This report examines data from the Baltimore City Public Schools to identify statistically significant, highly
predictive Early Warning Indicators of non-graduation outcomes, i.e., dropout.
Not exact matches
Also included will be an exploration of the following: • Research - based methodologies and measures for identifying at - risk students • A step - by - step process to create and implement an
Early Warning System • Existing models in use today, reviewing the most
predictive indicators and cut points.