Article #1: Why teachers must be data experts - 1/28/09

Standarized testing is only one type of data and can be somewhat limiting. There are many forms of data that are often much more relevant and informative to the classroom setting. Such data collection, although not numerical in nature can be just as effective, if not moreso. Science and math teachers, such as myself, generally and traditonally see only numerical date as valid and significant. "In teaching, relationships and perceptions matter as much as curriculum and practice"(Morrison, 2008). This approach allows educators to target their instruction on a global scale and also stimulates differentiation by virtue of targeting on a individual or subpopulation scale. The goal here is to inform the educator and to aid in adapting instruction, not to drive instruction. If resistance to data generated by standarized tests is evident in teachers it is because they have not bought into the idea that all data can be useful to create the overall picture. It is also perceived, at times, that standarized data must drive instruction - "teach to the test". In reality such data can be used successfully to guide student learning and instruction. Morrison points out that to have "buyin" by teachers, both the purpose and relevance of such data must be made clear - it is more than just a "snapahot". In additon, the data should be shared and interpreted amongst colleagues with a similar discipline - so all can benefit from what is revealed. Typically such data as Morrison points out is treated as a separate entity - a stand alond test. "The problem is that we frame data as an entity teachers need to meet and engage with, rather than as information that arises organically out of teachers work with learners"(Morrison, 2008). If both forms of data are used together they complement instruction and will most benefit student learning.