Reading the Tea Leaves

Standards: Why and What? November 11, 2009

My good friend Georgianna asked me a series of question in her comments to my post. They were great questions so I decided to blog on them!!!!:

>I find this conversation interesting and wonder if you could discuss the “why” of the standards?

This is an interesting question which I am daunted at the prospect of answering in a real way as opposed to giving a glib answer. Philip Howard wrote a post recently that speaks to some of the data reasons for a common data standard or data model.

I think there are some important considerations that make standards important. The following five points were identified by the State Chief School Officers as critical to the nation’s data needs (thanks to Chris Lohse, Director of Data and Research for his articulation of these). These are in my opinion the reasons why we need data standards.

1. Liquidity – Data liquidity is by far the most discussed challenge around education data. Today, the term has gained much more traction in the context of healthcare and patient records, but the fundamental concept as applied to education is that a student’s data should move with him or her and should not be bound to a particular school information system or district data system. As one healthcare commentator noted, it is after all, the individual’s data.

2. Comparability – We struggle greatly in education with developing common definitions for even the most straightforward of education terms. During a workshop in Toledo, OH, participants at six different working tables were asked to write their definition of ‘high school graduation rate.’ Participants were then asked to pass their definition to the next working table and have the participants at that table interpret the new definition just handed to them. The results demonstrated 1) nobody had the same definition of ‘high school graduate rate’ and 2) nobody agreed with the definition that was shared with them. Until common definitions for even our most basic educational outcomes are defined, we will be greatly limited in our ability to actually understand what is happening among all students across the country – and even across a state or school district.

3. Relevance – Schools and districts collect swaths of education data but much of what is collected has limited value to teachers, parents, students, and school leaders. More often, the data are merely tracking outputs, rather than an actual change in status or condition. For example, under No Child Left Behind, many saw limited value in knowing whether teachers were highly qualified according to certifications, tenure, and degree attainment. Rather, a more relevant outcome and metric would be a gauge of whether teachers were effective in terms of student growth.

4. Timeliness – Discovering that a particular student is behind their growth and learning trajectory at the end of a school year, with little to no time to change course, is of limited value. Instead collection, analysis, and reporting information about students, teachers, schools, school leaders, and districts should take place on a time schedule that allows for change of course and performance improvement. Data and analysis provided beyond the point when corrective action can be taken is, at best, useless. At its worst, it is irresponsible.

5. Accuracy – The strategy and analysis emerging from good information is only as good as the underlying data. Increasingly, self-validating data collection tools are improving data accuracy. Put simply, when relevant data are presented to teachers and other education stakeholders in a timely, coherent way, those stakeholders begin to ensure the quality of the data inputs.

>Are they to define or align expectations in US education?

This is a key thing for us to remember- there are different kinds of standards. There is work ongoing with 48 states to create a comparable, standardized set of student expectations. These are academic content standards. I am primarily talking about data standards.

These are more about defining data elements, their data type, their length, their description, their relationships with other data elements. For example – Student First Name, Course ID, Enrollment Status, etc. I would call these “data standards”.

There is a new effort coming under way which I will be involved with and documenting closely to set data standards in the country. This is being done in partnership between USED, CCSSO, SHEEO

>If so, in what realm – student expectations, teacher expectations, system expectations?

Yes – the direction is to both support next generation learners and teacher development. System expectations are directly correlated to that. I don’t have space right now to discuss this but it is happening.

Another question that came to me from a discussion with Jean around some pilot work in healthcare – these pilots have created a hospital in which doctors aren’t compensated in a fee for service format, but rather by salary with bonus incentives around patient outcomes.

I began to wonder if there is work going on to define standard desired outcomes for school systems and if so, if there are any areas where teams of teachers and administrators are given an incentive bonus for particular student outcomes?

This is a huge issue. I won’t attack it in this post and much has been written about it, but it is clear that teacher effectiveness and accountability is going to be massively focused on and it is- I believe- a general consensus that some kind of growth model is necessary to do any kind of reasonable analysis of effectiveness of students, educators or systems in education.

Enough for today- more later. Thanks for the questions!