaining 35% of their score. Of course, there's five of these assignments...each with their own sets of data and subdata...which ultimately only makes up a fraction of a fraction of a teacher's evaluation.
To prepare for all of this, we spent the day learning about how to make multiple choice questions, how to align assignments to standards, and what "assessment" really is. In addition to teaching, lesson plans, projects, assignments, standardized testing, and all the other teaching jobs out there...we not have to construct our own measures by which our students (and our own profiles) will be measured. See the slide below for an example.
If you're still reading this, I applaud you. It's way too complicated. All of this effort, from the observation, to the Keystone data, to the IEP information, to the Student Learning Objectives (SLOs) is all used not really to improve learning, but to "accurately measure" teachers...with either a 3, 2, 1, or 0. You can argue that the old "one observation per year/ Pass or Fail" model wasn't enough feedback for teachers...but this new convoluted system of trying to compress a teacher's qualitative body of work into a single quantitative number through varying degrees of algoritims, initiatives, tests, and paperwork defies not only logic itself, but the three-pieces-of-tape rule. I'm not sure how the system got this far, but it's clear it's no longer the best answer.