Collect Data
Two types of data are needed for the Pathways to Results process to be successful: student characteristics and student outcomes. Teams need to explore the relationships between student characteristics and student outcomes, and they need to consider how their program and process may impact outcomes for subgroups of students.
- Student characteristics. Attributes of students such as gender, race, ethnicity, socioeconomic class, first-generation status, age, and ability can be used to identify subgroups of students whose outcomes can be compared. This is just a sample of the types of attributes that Pathways to Results teams examine, so teams should explore what student groups they want to review data for. As an example, a team could compare grades received by males and females in an important course.
- Student outcomes. Results that are impacted by a program, change, or intervention such as grades, cumulative grade-point average, enrollment status, credits attempted and earned, and certificate and degree attainment.
Based on an institution's data practices, this data may already have been included in the analysis reviewed in Step 3 of the Engagement and Commitment phase. However, it is common for a Pathways to Results team to need to pull additional data for review so it can identify and select an equity gap to focus on for its Pathways to Results project.