Investigating the relationship between participation in the building infrastructure leading to diversity (BUILD) initiative and intent to pursue a science career: A cross-sectional analysis

Research, Science Identity, and Intent to Pursue a Science Career: A BUILD Intervention Evaluation at CSULB

“…2) introduced research participation to the model and the BUILD effect was effectively cut by more than 20% (exp (B) 4.156, p < 0.001) and research participation significantly predicted pursuing a science career (exp (B) 2.491, p < 0.001). As noted, the result of this large drop in the BUILD effect is expected as research participation is a strong predictor of intent to pursue a science and a major component of the BUILD intervention [18,19].…”

“…For example, using propensity score matching to generate a comparison group, Rodenbusch et al [14] found that freshman undergraduate students who participated in undergraduate research were more likely to graduate with a STEM degree than those who did not. Other studies have found that undergraduate research has a powerful effect on underrepresented student retention [15][16][17] and is also associated with increased intent to pursue a science career [18,19]. Furthermore, students involved in undergraduate research have an increased likelihood of enrolling in STEM graduate programs [8,20].…”

“…The higher education literature identifies that students with fewer financial resources face more challenges in completing a STEM degree and going on to graduate school [27,28]. Moreover, students from families with a higher income tend to begin at more selective institutions, which have higher degree attainment rates [19]. Also, the financial status of a student is a powerful predictor for majoring in STEM [19].…”

“…Moreover, students from families with a higher income tend to begin at more selective institutions, which have higher degree attainment rates [19]. Also, the financial status of a student is a powerful predictor for majoring in STEM [19]. Finally, socio-economic status is associated with a host of variables prior to college enrollment, for example, students in secondary school with higher incomes receive necessary assistance with college applications and apply to more colleges [29].…”

“…This survey item asked students if they will pursue a career in science on a 5-point scale. Given the unequal distribution of the answers to the survey item, for the present study, this variable was recoded to 3 points to effectively run the multinomial logistic regression models [19]. The following coding was used for the intent to pursue variable: 1 = Will not pursue a career in science, 2 = Will possibly pursue a career in science, 3 = Will Pursue a career in science.…”