As students and postdoc navigate your program offerings, you may find it useful to track how they participate, how their participation impacts future feelings and decisions, and their long term-career outcomes. Wayne State University, Michigan State University, and the University of California Davis share what they have learned about student, postdocs and alumni data collection and evaluation.
Why you should gather data
- Offers new or prospective students greater transparency with regard to training and career outcomes
- Locates alumni for possible participation in professional development opportunities for students and postdocs
- Identifies career mentors for current doctoral students
- Facilitates continuous program improvements and academic program review
- Places greater focus on student outputs, such as scholarships, conference presentations, internships, etc.
- Supports training grant application needs and accreditation requirements
Types of Data Collection Tools
Integrated databases: Programs often have data stored in disparate locations: University Human Resources, departments, the graduate school, a postdoc office, digital individual development plans, survey systems, and external databases such as LinkedIn. Data structures can integrate content from all of these sources to provide one central location for information on pre- and post-graduate progress. For example, Wayne State University uses Salesforce to merge data from all of these sources. Moreover, they scour the internet for additional information on alumni and email alumni an annual census to ensure they have up-to-date data. Data are used for internal decisions, external reports and showcased on their data dashboard.
Student and Postdoc generated databases: Trainee generated databases include the students and postdocs in data collection and data use. For example, Michigan State University has a web-based tool where students log the time spent on activities, the type of activities, and add notes as to the usefulness of an activity. Activities include formal BEST opportunities as well as any career development efforts a student may initiate on her own. Mentors are invited to also add activities to the student’s log, as are externship providers. A student gets a 360-degree view of his/her development activities, whole programs gather data on how individual experiences relate to career outcomes.
Qualitative Case Studies: Case studies are in-depth interviews with a few program participants. These interviews can be conducted by trained qualitative researchers, program staff, or through participant self-report and capture nuanced information missing from quantitative data. The University of California Davis uses the success case approach to better understand program impact and participant success. Interviews with successful participants can reveal patterns with only a dozen or so cases.
Data collection can be as simple as an annual survey or as involved as an integrated data system or time-intensive case study project. Each school will have different needs, resources, students and cultures, and thus different participant tracking processes. Regardless of your approach, your program and trainees will benefit from data on career outcomes and program strengths.