With the rising price of college and anxiety about graduates’ job prospects, the employability of graduates is a dominant narrative shaping postsecondary policy and practice around the world. Yet, completion and the acquisition of a credential alone do not guarantee employment, and research on hiring reveals its subjective aspects, particularly when cultural signals of applicants are matched to those of organizations. In this qualitative study of 42 manufacturing firms in the US state of Wisconsin, cultural capital theory is used to investigate the prevalence of hiring as “cultural matching” using thematic and social network methods to analyze interview data. Results indicate that 74% of employers hire for cultural fit, but, contrary to prior research, this matching process is not simply a matter of fitting applicant personalities to monolithic “organizational cultures” or interviewer preferences. Instead, employers match diverse applicant dispositions (e.g., personality, attitude) and competencies (e.g., cognitive, inter-personal, intra-personal) to the personalities of existing staff as well as to industry-specific norms that are dominant within specific departments. The paper explores implications of these findings for college students, faculty, and career advisors, especially in light of the potential for discriminatory practices during the job search and hiring process. © 2019, Springer Nature B.V.

According to Bandura's social cognitive theory, a student's self-efficacy influences his or her academic and career decisions, and his or her performance outcomes; as such, a student's self-efficacy changes with time in response to the student's experiences. Self-efficacy may also vary by academic domain. Differences in STEM self-efficacy have often been reported between men and women. The purpose of this study is to explore the evolution of domain-specific STEM self-efficacy in students in gateway physics and mathematics courses and how academic feedback influences the evolution of these differences with time. Further, this study explored whether gender differences in self-efficacy are consistent across STEM domains and how these differences change in response to academic feedback. Self-efficacy in multiple academic domains (current mathematics/science class, other STEM classes, and intended profession) was assessed at multiple time points with subscales adapted from the Motivated Strategies for Learning Questionnaire. Linear mixed effects modeling was used to understand how academic feedback provided by test scores influenced changes in self-efficacy. Students in all classes expressed different levels of self-efficacy toward different domains with the lowest self-efficacy toward their current class and the highest toward their intended profession. Only the current math/science class self-efficacy of men and women differed significantly, with women expressing lower self-efficacy. The differences in current class self-efficacy were evident very early in the class before substantive class feedback was received. The evolution of self-efficacy within the class and between classes was the same for men and women.

Mathematics learning, engagement, and performance are facilitated by quality interactions within the classroom environment. Researchers studying high-quality interactions in mathematics classrooms must consider adopting multiple methods of data collection so as to capture classroom quality from all perspectives. As such, this longitudinal study examined student, teacher, and observer perspectives of interaction quality in mathematics classrooms and their predictive associations with mathematics outcomes. Data were collected during the fall and spring semesters of the 2015-2016 school year from 1501 students in 150 mathematics classes (n = 499 fifth graders, 523 seventh graders, 479 ninth graders; 51% female; 51% European American, 30% African American, and 19% other ethnic background; 52% qualifying for free/reduced price lunch). Observer and aggregated student reports of interaction quality at the classroom level were moderately correlated with one another, and these reports predicted student mathematics engagement and performance. Individual student reports of interaction quality also predicted math engagement and performance; yet, teacher reports of interaction quality did not align with student or observer perspectives. Furthermore, teacher reports did not predict student mathematics outcomes. Implications for research, practice, and policy are discussed.

Using a national sample of 336 biology Ph.D. students, this study classified students based on their interactions with faculty and peers, and investigated longitudinal changes in their interaction classifications over 3 years. We also examined associations between students' interaction classifications, their demographic backgrounds (e.g., gender, international student status, first-generation status, and underrepresented racial/ethnic minority status), and doctoral outcomes (e.g., sense of belonging, satisfaction with academic development, institutional commitment, and scholarly productivity). The findings revealed that three distinct subgroups existed among the current sample of biology Ph.D. students, with respect to their interactions with their faculty and peers: high interaction with faculty and peers, high interaction with peers only, and low interaction with faculty and peers. However, such patterns of doctoral students' interactions with faculty and peers tended to, in general, be stable over time. In addition, while the differential effects of demographic variables on changes in these interaction patterns were widely founded, such changes were not substantially linked to doctoral student outcomes. Implications for research on doctoral education and socialization theory are discussed.

Conflation of sex and gender is implicated in the development of essentialist thinking, which has been linked to the justification of systems of prejudice in modern society. This exploratory study presents findings from a person randomized control trial conducted with 460 students in 8th-10th grade that investigated the extent to which students conflate sex and gender in their writing about genetics. Students were randomly assigned to one of three short readings that either (1) explained the genetics of sex in plants; (2) explained the genetics of sex in humans; or (3) refuted neuro-genetic essentialism, offering instead a social explanation for why women receive fewer PhDs in science, technology, mathematics, and engineering than men. While previous findings from the authors suggest links between the condition students were assigned to and psychological indicators related to essentialist thinking, no work was done to investigate how students' use of language might implicate cognitive conflation as a possible factor in understanding these results. In this study, student responses to a constructed response writing task given after the reading were analyzed to investigate the use of sex and gender language. Students in all three conditions used both sex and gender language. However, students in the refutational text condition tended to use sex and gender language deliberately in order to explain PhD attainment, while students in the traditional genetics conditions used the terms interchangeably, suggesting subconscious conflation. Students in the genetics of human sex condition were more likely to manifest this conflation than students in the genetics of plant sex condition. Implications for instruction are discussed.

Although it is well known that women have relatively high rates of attrition from STEM occupations in the United States, there is limited empirical research on the views and experiences of female STEM degree-earners that may underlie their commitment to their chosen fields. Utilizing survey data from 229 women completing STEM degrees at two U.S. universities, the present study examines how perceptions of occupational affordances and interactions with others in the field predict their occupational STEM commitment. Additionally, the study employs an intersectional lens to consider whether the patterns of association are different for Asian women and White women. Multivariate regression analyses reveal that although communal goal affordances do not significantly predict women's occupational STEM commitment, agentic goal affordances are a strong predictor of such commitment. Regarding experiences with others in the field, results reveal that classmate interactions are not associated with STEM commitment, whereas positive faculty interactions do significantly predict such commitment. However, further analyses reveal racial differences in these patterns because agentic goal affordances are much weaker predictors of occupational STEM commitment for Asian women than for White women, and results indicate that faculty interactions are significant predictors of STEM commitment only for White women. Thus, our results strongly suggest that the theoretical models of motivation and support that underlie much of the discussion around women in STEM do not similarly apply to women from all racial backgrounds and that more research is needed that considers how both gender and race simultaneously shape STEM engagement and persistence.

[No abstract available]

This paper reviews five ways to increase the effectiveness of instructional video and one way not to use instructional video. People learn better from an instructional video when the onscreen instructor draws graphics on the board while lecturing (dynamic drawing principle), the onscreen instructor shifts eye gaze between the audience and the board while lecturing (gaze guidance principle), the lesson contains prompts to engage in summarizing or explaining the material (generative activity principle), a demonstration is filmed from a first-person perspective (perspective principle), or subtitles are added to a narrated video that contains speech in the learner's second language (subtitle principle). People do not learn better from a multimedia lesson when interesting but extraneous video is added (seductive details principle). Additional work is needed to determine the conditions under which these principles apply and the underlying learning mechanisms.

Self-efficacy has a strong influence on the learning and motivation of science students at the postsecondary level, especially in upper division science classes, which are key to student success in science majors. This empirical mixed methods research study (N = 205) examines the associations between students’ participation in an online preparation course and student self-efficacy in organic chemistry. Qualitative content analysis indicated that students benefited from the online preparatory course in the subsequent organic chemistry course series. The analysis of students’ clickstream data indicated that students with self-efficacy ratings in the top 10th percentile exhibited more frequent and consistent engagement with relevant course materials compared to students in the bottom 10th percentile. Notably, linear regression models indicated that participation in the online preparatory course was associated with higher long-term self-efficacy for first-generation college students. These results suggest that online preparatory courses may benefit some students’ self-efficacy in demanding science courses. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

When solving counting problems, students often struggle with determining what they are trying to count (and thus what problem type they are trying to solve and, ultimately, what formula appropriately applies). There is a need to explore potential interventions to deepen students' understanding of key distinctions between problem types and to differentiate meaningfully between such problems. In this paper, we investigate undergraduate students' understanding of sets of outcomes in the context of elementary Python computer programming. We show that four straightforward program conditional statements seemed to reinforce important conceptual understandings of four canonical combinatorial problem types. We also suggest that the findings in this paper represent one example of a way in which a computational setting may facilitate mathematical learning.