Many datasets can be organized into natural hierarchies. Consider: spatial entities, such as counties, states, and countries; command structures for businesses and governments; software packages and phylogenetic trees. Even for data lacking apparent hierarchy, statistical methods such as k-means clustering may be applied to organize data empirically. Special visualization techniques exist to leverage hierarchical structure, allowing multiscale inferences of both individual elements and global trends.
The CSDE is also providing sample SLOs represent the best thinking of educators in the field at this time. As part of the SLO process, evaluators and administrators have an opportunity to discuss the SLOs as well as the supporting rationale for each SLO. As this process continues to evolve, we will add to these samples throughout the school year. We continue our work with the Northeast Comprehensive Center to develop SLO tools and resources for administrators and evaluators to use as part of a district-wide process and to focus discussions on improving instructional leadership and learning for all sample SLOs include annotations which are provided to encourage administrators and their evaluators to approach setting SLOs in a thoughtful manner.