Science identity development trajectories in a gateway college chemistry course: Predictors and relations to achievement and STEM pursuit

Abstract

This investigation of undergraduates’ heterogeneous science identity trajectories within a gateway chemistry course identified three latent classes (High and Stable, Moderate and Slightly Increasing, Moderate and Declining) using growth mixture modeling. Underrepresented minorities were more likely to exhibit Moderate-and-Slightly-Increasing science identities versus High-and-Stable patterns. Students with higher perceived competence were more likely classified into the High-and-Stable class compared to the other classes. Students classified into the High-and-Stable class scored significantly higher on the final exam and appeared to be more likely to remain in a STEM major across fall and spring semesters compared to the other two classes. Results suggest that some students’ identities shift within a single semester and supporting science perceived competence before college may support students’ science identity development.

Is it still worth it? Applying expectancy-value theory to investigate the intraindividual motivational process of forming intentions to drop out from university

“…Yet, they found no consistent trend, but rather differences in the strength and valence of students' changes of expectancies and values (cf. Dresel and Grassinger 2013;Kosovich et al 2017;Robinson et al 2019). For some students, success expectation and the overall study value improved, or did not change at all.…”

“…Micro longitudinal studies mirror these trends and revealed that students' motivation changes intraindividually (cf. Kosovich et al 2017;Perez et al 2014;Robinson et al 2019). Yet, they found no consistent trend, but rather differences in the strength and valence of students' changes of expectancies and values (cf.…”

Investigating underrepresented and first‐generation college students' science and math motivational beliefs: A nationally representative study using latent profile analysis

“…For example, Zhao and Bowers (2017) found that African American high school students were less likely to be in the group with positive beliefs towards math. Similarly, Perez, Wormington, et al (2019), along with Robinson et al (2018Robinson et al ( , 2019 found that, among college students, racial and ethnic minorities were more likely to be in those groups with less positive beliefs. In contrast, Dang and Nylund-Gibson (2017) found that the relationship between race and ethnicity and beliefs was different according to students' English learner status.…”

“…Among students enrolled in a computer science course, Shell and Soh (2013) found that women were more likely to be in the "surface learning profile" and not in the profile characterized by deeper engagement with the material. Similarly, in a study of chemistry students, Robinson et al (2018Robinson et al ( , 2019 found that women were more likely to be in the profile of students that began their college careers with middling and stable beliefs about science than in the profile of students with high and strengthening beliefs about science. Two studies reported findings related to students' race or ethnicity, though they grouped all UR racial and ethnic groups into one category.…”

“…First, the composition of our sample-only students who took math and science in their third year of high school-may mean that we have captured students who generally are more positive toward science and math. A second explanation is that Zhao Robinson et al (2018Robinson et al ( , 2019 examined college students and also combined all racially and ethnically UR students into one category. Our findings suggest that grouping UR racial and ethnic minorities into one category likely masks important intragroup variability.…”