Introduction by Theresa Jorgensen, University of Texas at Arlington
Featured example by Jake Marszalek, University of Missouri-Kansas City
In the first year of the PROSPECT S-STEM collaboration, we surveyed the participating projects to identify the activities in which they were currently engaged that could be defined as "professional learning communities" (PLCs). From this snapshot of the existing PLCs, we identified opportunities for cross-institutional, project-wide PLCs that would allow for brainstorming and sharing of challenges and solutions for supporting STEM transfer students with financial need.
Starting in Fall 2023 our monthly PROSPECT whole group meetings have incorporated substantial time for subgroups/PLCs established using the topics of interest identified in the PLC survey. These subgroups include participants in STEM disciplines from partners at both associates-granting and bachelors-granting institutions. The subgroups for the fall 2023 semester were focused on:
- Partnerships – Establishing/sustaining/nurturing co-equitable partnerships
- Advising – Coherence & effectiveness in advising students pre & post transfer
- Mentorship – Mentoring S-STEM Scholars (pre- and post-transfer)
- Curriculum – Curriculum coherence/alignment across partnering institutions
- REUs – research experiences for undergraduates with S-STEM students from associates and bachelors-granting institutions
- STEM Identities – problem solving persistence and self-efficacy
The STEM identities group began with discussions about how STEM identities affect success and persistence in STEM programs. Two related constructs, STEM self-concept and STEM self-efficacy, are also likely related to STEM identity. If one or more of these constructs can be increased, success and persistence may be increased, as well. However, these constructs must be measured to know if they have increased. Jake Marszalek, interim associate dean
of education, social work and psychological sciences at the University of Missouri-Kansas City, noticed that, although self-efficacy in specific STEM domains can be defined and measured, the various domain-specific forms of self-efficacy have a common attribute of self-efficacy in problem-solving. Searching the literature, Marszalek found a measure of problem-solving self-efficacy, the Personal Problem-Solving Inventory (PPSI), but it was intended to measure clients in therapy. Therefore, he administered the PPSI to undergraduate engineering students at UMKC and found evidence for the validity of using the scale for engineering students with some modifications (i.e., reducing the length to 18 items). Results were presented at the 2022 American Society of Engineering Education Annual Conference & Exhibition.
The STEM identities group has been discussing gathering evidence for the validity of using the revised PPSI with students in other STEM fields. Once there is evidence of validity, the PPSI could help track students’ evolving self-efficacy in problem-solving. Many student-centered teaching techniques in STEM involve problem-solving, such as inquiry learning, design thinking, and problem-based learning. An unstated goal of such pedagogical practices is to increase student confidence in solving problems (i.e., problem-solving self-efficacy).
A glimpse of how tracking could look can be seen below with the UMKC S-STEM program’s tracking of measures of constructs related to engineering self-efficacy: growth mindset, engineering identity, engineering self-efficacy, and career aspirations in engineering.
Table 1 is a simple summary of descriptive statistics of baseline measures of these constructs for 25 KCURE Fellows (KCURE, Kansas City Urban Renewal Engineering, is the UMKC S-STEM program).
From these statistics, we can discern that the Fellows begin the KCURE program with levels toward the upper end of each scale, particularly for engineering identity and perceived student-centered teaching practices (seemingly good news for our faculty). Table 2 provides a comparison of these baseline measures with end of year measures with the same scales.
In Table 2, we see variable results, some increases and some decreases. To see if the variability is simply due to sampling error, we ran t-tests of each pretest-posttest difference and summarized them in Table 3.
As shown in Table 3, none of the differences was statistically significant, so we cannot rule out that the differences observed in Table 2 are simply due to sampling error. However, some differences appear to be large enough to merit tracking over time because they are large enough to be significant if the sample size is a little larger, such as the increase in observed student-centered teaching practices; the decreases in performance competence, beliefs about intelligence, and self-efficacy in engineering skills; and aspiration toward engineering achievement and education.
The STEM identities group has also discussed adapting a measure of engineering identity for use with STEM students in general, and one recommended by several members was the one used at UMKC, the Engineering Identity Scale, which was presented at ASEE by Allison Godwin, assistant professor of engineering education at Purdue University. Some questions the group is interested in pursuing are:
- How do research experiences influence STEM identity? Leen-Kiat Soh, Charles Bessey professor of computing at the University of Nebraska-Lincoln, shared an interesting Science article addressing this area.
- How stable/dynamic is STEM identity? This would speak to how much we can influence STEM identity, and therefore, how much of a lever it would be for increasing persistence and success in STEM education.
- How should STEM identity be measured? Besides the aforementioned Engineering Identity Scale, Mindi Searls, research assistant professor in the Center for Science, Mathematics, and Computer Education at UNL, shared a single-item measure of STEM identity using a Venn diagram.
- How does STEM identity, or the closely related construct of STEM self-concept, relate to the performance of K-12 STEM teachers?
Click here to view a high-resolution image of Tables 1, 2, and 3.