Which data type is most effective for evaluating academic interventions?

Curriculum-based measurement (CBM) is considered the most effective data type for evaluating academic interventions because it directly assesses a student's academic performance in real-time and in relation to the curriculum being taught. CBM involves frequent, standardized assessments that track student progress in specific academic areas, such as reading or math, over time. This allows educators to identify trends and make data-driven decisions regarding the effectiveness of interventions.

The strength of CBM lies in its ability to provide immediate feedback on how well students are responding to targeted interventions, which is crucial for timely adjustments in instructional strategies. Since CBM is tied to the core curriculum, it ensures that the measurements are relevant and meaningful to the learning objectives being pursued.

In contrast, standardized tests typically assess a broader range of knowledge and skills but are generally administered less frequently. They may not reflect a student’s current academic performance or the immediate effects of specific interventions. Behavioral assessments focus on student behaviors rather than academic skills, which may be important for certain contexts but do not directly measure academic progress. Parent surveys can provide valuable insights into a child's learning environment and social-emotional factors but are less focused on academic outcomes. Thus, while all these data types have their place, CBM stands out for its targeted and ongoing assessment