2023 ASEE Annual Conference & Exposition

In this abstract, we describe our use of Group Concept Mapping (GCM) to reach consensus for data collection in a multi-site S-STEM Hub research team. Our team represents nine current NSF S-STEM projects united to catalyze co-equitable partnerships between two-year colleges and four-year institutions that empower low-income STEM transfer students. Upon being funded by NSF DUE (Division of Undergraduate Education) in spring 2022, our team recognized that co-equitable institutional partnerships (or lack thereof) could be identified through the collection and analysis of relevant documentation. Subsequent discussions in summer 2022 revealed the seemingly endless range of national, state, regional, and institutional documents that could prove relevant to our effort. To reach consensus systematically and equitably about document selection across our multiple sites, we employed GCM.

GCM has been used across engineering contexts, including biological engineering (Bergeron et al., 2019), engineering entrepreneurship (Bodnar, 2018), and sociotechnical thinking (Foley, 2021). It comprises six steps: (1) Preparation, (2) Generation, (3) Structuring, (4) Analysis, (5) Interpretation, and (6) Usage (https://groupwisdom.com/groupconceptmapping). Specifically:

• In Step 1, Preparation, the group project focus is defined. In our case, our defined focus was identification of documents deemed relevant. We defined ‘relevant’ as documents indicating presence/absence of a co-equitable partnership between institutions serving STEM transfer students.
• In Step 2, Generation, the focus is reframed as prompts to spur brainstorming. To brainstorm all possible relevant documents, team members individually used the GCM software groupwisdomTM (https://groupwisdom.com/). In all, forty-five relevant documents were identified (e.g., transfer course equivalency lists, general education requirements, and regional accrediting agency requirements).
• In Step 3, Structure, team members individually categorized the 45 documents in ways that made sense to them. As part of this step, they also rated each document by its perceived importance in responding to the project’s central research questions.
• In Step 4, Analysis, groupwisdomTM will aggregate participant ratings into a concept map using multidimensional scaling. Ideas (i.e., documents) closer together on the map would be those grouped together more frequently in the sorting. Hierarchical cluster analysis will be used to identify clusters of ideas, or “themes.” Finally, in this step, ratings will be averaged for each idea and theme.
• In Step 5, Interpretation, the resulting concept maps will be interpreted by our team.
• In Step 6, Usage, our team shall (in theory) soon have a systematically and equitably created a list of documents upon which we will agree will best inform our project’s goals.

We acknowledge the use of GCM to reach consensus has not been without challenges. While most project team members are familiar with concept-mapping as a pedagogical approach, many do not have first-hand experience using it for consensus-building. To encourage participation, we recently offered the chance to win a $25.00 Amazon gift card to those who complete the concept-mapping activity (about 20 team members were invited to participate in the concept-mapping activity; invitations were issued based on team members’ interest in being involved in document identification and analyses).

In the final ASEE poster, we will identify the documents we, as a multi-site team, selected based on GCM. By June of 2023, we will also have had a chance to put this section to the test. We will have field experiences, in the form of several two- and four-year institution case study site visits, to assess of how effective GCM was in helping us identify the relevant documents that shone a light on the degree to which co-equitable partnerships were being realized. We also anticipate that we may miss relevant documents, and we will use this hindsight to assess what we perhaps could have done differently in our use of GCM to reach consensus in our multi-site S-STEM Hub research team.