Keynotes

Professor Dr. Ursula Kessels, Free University Berlin, Germany

Being a good girl can backfire: How perceptions of female students' ways of learning might block their route to STEM

Gender stereotypes about students and their ways of learning indicate that girls are perceived as good, compliant and hardworking at school, while boys are seen as lazy and more troublesome. In my talk, I will discuss some consequences of these stereotypes. I will first look at ascriptions resulting from students’ overall (dis-) engagement at school, highlighting how disruptive or compliant student behaviors can trigger specific attributions for academic success and failure. More specifically, these gender stereotypes also have consequences regarding students’ perceived suitability for STEM. The stereotypes about female ways of learning and succeeding at school on the one hand, and the image of STEM on the other hand, should lead to not only female students’ own perceived lack of fit with STEM but also to biased perceptions by others. Extending existing research, I will discuss how negative stereotypes about girls in STEM might not always lead to more negative, but can, on the contrary, lead to more positive evaluations.

 

Professor Dr. Ingrid Schoon, University College London, UK

Gender Differences in Aspirations and Attainment. A life course Perspective

Major strides have been made regarding educational and occupational opportunities for women. Yet women continue to be paid less than men, even for doing the same task. Furthermore, men and women tend to pursue different subject courses and occupations, with women being under-represented in certain fields, especially science, technology, engineering and maths. A number of explanations for persisting gender inequalities have been put forward, including gender essentialism, socialisation experiences and the choices men and women make, as well as downright discrimination. In this paper I present an integrative developmental approach model of motivated choice and behaviour and take a complex systems view to argue that for a better understanding of and response to persisting gender inequalities one has to take into account multiple influences that occur over the life course. Early experiences in the family and school contexts cumulate to shape self-concepts, choices and behaviours which in turn become part of the gendered social world. Gender differences become apparent in early childhood and are re-created through everyday social relations with significant others as well as by interactions with the wider social context. Small biasing effects can accumulate across different situations and over time, leading to distinct behavioural pathways for men and women who might have similar capabilities and social backgrounds. To instigate change in perceptions and behaviour it is important to raise awareness of existing inequalities, and to foster equality-promoting policies and institutional reform.

 

Professor Dr. Gail Jones, NC State University, USA

Mapping Science Career Aspirations: Intersectionality Factors

Researchers are beginning to unravel the myriad of factors that influence STEM interests and career aspirations. In this presentation, we explore the intersectionality factors that contribute to science career aspirations. These factors include gender identity, racial/ethnic identity, location (urban, rural, suburban), access to science-related tools at home, and access to an adult who works in a science job, does science hobbies, or talks about science. Using structural equation modeling we examined relationships among the factors. The results of this study, along with those of other studies, suggest that science capital factors (knowing people in science, having access to science resources, and having experiences in science) contribute to individuals’ perceptions of themselves as learners of science, their science identity, and their self-efficacy for being successful in science in the future. These findings document important ways in which youth access and exposure to science experiences, tools and scientists lays the groundwork for science motivation and ultimately to valuing future engagement with science.

 

Professor Dr. Jacquelynne S. Eccles, University of California, Irvine, USA

Shifting gendered pathways into and out of STEM

Eccles has spent much of the last 50 years thinking about and studying gendered engagement in STEM  and other educational and occupational options. She has overseen two very large and longitudinal studies and one major evaluation of a utility value intervention in college physics and chemistry and worked with a graduate student on a role model based UTube intervention in college intervention.  Now she is approaching retirement and has begun reflecting on what she has learned from these experiences. She would like to share these reflection with you in an informal Q & A type interaction.

Distinguished Talks

Professor Dr. Judith Harackiewicz, University of Wisconsin-Madison, USA

A Prosocial Value Intervention in Gateway STEM Courses: Implications for Performance and Persistence

College students, especially first-generation students and women desire courses and careers that emphasize prosocial values. However, despite their relevance for public health, the planet, and the human condition, STEM courses often emphasize technical knowledge at the expense of real-world applications. We developed a prosocial utility-value intervention (UVI) in which students were asked to reflect on the prosocial value of science course content, with a focus on reducing performance gaps between continuing generation (CG) and first-generation (FG) college students (there are no gender differences in performance), and promoting persistence in the STEM pipeline. In Study 1, we piloted two versions of a prosocial UVI in an introductory biology class to test whether we could encourage students to write about the prosocial value of course content (N = 282). In Study 2, we tested a version of the UVI that combines personal and prosocial values, using a randomized controlled trial in an introductory chemistry course (N = 2,679), and examined effects on course performance. Results suggest that the prosocial UVI may be particularly effective in promoting motivation and performance for first-generation college students, especially those who are more confident that they can perform well in the class, reflecting a classic expectancy-value interaction. Mediation analyses suggest that this intervention worked by promoting engagement and interest in chemistry and also by fostering students’ beliefs that their instructor values the applications of chemistry for solving real-world problems.

How might these effects carry forward? Any boost in performance in a gateway class, especially if taken the first or second year of college, can have significant consequences. Performance in gateway courses can send a strong signal to students of their potential to succeed in the field, and the confidence and motivation that higher grades in these courses can stimulate may embolden them to proceed in the field. If a UVI helps to develop students’ interest in a field, this may motivate them to choose additional courses, a major, or a career in that field.

In our most recent work, we are following these students through graduation, with interviews and institutional data. We are examining persistence in STEM and finding some promising effects of our prosocial intervention. Of particular interest is that although we did not find intervention effects for women on performance, we are finding preliminary evidence of intervention effects on persistence for women, indicating the importance of evaluating interventions over time.

 

Professor Dr. Katariina Salmela-Aro, University of Helsinki, Finland

Gendered pathways to STEM: variable and person-oriented approach

Drawing on Eccles expectancy-value model of achievement-related choices using both person- and variable-oriented approach my aim to (1) identify both elementary and high school students’ self-concept and intrinsic value profiles across the subjects of Finnish language, mathematics and science and to examine (2) the stability and change of these motivational profiles, (3) gender differences in profile membership as well as (4) the relation to students’ STEM (Science, Technology, Engineering and Mathematics) occupational aspirations and attainment.

Based on data from 383 Finnish elementary school students (56.7% girls) three profiles were identified: High motivation across all three subjects, low motivation across all subjects, and a math-motivated profile with low motivation in the other two subjects. Latent transition analyses revealed moderate stability, particularly in the high motivation profile. Girls were less likely to be and to remain in the math-motivated profile, but they were more likely than boys to remain in the high motivation profile. The math-motivated profile transition pattern was associated with students’ STEM occupational aspirations. Second, during high school while 849 adolescents’ average task values in different domains remained stable, three differential joint task value trajectories emerged across domains. Individual changes in one domain shaped task values in other domains to form unique relative task value hierarchies within subgroups that impacted long-term STEM aspirations and participation. Gender differences in STV trajectory profile distributions partially explained the overall underrepresentation of women in STEM fields during high school on STEM aspirations at four years postsecondary school and STEM participation at six years postsecondary school.

Finally, I will introduce G-versity Innovative Marie Curie Training network focusing on gender diversity both in educational and occupational pathways.

 

Professor Dr. Sarah Hofer, Ludwig-Maximilians-Universität München, Germany

It's about the journey, not (only) the destination - Gender-specific relations between perceived self-determination, engagement, and math performance

Although it is vital to be informed about mean-level similarities and differences between girls’ and boys’ STEM outcomes, it is equally important, both for researchers and practitioners, to know more about the nature of the relations between central constructs in the context of STEM education and whether these relations differ as a function of individual characteristics, such as gender. In a recent study, we hence investigated gender-specific relations between perceived self-determination, engagement, and performance in school mathematics.

Math is one of the STEM subjects without consistent gender differences in terms of performance – at the same time, female students regularly indicate less positive attitudes and lower levels of motivation than male students. Analyzing gender-specific pathways to math performance might help to better understand this discrepancy. We hence administered an online survey in a sample of N=221 7th-Grade students from Germany (Mage=12.84 years, SDage=0.55, Nfemales=115) to assess perceived competence and autonomy support, social relatedness, as well as cognitive and behavioral engagement in math classes. Math performance and sustained attention, which was included to control for the basic cognitive ability to concentrate during math lessons, were measured by means of online tests. While we also looked at mean differences and bivariate correlations, gender-specific relations were examined with multiple group path analyses. As expected, girls and boys didn’t differ in their math performance. The only significant gender differences on the mean-level were found for behavioral engagement with higher manifestations among girls and perceived competence support with higher manifestations among boys. Perceived autonomy support predicted cognitive and behavioral engagement for both girls and boys without a direct effect on math performance.Yet, it seems to indirectly influence math performance via cognitive engagement for female students and via behavioral engagement for male students. While, only for boys, sustained attention was as a significant positive predictor, only for girls, perceived competence support in the math classroom was a significant negative predictor of math performance. Not only did girls report experiencing competence support less frequently than boys, but they also seem to receive this kind of attention more often in response to low performance. Math teachers may therefore tend to neglect supporting female students with high cognitive potential, (implicitly) complying with gender-math stereotypes. Considering the influence of behavioral engagement on boys’ math performance, distraction-free and quiet learning environments might be particularly helpful to increase male students’ perseverance and diligence, and thus their performance.

 

Professor Dr. Burkhard Gniewosz, Paris Lodron University Salzburg, Austria

Potentials of Contemporary Statistical Methods for Research on Gender & STEM Motivation

The Gender & STEM network aims „to interrogate personal and contextual influences towards, or away from, diverse STEM pathways across stages and settings. The specific theme of Sticking with STEM: Who comes, who stays, who goes, and why?“. Given adequate data sets and methods, it is possible to answer questions such as: Do boys and girls differ in their motivational trajectories? Are some trajectories more likely for girls: which trajectories?, for all girls?, which girls?, under what conditions? Do all predictors of STEM motivation changes work in the same way for boys and girls?: for all girls?, which girls?, under what conditions?

The above-mentioned aims call for longitudinal methods. Therefore, the changes, for instance of STEM motivation, have to be adequately modelled and predicted, for example by Growth Curve Modelling (McArdle, 2008), Random Intercept Cross-lagged Models (Hamaker, Kuiper, & Grasman, 2015), Latent Change Modelling (McArdle, 2009; Steyer, Partchev, & Shanahan, 2000) etc. Adding a multi-level perspective (Raudenbush, Bryk, & Congdon, 2005), it is possible to add predictors of the changes on different levels, in all of these models.

Applying a person-centered perspective (Howard & Hoffman, 2017), it is possible to model differential prediction patterns in mixture analyses (Berlin, Parra, & Williams, 2013). A certain (set of) predictor(s) might only be valid for a certain subgroup of people – not all. Moreover, the change trajectories do not necessarily be the same for all study participants. Furthermore, in longitudinal mixture analyses, these change patterns can be identified and (differentially) predicted.

This talk will give an overview of state-of-the-art methods to address the above mentioned research questions and shortly explain the potentials but also the prerequisites, based on empirical examples from gender and STEM research.

 

PD Dr. Hanna Gaspard; Dr. Cora Parisius; Prof. Dr. Benjamin Nagengast; Prof. Dr. Ulrich Trautwein, Technische Universität Dortmund, Germany

Promoting Motivation in Mathematics: Effectiveness and Student Responsiveness in a Cluster-randomized Trial

Many adolescents do not see the relevance of mathematics for their lives, and math utility value has been found to decrease throughout secondary school (e.g., Gaspard et al., 2017). Relevance interventions have shown a great potential to foster students’ motivation and achievement in math and sciences (Lazowski & Hulleman, 2016; Rosenzweig & Wigfield, 2016). Yet, further research is warranted to examine how these interventions can be successfully implemented. We conducted a cluster-randomized trial in ninth-grade math classrooms to test the effectiveness of a relevance intervention, which was previously shown to be efficacious when implemented by researchers (Brisson et al., 2017; Gaspard et al., 2015), under conditions closer to educational practice.

The 78 participating classrooms (N = 1,744 students) were randomly assigned to one of two intervention conditions or a waitlist control condition. The 90-min intervention consisted of an instructor-led psychoeducational presentation and an individual task that asked students to rate six quotes from young adults referring to the relevance of mathematics. The intervention was implemented by master’s students or the regular math teachers. Intervention effects were evaluated using self-reports, teacher ratings, and achievement tests 4 weeks and 3 months after the intervention. Compared with the control condition, both intervention conditions showed similar positive effects on utility value. Unexpectedly, students in both intervention conditions also reported higher perceived cost compared with students in the control condition after the intervention. When implemented by master’s students, additional effects on students’ growth mindsets and a standardized achievement test could be observed. Overall, the intervention thus showed mixed effects. Future research should therefore continue to examine the conditions under which relevance interventions work in practice.

To better understand how intervention materials can be tailored to individual students, we also investigated student responsiveness to the intervention tasks used in both intervention conditions. Students’ ratings of the personal relevance of the six quotes were used as indicators of student responsiveness. A broad set of student characteristics was considered as predictors, including gender, migration background, prior motivation, STEM career aspirations, and vocational interests. Student characteristics predicted students’ ratings of the personal relevance of the different quotes in line with expectations. Furthermore, a higher personal relevance across the six quotes was associated with positive changes in perceived utility value in the two intervention conditions. These results yield important knowledge for personalizing the intervention materials to individual students and contribute to identifying the processes through which relevance interventions work.

 

Dr. Jiesi Guo, Australian Catholic University

The Educational Gender-Equality Paradox in STEM: Fact or Artifact?

The Educational gender-equality paradoxes in STEM posit that countries with high levels of gender equality have larger gender gaps in STEM performance, motivation, and enrolment in secondary and tertiary education. These paradoxical results suggest that efforts to improve gender equality might be counterproductive. Recently, I conducted a series of studies and provided critiques and replications to demonstrate that this so-called gender-paradox is an artifact of three fundamental flaws: 1) the linear relationship was driven by a small set of outlier countries; 2) using the relative-score between-country (absolute) measures of gender equality rather than true gender-gap measures—within-country (relative) female-male differences; 3) using composite gender-equality indices rather than domain-specific (i.e., education-related) gender-gap measures. Furthermore, at the student level, the relative-score approach that captures within-person relative strength across subject domains is useful to explain gender differences in academic motivation, aspirations, and behavioral choices in STEM. However, there are some heoretical and methodological issues relating to this approach in previous studies. In this talk, I will also illustrate how to use the relative-score approach correctly.

 

PD Dr. habil. Yves Jeanrenaud, Ludwig-Maximilians-Universität München, Germany

Women in STEM. Why not? Barriers and Obstacles on Academic STEM Carriers With Regards to Gender and Family of Origin

In Germany, the proportion of women in STEM subjects, remains low and is only slowly increasing (cf. Destatis, 2021a). This is even more striking for especially in engineering and computer science courses, which are central to mechanical and plant engineering, a key sector to the German industry (cf. Bundesagentur für Arbeit, 2019; Destatis, 2021a; Jeanrenaud, 2020, pp. 8–23). While the proportion of women in the first semester of the relevant subjects has risen several percentage points over the past decade, there has also been an increase in the proportion of women passing university examinations in these subjects (Destatis, 2021b). But women engineers in mechanical and plant engineering continue to be underrepresented even compared to STEM subjects as a whole (Jeanrenaud, 2021, pp. 8–12).

As studies suggest, the underrepresentation of women engineers in mechanical and plant engineering is also due to both cultural and structural causes (for an overlook, see Jeanrenaud, 2020), it is obvious to look at individual career and life histories of women in STEM as well as to link them to social and organisational contexts.

This distinguished talk seeks to give an overview of research on the subject of women STEM in Germany and beyond whilst focussing on study choice behaviour and the families of origin as two major play fields of social inequality and illuminating their role in the underrepresentation of women in German STEM professions.