Educators need to be data literate. Teachers need to know how to integrate all sorts of data, including student performance results, attendance and a range of other information, into their classroom practices. Administrators need to use other sources of data to make curricular, personnel, financial and other types of decisions.
But where are the preservice courses to help ensure that the next generation of educators is able to use data effectively? Many schools of education may think they are teaching data literacy skills either through stand-alone courses or integrated courses. Research calls that into question.
Schools of education and preservice data literacy
A recent survey by WestEd indicates that although institutions report that they have such courses, syllabi indicate otherwise. Specifically, on deeper examination, many syllabi describe courses that cover only a fraction of the skills educators need to make effective use of data in the classroom. For example, many so-called data courses are really assessment courses—a serious problem given that the ability to understand and react to assessment data is only a subset of the broader data literacy skills that educators are increasingly expected to have.
Why don’t education schools teach this critical skill? We can look at the problem on two levels. First is the school-by-school level. Every school of education faces constraints that slow the pace of change. For instance:
- A given institution may not have room in their curriculum for another course.
- It may not have faculty who have the expertise to teach education data courses. (Look around and such experts are rare; there’s a sectorwide deficit of candidates qualified to teach courses on education data literacy.)
- It may not have open faculty slots, and when it does, the institution may opt to use the slots for more mainstream positions.
Second is the systems level. These institutions are part of a complex system that includes professional organizations, credentialing and licensure agencies, testing companies, state departments of education, and local education agencies. The institutions, although autonomous, do not function in isolation. They must react to emerging trends and needs in the field. Data literacy is one such emerging trend.
The barriers to change at this systems level remain significant, however. For instance, as a sector, we haven’t even agreed on a cogent definition of data literacy yet. And educator licensure requirements vary greatly from state to state, ranging from no requirements other than proof of citizenship to meeting highly specific sets of skills and knowledge.
Those who believe that data literacy is a must-have skill among educators must evaluate how best to create a similarly broad chain of demand.
Can licensure requirements accelerate change?
Variable though they are, such licensure requirements are worth close examination as an acceleration mechanism. To date, there’s been little to no incentive for the sector to produce candidates who can demonstrate a data orientation and are proficient in evidence-based instructional techniques. But if teacher candidates begin to regularly fail licensure requirements, schools of education would have little option but to react and change.
In other words, licensure and certification are potentially powerful incentives for change (what the Data Quality Campaign might call “hammers”). We may be seeing a move toward using such hammers. For instance:
- Some districts are now requiring data literacy among their teachers and administrators. One example is the Tucson Unified School District where candidates for principalships must demonstrate, through the use of a simulated data set, that they can examine and analyze the data, and then produce a school improvement plan.
- Praxis, a series of tests education school graduates must pass as part of the certification process required by many states and professional licensing organizations, is considering the inclusion of data literacy proficiency for teacher candidates.
- The new licensure requirements and professional standards outlined by the Interstate Teacher Assessment and Support Consortium (InTASC) are steeped in data literacy skills.
Experience in other sectors indicates that licensure and certification can drive change at a relatively fast clip. Of particular interest is the Robert Wood John Foundation’s 2011 analysis of the development of the field of palliative medical care. Virtually unknown in 1995, palliative care was formally recognized as a specialty in 2006 and approved for Medicaid reimbursement in 2008. Per RWJF, the inclusion of palliative care questions in examinations administered by the National Board of Medical Examiners (NBME) had a key role in driving change quickly. Certification requirements drove a sectorwide “chain of demand” for knowledge of palliative care, dramatically accelerating the field’s development.
Education data literacy: How we get there
Those who believe that data literacy is a must-have skill among educators must evaluate how best to create a similarly broad chain of demand. In the end, we may not want or need hammers like licensure and certification. Schools of education may well recognize on their own 1) that they must begin to produce data-literate educators, and 2) that current data offerings miss the mark. And there may be routes other than licensure to motivate change. (For instance, we may see the emergence of feeder school districts that, by demanding data-literate educators, push schools of education to respond.) But until we see stronger signs of such a movement, understanding the potential power of licensure and certification requirements makes sense.
Ellen Mandinach is a leading expert in data-driven decision making, focusing on understanding how educators are using data to inform practice. She serves as Senior Research Scientist and Director of the Data for Decisions Initiative at WestEd.
Read Ellen’s related posts, Data literacy vs. assessment literacy and The capacity gap: Grad schools & education data literacy.