Listening lab – OUR WORK

Student Centered Advising (SCA) Initiative

Kicking off in 2021, the SCA Initiative is a robust inquiry agenda that utilizes mixed methodology to explore lived experiences of undergraduates and academic advisors.  Via focus groups with each of these groups, respectively, project members aim to

  1. Understand the student-advisor relationships
  2. Identify areas of support and growth
  3. Implement infrastructure to better serve the professionals and students at Purdue University
Student Centered Advising (SCA) Initiative Decorative Image

Faculty Job Satisfaction Survey (FJSS)

Purdue first participated in the FJSS, which is a survey hosted by Harvard via their Collaborative on Academic Careers in Higher Education (COACHE).  Operating on a three-year cadence, the FJSS explores different aspects of faculty life at Purdue.  The Lab supports the analysis of response to open-ended questions in this survey, to help senior leaders across Purdue (department heads, associate deans, deans, etc.) gain deeper insights – in connection with the quantitative data – into the unique experiences of Purdue faculty and how best to support their success.

Faculty Job Satisfaction Survey (FJSS) Decorative Image

Purdue University Online (PUO)

The Listening Lab serves as a third-party to support the administration, analysis of, and reporting from the Great Place to Work survey, on an annual basis, to ensure all data remains anonymous between employees and supervisors.  With a focus on qualitative methodology, the Lab provides PUO with reports that synthesize employee engagement by analyzing responses to open-ended survey questions or by conducting focus groups when quantitative insights alone do not clarify changes in satisfaction, belonging, or other survey topics.

Entrance to Engineering Mall, Purdue University, Spring 2015, Campus Scenes

Course Evaluation, Automation

The Listening Lab began collaborating on the analysis of course evaluations in Spring 2025.  The nature of the unstructured data from the open-ended question(s) opens an exciting new door for the Listening Lab – Big [Qualitative] Data.  Future work aims to explore the functionality and implications of utilizing Learning Language Models (LLM) in automating qualitative analysis, given that tens of thousands of responses to these course evaluations are gathered every semester.

Course Evaluation, Automation Decorative Image