Which model involves reviewing student progress through data collection?

The Data-Driven Decision-Making model is distinguished by its focus on using data to evaluate student progress and inform decision-making processes. This approach emphasizes the systematic collection and analysis of data, which allows educators and counselors to track student performance over time and adjust strategies to better meet students' needs. The core principle of this model is that informed decisions, grounded in empirical evidence, are more effective in promoting student outcomes. By continuously reviewing data on academic performance, behavioral trends, and other relevant metrics, school counselors can identify areas for improvement, target interventions effectively, and ultimately enhance the educational experience for students.

Other models mentioned may focus on assessment or evaluation but do not specifically emphasize the role of data analysis in decision-making to the same extent as this model does. For instance, while the Comprehensive Assessment model might involve various types of assessments, it does not solely center on the collection and review of data as a basis for ongoing decisions. Similarly, the Student Success model typically focuses on the holistic support of student needs, and the Outcome Evaluation model may concentrate on measuring results after interventions rather than the ongoing process of data collection and analysis that characterizes the Data-Driven Decision-Making model.