Ways-of-Thinking

Assumptions That Support Decisions and Processes

As we have evaluated grant-funded education programs, helped schools with School Improvement Plans, and helped educators move to data-driven decisions, we have seen that many programs are designed based on beliefs that have their roots in previous eras, and lack of awareness of what can be known using computers, technology, and research on best practices.  Sometimes people don’t know what they don’t know.

People designing the programs we evaluate have good intentions, and believe the programs may result in the outcomes they want.  To help them move toward modifying programs to get better outcomes for kids, we try to understand what beliefs they have, and what skills they lack and may even be unaware of.  We aren’t always successful, because changing beliefs and learning new skills can be very difficult.  But, often we are successful. Some trends we’ve seen repeatedly make sense given how our culture has evolved, how programs used to be funded (for demographic groups), and the advances in technology that people may not even be aware of.

Beliefs About At-Risk

We see that the idea of “at-risk” meaning low-income or minority, instead of meaning “reads below grade level” accounts for a lot of mis-alignment of services. Schools used to use the lunch-status list to align academic services.  As that practice has stopped, we found people telling us that they had to “guess” who was poor now that they could no longer use that list.  They’d tell us they look at the mothers’ pocket books, the buses that kids ride, and other clues to decide who to enroll in services designed for students who read below grade level, for example.  This has not been uncommon.

We have observed over and over that providing average and above average students with remedial curriculum results in far less learning than if these students are challenged with enriched curriculum.  In fact, we have seen this so frequently that we believe most of the achievement gap between low- and not-low income students is caused by the curriculum each group generally gets.  As we’ve helped schools use data to identify high achieving low-income students and get them out of remedial programs and into enriched programs, we see achievement gaps close and suspensions and dropout rates lower.

Knowledge and Skills for Working With Data

No experience working with data often leads to keeping records in ways that make identifying effective practices impossible.  We see people doing things on paper that could be done more accurately and in a fraction of the time if done on a computer (in a fraction of the time and with far greater accuracy and permanence).  We also see that not understanding that the skills and knowledge needed for working with data sets is extensive and often results in having school systems hiring people without these skills to work with data.

Below, we profile some of the programs that we have worked with.  These might provide insight into what kinds of beliefs and skills are impacting educational programs and practices, and how we could get better outcomes.