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Despite efforts to attract and maintain diverse students in the science, technology, engineering, and math (STEM) pipeline, issues with attrition from undergraduate STEM majors persist. The aim of this study was to examine how undergraduate science students’ competence beliefs, task values, and perceived costs in science combine into motivational profiles and to consider how such profiles relate to short‐term and long‐term persistence outcomes in STEM. We also examined the relations between underrepresented group membership and profile membership. Using latent profile analysis, we identified three profiles that characterized 600 participants’ motivation during their first semester in college: Moderate All, Very High Competence/Values‐Low Effort Cost, and High Competence/Values‐Moderate Low Costs. The Moderate All profile was associated with the completion of fewer STEM courses and lower STEM grade point averages relative to the other profiles after 1 and 4 years of college. Furthermore, underrepresented minority students were overrepresented in the Moderate All profile. Findings contribute to our understanding of how science competence beliefs, task values, and perceived costs may coexist and what combinations of these variables may be adaptive or deleterious for STEM persistence and achievement.

Expectancy-value theory (Eccles, 2009) posits that students’ relative expectancies and values across domains inform their academic choices. Students should therefore be more likely to choose a STEM major if they have higher expectancies and values in STEM domains compared with other domains. Accordingly, this study aimed to explore how upper secondary school students’ profiles in expectancy-value beliefs in math and English are related to concurrent achievement and university major choice. Data on expectancies and values in math and English were collected from 2,153 German students in their last school year, along with their concurrent math and English achievement and their university major 2 years later. Latent profile analyses revealed four distinct expectancy-value profiles characterized as Low Math/High English, Moderate Math/Moderate English, High Math/Low English, and High Math/High English. Students’ gender, socioeconomic status, and type of school were meaningfully associated with profile membership. For instance, female students were overrepresented in the Low Math/High English profile compared with other profiles. Students in the four profiles also differed in their math and English achievement. These differences were mostly in line with students’ expectancies and values in the respective domain, but some differences suggested that intraindividual cross-domain comparison processes were also at play. Finally, profile membership predicted students’ choice of a STEM major over and above demographic characteristics and achievement. Students in the High Math/Low English profile were most likely to choose a STEM major. These findings support the importance of considering intraindividual comparisons of expectancies and values for students’ achievement-related behavior and choices.

Although online courses are becoming increasingly popular in higher education, evidence is inconclusive regarding whether online students are likely to be as academically successful and motivated as students in face-to-face courses. In this study, we documented online and face-to-face students’ academic motivation and outcomes in community college mathematics courses, and whether differences might vary based on student characteristics (i.e., gender, underrepresented ethnic/racial minority status, first-generation college status, and adult learner status). Over 2,400 developmental mathematics students reported on their math motivation at the beginning (Week 1) and middle (Weeks 3, 5) of the semester. Findings indicated that online students received lower grades and were less likely to pass from their courses than face-to-face students, with online adult learners receiving particularly low final course grades and pass rates. In contrast, online and face-to-face students did not differ on incoming motivation, with subgroup analyses suggesting largely similar patterns of motivation across student groups. Together, findings suggest that online and face-to-face students may differ overall in academic outcomes but not in their motivation or differentially based on student characteristics. Small but significant differences on academic outcomes across modalities (Cohen’s ds = 0.17–0.28) have implications for community college students’ success in online learning environments, particularly for adult learners who are most likely to be faced with competing demands.