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How interest fit relates to STEM study choice: Female students fit their choices better
Abstract
STEM (Science, Technology, Engineering and Mathematics) enrolments in higher education are declining while the STEM gender gap of female underrepresentation seems to widen. The present study addresses both issues by exploring how the fit between a student's vocational interests and the STEM field contributes to a (non-) STEM study choice. Data was collected in the unique setting of an open access and low cost higher education system, which allowed for study of vocational interests without unwanted influence of admission conditions. Specifically, we assessed the interest fit of N = 9162 first-year Belgian university students with (1) the STEM field (i.e., STEM fit) and (2) their specific program of choice (i.e., program fit). Results indicated STEM fit indeed predicted STEM study choice, with a stronger effect in female students. Results also indicated that female students showed a better specific program fit. In order to promote student STEM enrolment and address the gender gap, the present study therefore advocates a gender-specific approach to attract more students with appropriate interest profiles.
... While many barriers and factors contribute to women's disparate pursuit of engineering (Kanny et al., 2014), goal congruity theory highlights that a key underlying factor is the perceived disconnect between engineering (which is stereotypically seen as agentic [self-oriented]; National Academy of Engineering, 2008;Su & Rounds, 2015) and women's values (which are more, though not exclusively, communal [other-oriented]; Diekman et al.,, 2011Diekman et al.,, , 2015Diekman et al.,, , 2020Eagly & Wood, 1999;Eagly, et al., 2020;Schmader, 2023;Schwartz, et al., 2005). Because individuals are driven to seek environments that allow them to manifest their values behaviorally, the perceived disconnect reduces women's pursuit of engineering both academically and professionally (Bonilla et al., 2023;Diekman et al., 2010Diekman et al., , 2011Hill et al., 2010;Schelfhout et al., 2021;Su et al., 2009;Webb et al., 2002). ...
... Empirical studies have produced work consistent with the propositions outlined by GCT, finding that women's preferences, manifested as communal v. agentic values, are key drivers in decisions related to academic and vocational pursuits (Allen & Robbins, 2008;Bruch & Krieshok, 1981;Holland, 1997;Le & Robbins, 2016;Le et al., 2014;Leuwerke et al., 2004;Porter & Umbach, 2006;Rounds & Tracey, 1990;Schelfhout et al., 2021). Additionally, work has found that women are more likely to prefer careers that have a clear social purpose (Eccles, 2007;Jozefowicz et al., 1993;Lubinski & Benbow, 2006;Margolis et al., 1999). ...
... Additionally, work has found that women are more likely to prefer careers that have a clear social purpose (Eccles, 2007;Jozefowicz et al., 1993;Lubinski & Benbow, 2006;Margolis et al., 1999). As such, scholars have come to agree that men and women's sizable differences in values may be one of the most important psychological mechanisms leading to gendered academic and career choices, including in STEM fields such as engineering (Brown et al., 2018;Ceci et al., 2009;Lubinski & Benbow, 1992;Schelfhout et al., 2021;Su et al., 2009). ...
Background
Women are underrepresented in the field of engineering within academic and professional settings. Based upon premises outlined by social role theory and goal congruity theory, a key factor that contributes to this underrepresentation is a gendered societal belief that there is a disconnect between engineering (seen as more agentic, or self-oriented) and women’s values and abilities (which are believed to be more communal, or other-oriented). While there is evidence that this perceived disconnect influences women’s pursuit of engineering, the extent to which an intervention could realistically counter these perceptions at key points along the engineering pathway has not been explored. Across two studies, we examine the impact of a communal-based intervention (in which we frame engineering majors and careers in more, though not exclusively, communally oriented ways) on women’s engineering-related attitudes and behavioral intentions at two points along the academic-employment pathway: women’s major selection and women’s job selection.
Results
Study 1 found that women with undeclared majors had more positive attitudes (confidence and interest) towards engineering majors when engineering major descriptions were framed as more communal versus more agentic. However, there was no impact on their behavioral intentions to pursue the major. Study 2 found that women with engineering majors were more confident in their ability to be successful in a job role and were more likely to apply when the job role was framed as more communal as compared to more agentic. However, they did not indicate greater interest in the job role.
Conclusions
Testing this intervention on relevant populations advances the literature by providing greater evidence for the potential of such an intervention to meaningfully address women’s underrepresentation at multiple points along the engineering pathway. Furthermore, this study provides evidence that a messaging-based intervention is impactful with a realistic representation of engineering as both an agentic and communally oriented field, which ensures that the retention of those attracted to the field is not negatively impacted by idealistic messaging. While addressing women’s pursuit of engineering is important, work must continue to seek ways to always improve women’s experience in engineering contexts as well.
... Besides gender bias in predictions of academic achievement, there have also been reports of gender bias in study interest orientation tools. Indeed, studies have shown that there are not only substantial gender differences in predictor values, but also in the study choice process (Schelfhout et al., 2021;Stoet & Geary, 2020). For instance, Schelfhout et al. (2021) reported that females (vs. ...
... Indeed, studies have shown that there are not only substantial gender differences in predictor values, but also in the study choice process (Schelfhout et al., 2021;Stoet & Geary, 2020). For instance, Schelfhout et al. (2021) reported that females (vs. males) have more explicit knowledge about their profile of vocational interests and they also use this knowledge more explicitly. ...
... males) have more explicit knowledge about their profile of vocational interests and they also use this knowledge more explicitly. Furthermore, research has shown that study choices for the field of science, technology, engineering, and mathematics (STEM) are less determined by STEM preparation (e.g., knowledge of mathematics) for females, as they evaluate their cognitive capabilities much more modestly than men (Buchmann et al., 2008;Nix et al., 2015;Schelfhout et al., 2021). In sum, gender affects to what extent various cognitive and affective factors play a role in the study choice process. ...
Predictive models of academic achievement are used in various (often high stakes) applications, including selection and study orientation procedures for higher education. Considering the far-reaching consequences of their outcomes, these models should show as little bias for irrelevant factors as possible. While numerous studies have researched the impact of gender on the isolated individual predictors of academic achievement, no studies yet have explored how gender affects program-specific prediction models of academic achievement. As such, the present study examined whether prediction models exhibit gender differences in the accuracy of their predictions, and how such differences relate to the gender balance within a study program. Besides that, we developed gender-specific prediction models of academic achievement in order to examine how these models differ in terms of which predictors are included, and whether they make more accurate predictions. Data was examined from a large sample of first year students across 16 programs in an open access higher education system (N = 5,016). Results revealed interactions between gender and several predictors of academic achievement. While the models exhibited little difference in the accuracy of their predictions for male and female students, analyses showed that using gender-specific models substantially improved our predictions. We also found that male and female models of academic achievement differ greatly in terms of the predictors included in their composition, irrespective of the gender balance in a study program.
... This finding is surprising as it appears to contradict some previous studies that reported no advantage for female students in entering popular advantageous majors [47]. Some studies suggest that differences in academic performance may be an important factor contributing to gender disparities in major choices [48]. In this study, even after controlling for academic performance and other potentially influencing variables, the analysis results robustly support the significant tendency of female students to choose popular applied majors over male students. ...
... Shao et al. pointed out various obstacles hindering female students from choosing high-paying surgical specialties when analyzing the likelihood of female students selecting such specialties. These obstacles include excessive physical demands, discrimination in recruitment, unfriendly work environments for women, and difficulties in balancing family responsibilities [48]. From the perspective of maintaining social gender segregation, both males and females, influenced by external factors and driven by internalized different values and potential social discrimination, make distinct decisions in education and major choices, tending towards the professions society expects of them [49]. ...
Higher education attainment is a focus of gender differences research. However, little is known about differences in university students’ major choices at the same level of higher education in China’s education hierarchy. Based on a web survey of 1164 undergraduate students in China’s broad enrollment context, this study uses Wenjuanxing to collect information by posting questionnaires on social media platforms and analyzes the impact of gender differences on the major choices of finance and economics undergraduates by using the Linear Discriminant Model (LDM). Moreover, this study explores the differential impact of income level, urban–rural settings, and regional differences on university students’ major choices. This study finds that female students are approximately 2.62 times more likely than male students to choose applied majors (such as accounting, financial management, auditing, international business, and so on), a gap that is more pronounced in high-income families and Eastern regions. In addition, in rural areas, female students have a higher probability of choosing applied majors than male students. These findings indicate that in China’s broad discipline enrollment model, gender differences still significantly affect students’ major choices, and female students are more likely to enter applied majors than their male counterparts.
... While there is a lack of person-centered research, this study does contribute to previous research that aimed at investigating career choices using vocational interests, especially regarding fields with unbalanced gender distributions (e.g., [19,[44][45][46][47][48]). ...
... Thus, regarding the topic of the special issue "Sticking with STEM: Who Comes, Who Stays, Who Goes, and Why?" we can conclude that female students in STEM-L, although studying a subject with a male sextype according to Gottfredson [6,12,13], rather seem to estimate this sextype as inappropriate and turn away towards occupations with a more appropriate sextype. Previous studies have made various conclusions which suggest that a good fit in STEM is particularly relevant (e.g., [19,[44][45][46][47][48]), which leads us to hypothesize that STEM-L studies might just be seen as a vehicle for female students to come to a more sex-balanced profession. ...
Various factors may be important while individuals develop vocational aspirations. Although occupations that fit one’s personal interests appear to be attractive, contextual factors may repel groups, such as young girls, to develop towards areas such as STEM. Especially, the sextype of STEM occupations, that is often considered as male, could limit STEM career choice of young girls. This study investigates career profiles of n = 9277 German university freshmen based on interests, prestige, and sextype. Eleven latent profiles were found. Five profiles can be characterized by their prestige levels and two further by their sextype. Certain profiles are significantly associated with study outcomes and study satisfaction, which allows to identify at-risk profiles. Of note, especially female students in STEM subjects with a low proportion of females distributed widely across the 11 profiles. The implications of this study suggest that career choice profiles according to Gottfredson’s framework can help to identify at-risk students.
... Most obviously, future research is needed that evaluates the generalizability of our findings by comparing our results to those obtained in different educational settings where (1) study programs are composed in a different manner, (2) a different measure is used to assess (future) students' interest profiles and/or (3) student performance (i.e., first year GPA) is assessed differently, for instance through (future) degree attainment. Studies towards degree attainment seem especially warranted, as a degree forms the primary gateway to the work field (Schelfhout et al., 2021b). ...
... The education system in which the project is embedded is characterized by a relatively low entry cost (i.e., a maximal tuition fee of about € 1,000 or $ 1,170) and an open access policy (i.e., no admission tests or entry level GPA requirements). Such an environment also provides an excellent opportunity to investigate the influence of vocational interests on study choice and academic achievement(Schelfhout et al., 2021b), in the absence of additional (financial and achievement-related) requirements.For the present prospective study, the dataset features interest and performance data from a large overall sample of N = 4,407 first year generation (i.e., first registration) students (59% female, with a mean age of M = 18.16, SD = 0.82 and a median age of Mdn = 18, which covered 88% of the sample), distributed across ten faculties and 22 bachelor programs of a Belgian university that is ranked in the top 100 of the Academic Ranking of World Universities (ARWU, formerly known as the Shanghai Ranking, see also https://www.shanghairanking.com/rankings).At the start the academic year 2018-2019 first-year students were strongly advised through multiple channels (e.g., lectors, emails and messages distributed through online student platforms) to fill out an online RIASEC questionnaire, specifically designed for the transition towards higher education(Fonteyne et al., 2017). ...
Polynomial regression is a proven method to calculate person-environment (PE) interest fit between the RIASEC (realistic, investigative, artistic, social, enterprising and conventional) interests of a student and the RIASEC profile of a study program. The method has shown much larger effects of PE interest fit on academic achievement than earlier approaches in literature. However, the polynomial regression method in its current form only focuses on establishing the regressed interest fit (RIF) of a population of students with their study environments, in order to observe how large the general impact of PE interest fit can become on academic achievement. The present study (N = 4407 across n = 22 study programs) further validates this method towards new applications by theoretically deriving two measures of RIF that only affect a single environment like a study program. Analyses show that the use of RIF for a single study environment results in an even stronger positive relation between PE interest fit and academic achievement of r = 0.36, compared to r = 0.25 for the original polynomial regression method. Analyses also show that RIF for one environment can be used to generate interpretable and reliable RIASEC environment profiles. In sum, RIF for a single (study) environment is a promising operationalization of PE interest fit which facilitate both empirical research as well as the practical application of interest fit in counseling settings.
... In vocational psychology interests represent trait-like preferences that guide individuals towards their (work) environments (Armstrong et al., 2011;Su et al., 2019). Vocational interests (VI) demonstrate a predictive efficiency in career and academic outcomes (Hoff et al., 2019;Schelfhout et al., 2021;Tracey et al., 2012). Holland's (1997) Theory of vocational personalities and work environments proposes the classification of six distinct interest types referred to as the RIASEC model: Realistic (R) interests favor mechanical, manual, or outdoor activities, Investigative (I) involve a preference for research, Artistic (A) for the expression and an appreciation of arts, Social (S) for working with and helping others, Enterprising (E) for leadership, negotiation, and self-management, while Conventional (C) interests involve accurate problem solving by adhering to rules. ...
... We build upon the personenvironment fit assumption and draw upon Holland's theory which states that individuals seek out and construct permanent social environments that are in congruence with their own characteristics (e.g. VI; Hoff et al., 2021;Schelfhout et al., 2021). Additionally, we follow the evolutionary perspective (Buss, 1984;Laland et al., 2001;Thiessen & Gregg, 1980), which states that having a similar partner is beneficial for the adaptation of the present and future generations. ...
The present study links the person‐environment fit theory of vocational interests (VI) with the research on the selection of romantic partners. Empirically, we explore the assortment for VI in 215 heterosexual romantic partners. Using both the variable‐centered (VCA) and couple‐centered (CCA) approaches, we test the hypotheses on positive versus negative assortment, initial assortment versus convergence, and active assortment versus social homogamy. A modest to moderate positive assortment was found for Realistic, Investigative, Artistic, and Social interests but not Conventional interests, whereas evidence of couple similarity in Enterprising interests was less consistent. A moderate level of positive assortment was identified in couples when full interest profiles were evaluated. The results indicate an initial and active assortment rather than convergence or social homogamy effects. The analysis also shows that the assortment for interests represents an independent preference that cannot be easily seen as a by‐product of the assortment in the five‐factor personality traits. These findings highlight the importance of VI in the active selection of romantic partners. We discuss implications for future research and practice.
... Consequently, previous empirical research on the science domain has found that science interest was a stronger predictor of science aspirations for women than for men, while science self-concept mattered less for women than for men (Kang et al., 2021). Female students in STEM subjects in higher education also tend to report a higher fit between the content of their program and their interests than male students (Schelfhout et al., 2021). ...
The use of information and communication technologies (ICT) is now an integral part of many occupational task profiles. Therefore, like mathematics and science, ICT represent an important content domain that adolescents may consider in their early vocational choices. Drawing on Eccles’ situated expectancy value theory and related theories, we hypothesize that adolescents’ ICT interest and self-concept should influence their vocational choices with respect to the intensity of ICT use in future occupations. Using longitudinal data from 1,964 Swiss adolescents transitioning into firm-based vocational education and training, we find strongly gendered patterns. Higher ICT interest predicts selection into occupations involving greater intensity of both basic and advanced ICT use, but only for girls. A more positive ICT self-concept is a significant predictor of greater occupational ICT use in future occupations only for boys, and this association is driven mainly by boys choosing careers as ICT specialists. Girls’ lower average ICT interest and their less positive ICT self-concepts explain almost half of the gender differences in the intensity of advanced ICT use. These findings emphasize that ICT are an important content domain of adolescents’ vocational choices today and highlight how gendered interests and self-concepts towards ICT perpetuate occupational gender segregation.
... For female students in STEM, this includes their family, school, and peer interactions. Early educational experiences, support from family, and personal interests play a crucial role in sparking interest in STEM subjects [29]. For example, a young girl encouraged by her parents to explore science kits or participate in math clubs may develop a keen interest in STEM fields. ...
This study explores factors influencing female engagement in STEM (Science, Technology, Engineering, and Mathematics) fields in Mozambique, Nigeria, and Uganda through Urie Bronfenbrenner’s Ecological Systems Theory. The research collected qualitative data from 81 women across these countries through open-ended surveys. Using content analysis, the results demonstrate the critical role of personal interests nurtured by family, showing how direct interactions with family influence STEM engagement at a microsystem level. The mesosystem level reveals the supportive influence of community and school interactions, emphasizing the importance of relationships between different microsystems, such as family–school collaborations, in fostering female participation in STEM. The exosystem level identifies the impact of positive media portrayals and role models, illustrating how external environments indirectly affect perceptions and aspirations in STEM through media and societal influences. The macrosystem level underscores the persistent cultural norms shaping gender roles, reflecting broader societal and cultural values that influence gender diversity in STEM fields, with 63% of respondents in Mozambique, 57% in Nigeria, and 67% in Uganda indicating that societal views on gender roles discouraged participation. Lastly, the chronosystem level captures the temporal changes and progress in gender diversity in STEM, highlighting the need for targeted interventions and policy reforms to address longstanding gender imbalances. Despite progress, significant gender imbalances remain, necessitating targeted interventions and policy reforms. The study proposes a sustainable, collaborative model to foster early interest and sustained participation of females in STEM, emphasizing the importance of seamless cooperation among families, educational institutions, communities, and government bodies. The findings aid in creating supportive environments for sustaining female STEM participation, promoting economic and social development in Sub-Saharan Africa.
... Studies have shown that students often select their programs based on an intrinsic interest in the subject matter (Sarkodie et al., 2020). Research by Schelfhout et al. (2021) highlights how the fit between a student's interest and the chosen program significantly impacts his ability to succeed in his studies. Moreover, a study by James (2007) emphasizes that factors like interest, enjoyment, and career aspiration heavily influence students' choices. ...
This study explores the factors influencing the choice of diploma programs among undergraduate students at Universiti Teknologi MARA (UiTM), Sarawak Branch, Malaysia, and their interrelation with interest and satisfaction. Data were collected from 715 first-semester diploma students across three UiTM Sarawak campuses during the October 2023-February 2024 session, via a questionnaire. The findings highlight the significant impact of personal decisions and family influence in shaping students' choices of diploma programs. Employment opportunities, career aspiration, and academic qualifications emerged as the most influential factors. Nonetheless, students who enrolled in their first-choice programs report high satisfaction, demonstrating that strong interest plays a crucial role in fostering a positive educational experience. Additionally, intrinsic factors are the most significant determinants of students' interest and satisfaction, while extrinsic factors significantly influence interest but have a lesser impact on satisfaction. In contrast, interpersonal factors were found to have minimal effect. This study establishes a comprehensive conceptual model explaining the factors influencing students in choosing their diploma programs and their interrelation with interest and satisfaction. It highlights the importance of intrinsic and extrinsic factors in educational decision-making and suggests that a supportive environment enhances satisfaction and educational outcomes. The insights can inform policies to enhance student experiences and support informed programs choices in higher education. At the same time, they can contribute to ensure inclusive and equitable quality education, in alignment with Sustainable Development Goal 4 (SDG4), which promotes lifelong learning opportunities for all.
... Theoretically and empirically, interest is regarded as a key component for educational as well as vocational choices (Eccles & Wigfield, 2002; J. L. Holland, 1997;Lent et al., 1994;Simpkins et al., 2006;Wigfield et al., 2015), and promoting students' interest has long been considered an effective way to facilitate career choices (Betz & Schifano, 2000;Lent et al., 1994;Luzzo et al., 1999;Renninger et al., 1992;Turner & Lapan, 2005). For example, students with higher realistic (i.e., preferences for the manipulation of objects, tools, and machines; J. L. Holland, 1997) and investigative (i.e., preferences for the systematic observation and investigation of physical, cultural, and biological phenomena; J. L. Holland, 1997) vocational interests are more likely to choose school subjects and study majors in STEM (e.g., Elsworth et al., 1999;Fonteyne et al., 2017; J. L. Holland, 1997;Päßler & Hell, 2012;Perera & McIlveen, 2018;Ralston et al., 2004;Schelfhout et al., 2021;Wille et al., 2020). ...
Unstructured out-of-school time (OST) science activities, such as reading a science book, watching a science television show, or researching on the internet about science, constitute a self-sustaining way for adolescents to engage in science, technology, engineering, and mathematics (STEM). Although it is suggested that long-term engagement in such activities could have a broad influence on several STEM-related constructs, so far little is known about the impact of unstructured OST science engagement. The current study therefore investigated the effects of unstructured OST science engagement on the development of vocational interests, occupational aspirations, competencies, school achievement, and ability self-concepts. For this purpose, we used a large longitudinal subsample (N = 2,655) from the National Educational Panel Study (NEPS; Blossfeld & Roßbach, 2019) where students in Germany were assessed in Grades 9, 11, and 12. Following the recommendations of VanderWeele et al. (2020), we used an outcome-wide longitudinal design for causal inference: Outcome-wide effects of unstructured OST science activities were estimated while controlling for a set of joint confounders and pretest measures. Our findings show that unstructured OST science activities influence investigative vocational interests, but do not influence occupational aspirations, competencies, school grades, and ability self-concepts. The results suggest that adolescents with similar initial interest trait levels who engage in unstructured OST science activities develop a stronger interest toward STEM, compared to adolescents who do not engage in such activities.
... In particular, mentoring programs should have a positive effect on students' educational choices (Kuchynka et al., 2022;Nickolaus et al., 2018). Two literature reviews (Neher-Asylbekov & Wagner, 2022;Wang & Degol, 2013) noted that gender should be explored in future research as it may play an important role in one's career identity or educational choices (Schelfhout et al., 2021;Stringer et al., 2019). Additionally, the influence of digitalization merits exploration (Neher-Asylbekov & Wagner, 2022). ...
The evidence regarding the effectiveness of STEM support programs for K–12 students to spark their interest in the STEM field is mixed. The goals and contents of support programs vary and mostly cover short intervention periods. So far, not many studies exist that cover different learning characteristics of students in long-term STEM support programs. Against this backdrop, the present paper engages in intra- and intergroup comparisons, characterizing groups of students interested in STEM who participated in three long-term STEM support programs and a control group. The sample contained a total of N = 1170 students. For this purpose, the study was divided into a description of the samples, an analysis of the factors influencing career choice decisions, and an analysis of the interest profiles of students in support programs based on a circumplex model comparing STEM and non-STEM students. The results of this study indicate that female students in different support programs tend to fall into the Ideas domain on Prediger’s axis, and male students in support programs are located close to male students in the control group. Overall, the results align with the state of research, suggesting that support programs should be offered regularly, integrated into school curriculums, and linked with STEM universities and mentoring. This study indicates that future research in the context of STEM support programs could verify the effects on students’ vocational interests with longitudinal analyses.
... Interestingly, this gender stereotype even has an impact on STEM job vacancies which increase over time, but inversely proportional to the number of people who want to fill the 'empty seat'. Schelfhout, Wille, Fonteyne, Roels, Derous, Fruyt, and Duyck (2021) stated that industrial areas around the world are experiencing difficulties in filling STEM vacancies due to a decrease in the number of applicants, which is also influenced by the gender gap, shown by the participation of women diminishing returns in the STEM field. In addition, according to McGuire (2021), gender stereotypes related to STEM abilities have important consequences for the involvement and motivation of women to have careers in the STEM field in the future. ...
Women in Asia still experiencing difficulties in flourishing their career aspirations optimally due to strong cultural perspectives. This systematic literature review aims to explore the factors that influence Asian women’s career aspirations in various cultural settings. PRISMA 2018 was used in this study. Through Scopus, ScienceDirect, Springer, and Ebsco Host databases, we found eight articles that met the inclusion criteria after passing the article selection. This study resulted women’s career aspirations in Asia are influenced by internal enabler factors (including self-efficacy, career orientation, abilities and knowledge, need for usefulness, desire for family cohesion, and marriage prospects expectation), external enabler factors (including education, social support, contextual support, and cultural support), internal barrier factors (including fear of marriage prospects, beliefs on choice restrictions, and awareness of domestic roles), and external barrier factors (including social pressure, gender stereotype, peer conformity, financial hardship, and career consequences). Future research to examine women’s career aspirations in the wider cultural setting of various countries in Asia is needed.
... Therefore, S & T and its transfer from the education system to the economy play a central role in the modern society based on knowledge and technology [1][2][3]. In this context, traditional education in science, technology, engineering, and mathematics (also known, colloquially, as STEM education) is an inter-/multi-/transdisciplinary approach to curriculum in many educational systems connecting independent disciplines and represents the primary gateway of higher education to the field of STEM work [4,5]. In fact, the symbiosis ...
Since the beginning of this century, STEM education has become increasingly important in preserving prosperity and economic competitiveness. Architecture has its own specific attributes. It overarches the STEM and HASS disciplines, and it should be perceived as a cultural phenomenon rather than as a field of study. The main objective of this article is to highlight the methodology based on the statistical method evaluating the correlation rate between the Bachelor’s student performance (SP) in design studio courses and STEM and HASS categories, represented by particular subjects of various areas of study. The relationship between the admission examination procedure and the academic performance of graduates in the DESIGN category was also analyzed. Although the level of knowledge and skills required based on the study results within the curricula was more significant in the HASS category, the direct correlation between subjects in the STEM category, especially engineering, and the quality of the design studio¢s outputs as the main and fundamental part of the creative architectural work, was also confirmed. The authors of the article found that STEM knowledge and STEM skills do not reach the required level and, therefore, the emphasis should be placed on changing curricula, balancing the ratio of STEM and HASS categories, adjusting the credits assigned to STEM subjects, or reviewing the classification system.
The difficulty of finding vocational interest measurement tools with good psychometric properties and relevance to modern developments is a current concern in Indonesia. Therefore, this scoping review aims to compile a list of vocational interest measurement tools available in Indonesia that have been psychometrically tested. For this purpose, a total of 2,196 articles were extracted from the Google Scholar, Garuda, and Scopus databases. The article selection procedure followed the PRISMA-ScR flow diagram, and the screening process resulted in 17 sample articles (2014–2024). The analysis showed that most vocational interest measurement tools in Indonesia use a top-down development approach, based on Holland’s Structure of Interests, and emphasize internal structure validity and internal consistency reliability as the tested psychometric properties. Further research is needed to address the gaps in validity evidence that remain among Indonesian vocational interest measurement tools.
Gender and racial-ethnic disparities continue to exist in participation within science, technology, engineering, and mathematics (STEM) fields. Because vocational interests predict career choice and educational interventions to help promote STEM interest among underrepresented groups have increased, research is needed to assess if meaningful changes have occurred with STEM-related interests, particularly among women and people of color who have historically been underrepresented in the STEM workforce. The present study examines vocational interests in large samples of college students across two cohorts who completed the Strong Interest Inventory in 2005 ( N = 6,496) and 2019 ( N = 21,146). Results indicate that STEM-related interest levels have increased both across gender (i.e., men and women) and racial-ethnic groups, specifically for Black, Latinx, Asian, and White college students over this period. Notably, STEM-related interests declined or stayed the same across cohorts for Native American students. Additionally, the gap between women and men narrowed for the Investigative General Occupational Theme and STEM-related Basic Interest Scales. Finally, these results are discussed within the context of vocational interest development and societal STEM-related initiatives and focus on increasing STEM interests among underrepresented youth living in the United States.
Vocational interest research relies on interest taxonomies that partition the construct space of activity preferences into a small number of broad interest domains. To this day, the most widely used classification system is the RIASEC taxonomy (Holland, 1997), which distinguishes between six overarching interest domains. A central feature of this model is that the six domains are connected via a circular similarity structure, the circumplex, which is often described with the help of two orthogonal core dimensions: People-Things and Data-Ideas. In recent years, alternative interest taxonomies have been proposed, which suggest different partitionings of the construct space that are said to better reflect today’s world of work. Using the example of one such alternative, namely, the recently introduced SETPOINT model (Su et al., 2019), the current article argues that alternative taxonomies strongly reflect the underlying core dimensions that define the interest circumplex. Using a mixed online sample from Germany (N = 560), it is shown that 1) the main and subdomains of the SETPOINT model reflect a circular similarity structure, 2) this circular similarity structure is conceptually identical to the ones identified in previous research, and 3) the discriminatory power of the SETPOINT scales for occupational group membership can largely be traced back to the core dimensions of the interest circumplex.
Research has shown the challenges women face in the STEM fields, even though there are benefits. Therefore, knowing the challenges can help better prepare females for careers in STEM and help with policymaking. In this chapter, the authors have highlighted the impact of remote learning in STEM and how to increase women's representation and STEM on college students. They recognize that interventions are needed to help recruit and retain women in STEM fields, and female role models are required. Therefore, having a diverse workforce culture is vital, and removing the gender stereotypes associated with women in STEM is critical for the future of women's interest and employment in STEM fields.
The first wave of the COVID-19 epidemic brought a lot of
uncertainty, as it was the first time, we encountered such
stringent measures to limit the transmission of the infection, such
as school closures, social-distancing, inability to work, etc. and
for many, that posed great stress. The aim of this study was
to investigate the perceived stress of Slovenian high school
students in the first wave of the epidemic. For this purpose, we
conducted an online survey sent to secondary schools and student
dormitories. Data on a sample of 1492 students show that the
majority of the student population (69.9%) perceived moderate
stress (low-medium-high categories) in the first wave of the
epidemic and a good sixth of students (17.8%) high stress. 34-
44% of students had more sleep problems, were more irritable,
had stronger and/or unpleasant emotions, more feelings of
helplessness and a lack of energy than before the epidemic. 8-10%
of students experienced it significantly more than before the
epidemic. The research also showed that the level of perceived
stress is significantly related to gender, school program,
(non)staying in the dormitory, and chronic diseases
Each student faces the challenge of choosing a study program that matches his or her vocational interest. A good person-environment fit (PE fit) between student and study program influences study success and persistence, prerequisites to obtaining the desired degree. But which criterion should be used when presenting advice sets of study options to orient students toward study programs that match their vocational interests? And how long should such a list of study options be? Moving beyond existing, non-evidence-based approaches, present study sets out to develop an empirical advice set engine (EASE) to optimize the process of matching future students to fitting study options. Compared to existing, non-evidence-based alternatives, EASE shows a better balance between the number and PE fit of the options presented. EASE may be a promising way to rethink how student PE fit information can be used in student orientation and higher education research.
The extent to which a good person-environment (PE) interest fit between student and study program leads to better study results in higher education is an ongoing debate wherein the role of the study program environment has remained inadequately studied. Unanswered questions include: how diverse study programs are in the interests of their student populations, and how this program interest diversity influences study results, in comparison to individual PE fit? The present study addressed these questions in students (N = 4,635) enrolled in open-access university education. In such an open access system, students are allowed to make study choices without prior limitations based on previous achievement or high stakes testing. Starting from the homogeneity assumption applied to this open access setting, we propose several hypotheses regarding program interest diversity, motivation, student-program interest fit, and study results. Furthermore, we applied a method of measuring interest diversity based on an existing measure of correlational person-environment fit. Results indicated that interest diversity in an open access study environment was low across study programs. Results also showed the variance present in program interest diversity was linked to autonomous and controlled motivation in the programs’ student populations. Finally, program interest diversity better explained study results than individual student fit with their program of choice. Indeed, program interest diversity explained up to 44% of the variance in the average program’s study results while individual student-program fit hardly predicted study success at all. Educational policy makers should therefore be aware of the importance of both interest fit and interest diversity during the process of study orientation.
The underrepresentation of girls and women in science, technology, engineering, and mathematics (STEM) fields is a continual concern for social scientists and policymakers. Using an international database on adolescent achievement in science, mathematics, and reading (N = 472,242), we showed that girls performed similarly to or better than boys in science in two of every three countries, and in nearly all countries, more girls appeared capable of college-level STEM study than had enrolled. Paradoxically, the sex differences in the magnitude of relative academic strengths and pursuit of STEM degrees rose with increases in national gender equality. The gap between boys’ science achievement and girls’ reading achievement relative to their mean academic performance was near universal. These sex differences in academic strengths and attitudes toward science correlated with the STEM graduation gap. A mediation analysis suggested that life-quality pressures in less gender-equal countries promote girls’ and women’s engagement with STEM subjects.
Normative circular and dimensional models are the dominant structures for the organization of vocational interests in the scientific literature. However, it is increasingly recognized that not all individuals’ interest configurations can be adequately represented by normative models. Adopting a person-centered, multidimensional perspective on vocational interests, the current study seeks to identify distinct profiles of interests based on RIASEC data that integrate interest configurations that align with and deviate from normal circular and dimensional structures. We also test the replicability of the profile structure, examine the likelihood of STEM degree choice as a function of profile membership, and investigate core personality predictors of interest profile membership. Latent profile analyses revealed six profiles of vocational interests, representing distinct combinations of the RIASEC interests (i.e., social-dominant, disinterested, high realistic-dominant, investigative-dominant, ambivalent, and conventional-dominant), which replicated entirely across independent subsamples. Furthermore, the profiles differed on the likelihood of STEM degree choice, with the conventional-dominant profile evincing the highest probability of choice and the social-dominant profile evincing the lowest probability of choice. Finally, results revealed that the Big-Five personality traits were differentially related to interest profile membership, largely in line with vocational interest theory. The present findings constitute novel evidence that a person-centered framework for the representation of interest configurations can accommodate both people’s adherence to and deviations from normative structures for the organization of interests. The findings also underpin the use of all available interest information on individuals, rather than reliance on the two or three highest interest dimensions, to inform educational and vocational decision-making.
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Increased efforts to diversify science, technology, engineering, and mathematics (STEM) education in the United States have drastically increased the number of studies offering insight into the experiences of women in STEM programs in higher education. This paper presents a thematic review of the literature regarding their status from 2007 to 2017 including journals, trade magazines, theses, and dissertations. It focuses on areas of recruitment, retention, barriers, and faculty issues. Stereotypes, biases, campus culture, classroom experiences, identity, and sense of belonging are also explored. The author additionally identifies gaps and suggests related areas for new research as well as implications for librarians. Full-text available at http://dx.doi.org/10.1080/0194262X.2017.1371658
Vocational interests are important aspects of personality that reflect individual differences in motives, goals, and personal strivings. It is therefore plausible that these characteristics have an impact on individuals’ lives not only in terms of vocational outcomes, but also beyond the vocational domain. Yet the effects of vocational interests on various life outcomes have rarely been investigated. Using Holland’s RIASEC taxonomy (Holland, 1997), which groups vocational interests into 6 broad domains, the present study examined whether vocational interests are significant predictors of life outcomes that show incremental validity over and above the Big Five personality traits. For this purpose, a cohort of German high school students (N = 3,023) was tracked over a period of 10 years after graduating from school. Linear and logistic regression analyses were used to examine the predictive validity of RIASEC interests and Big Five personality traits. Nine outcomes from the domains of work, relationships, and health were investigated. The results indicate that vocational interests are important predictors of life outcomes that show incremental validity over the Big Five personality traits. Vocational interests were significant predictors of 7 of the 9 investigated outcomes: full-time employment, gross income, unemployment, being married, having children, never having had a relationship, and perceived health status. For work and relationship outcomes, vocational interests were even stronger predictors than the Big Five personality traits. For health-related outcomes, the results favored the personality traits. Effects were similar across gender for all outcomes—except 2 relationship outcomes. Possible explanations for these effects are discussed.
A new, Holland-based Interest Inventory is proposed, intended to facilitate the transition from secondary to tertiary education. Specific interest items were designed to grasp activities that are prevalent during tertiary studies, including an Academic-track-scale to assist in the choice between academic and vocational-oriented programs. Interest profile descriptions are complemented by a list of matching study programs. Data from 3,962 students were analyzed to evaluate the underlying circumplex structure, the criterion validity of the Academic-track-scale and the study program RIASEC codes. It is concluded that the assessment and feedback tools are promising instruments to facilitate the transition to tertiary education.
Recent attention has been brought to light in the United States regarding low numbers of students pursing STEM (Science, Technology, Engineering and Math) disciplines and degree programs (National Science Board, 2010). There is a great need in America for talented scientists and engineers. Numerous programs abound for high school and middle school students in regard to STEM initiatives; however, fewer opportunities exist for elementary students and their teachers. Research has shown that early exposure to STEM initiatives and activities positively impacts elementary students' perceptions and dispositions (Bagiati, Yoon, Evangelou, & Ngambeki, 2010; Bybee, & Fuchs, 2006). By capturing students' interest in STEM content at an earlier age, a proactive approach can ensure that students are on track through middle and high school to complete the needed coursework for adequate preparation to enter STEM degree programs at institutions of higher learning. As a result, programs focusing on STEM initiatives and content are a growing priority in American schools with aims to provide early exposure for elementary students.
Samples of high school (n = 370) and college (n = 223) students completed the Vocational Preference Inventory (J.L. Holland, 1985b) and the Inventory of Occupational Preference (IOP; T.J. Tracey & J. Rounds, in press). Their responses were examined with respect to whether they fit a uniform circular distribution. For both the high school and college samples, the individual interest items were uniformly arranged in a circle, indicating that there are no preferred points around the circle. Also, the 8 IOP octant scales and the 6 RIASEC scales (i.e., Realistic, Investigative, Artistic, Social, Enterprising, and Conventional) fit the data equally well, indicating that the 6 RIASEC scales are only one of many scale configurations that will fit a circular ordering. The results confirm that vocational interests have a uniform distribution along a circle and that the number of scales used is a matter of convenience. The relative utility of 6 or 8 scales and viewing interests as a set of concentric circles are discussed.
Students' perceptions of their mathematics ability vary by gender and seem to influence science, technology, engineering, and mathematics (STEM) degree choice. Related, students' perceptions during academic difficulty are increasingly studied in educational psychology, suggesting a link between such perceptions and task persistence. Despite interest in examining the gender disparities in STEM, these concepts have not been considered in tandem. In this manuscript, we investigate how perceived ability under challenge—in particular in mathematics domains—influences entry into the most sex-segregated and mathematics-intensive undergraduate degrees: physics, engineering, mathematics, and computer science (PEMC). Using nationally representative Education Longitudinal Study of 2002 (ELS) data, we estimate the influence of perceived ability under challenging conditions on advanced high school science course taking, selection of an intended STEM major, and specific major type 2 years after high school. Demonstrating the importance of specificity when discussing how gender influences STEM career pathways, the intersecting effects of gender and perceived ability under mathematics challenge were distinct for each scientific major category. Perceived ability under challenge in secondary school varied by gender, and was highly predictive of selecting PEMC and health sciences majors. Notably, women's 12th grade perceptions of their ability under mathematics challenge increased their probability of selecting PEMC majors over and above biology. In addition, gender moderated the effect of growth mindset on students' selection of health science majors. Perceptions of ability under challenge in general and verbal domains also influenced retention in and declaration of certain STEM majors. The implications of these results are discussed, with particular attention to access to advanced scientific coursework in high school and interventions aimed at enhancing young women's perceptions of their ability, in particular in response to the potentially inhibiting influence of stereotype threat on their pathways to scientific degrees.
The degree of women's underrepresentation varies by STEM fields. Women are now overrepresented in social sciences, yet only constitute a fraction of the engineering workforce. In the current study, we investigated the gender differences in interests as an explanation for the differential distribution of women across sub-disciplines of STEM as well as the overall underrepresentation of women in STEM fields. Specifically, we meta-analytically reviewed norm data on basic interests from 52 samples in 33 interest inventories published between 1964 and 2007, with a total of 209,810 male and 223,268 female respondents. We found gender differences in interests to vary largely by STEM field, with the largest gender differences in interests favoring men observed in engineering disciplines (d = 0.83–1.21), and in contrast, gender differences in interests favoring women in social sciences and medical services (d = −0.33 and −0.40, respectively). Importantly, the gender composition (percentages of women) in STEM fields reflects these gender differences in interests. The patterns of gender differences in interests and the actual gender composition in STEM fields were explained by the people-orientation and things-orientation of work environments, and were not associated with the level of quantitative ability required. These findings suggest potential interventions targeting interests in STEM education to facilitate individuals' ability and career development and strategies to reform work environments to better attract and retain women in STEM occupations.
This article presents an overview of the recent literature on gendered patterns of academic choice in mathematics, science, and technology. It distinguishes in this literature micro-level, macro-level, and institutional explanations. Micro-level explanations focus primarily on psychological constructs, that is, variables at the level of the individual students. Macro-level explanations focus primarily on socioeconomic conditions and cultural understandings of gender roles. Institutional explanations focus on design characteristics of (national) education systems. After a presentation of these perspectives and of recent research progress that has been made, the authors critically discuss the lacunae that still exist in explaining cross-national variety, and provide suggestions for designing future research in this field.
Research for more than 60 years has shown that entry into occupations can be predicted from scores on interest inventories at a rate better than chance (Donnay, ). The psychometric scoring methodologies used today by a majority of vocational interest inventories were developed in the 1920s and 1960s. Researchers are challenged with improving the theory and science behind vocational interest inventories to align them with current vocational constructions. In this study, validity comparisons were made between person matching and standard scoring based on 5,143 medical students who had taken a vocational interest inventory and had entered their medical residency. Person matching was found to improve differentiation between occupational groups and increase the amount of information offered in the scoring report; in addition, it could potentially increase occupational group assignment to advance vocational interest inventory validity.
National debate about K-12 Science, Technology, Engineering, and Mathematics (STEM) education has given rise to questions about appropriate materials for engineering education from prekindergarten through grade 12. Introducing engineering in the early years entails recognition of the need for teachers to understand its content and poses the challenge of preparing teachers to incorporate engineering education into their practice. Teacher preparation has historically included seeking information in books, journals, and magazines, and the professional development offered by universities, school districts, and other educational entities continues to provide the majority of formal options accessed by teachers. However, the advent of the Internet has expanded the ways that teachers undertake professional development and how they prepare to present new content. An online search for open source preschool through grade 12 (P-12) engineering materials revealed a wide variety of Web sites and online documents that included curricula, lesson plans, and descriptions of activities. Narrowing the search to the P-3 level revealed that the pedagogically and content-reliable sources available are limited in number and may be difficult to identify among the plethora of information. This study begins to describe the current landscape of open-access Internet materials in the field of early STEM with emphasis on engineering. The authors offer a guide-in-progress for selecting material for teachers and parents interested in introducing their young children to engineering. The authors also address emerging pedagogical fidelity and engineering content issues.
Despite their significance to both individuals and organizations, interests are often misunderstood, and their predictive power is often overlooked. In this article, we discuss the nature of interests, describe several key features of interests, and, contrary to the received knowledge of many, explain how interests can be used to predict career and educational choice, performance, and success. Finally, we discuss the continuity of interests across the life span and explain how evidence of stability supports conceptualizations of interests as being distinct dispositions rather than simply extensions or workplace instantiations of basic personality traits.
This retrospective cohort study characterizes how interest in science, technology, engineering, mathematics (STEM) careers changes during high school for more than 6,000 students in a representative national sample of 34 two- and four-year colleges taking mandatory college English courses. Overall, large gender differences in career plans were found, with males showing far more interest particularly in engineering, whereas females were more attracted to careers in health and medicine during their high school years. The key factor predicting STEM career interest at the end of high school was interest at the start of high school. There was an additional effect of gender, indicating both a lower retention of STEM career interest among females and a greater difficulty in attracting females to STEM fields during high school. During the high school years, the percentage of males interested in a STEM career remained stable (from 39.5 to 39.7), whereas for females it declined from 15.7 to 12.7. The students' initial specific (disciplinary) career interests were found to influence the stability of their interest in a STEM career, with those interested in physics careers at the start of high school having the highest retention in STEM. © 2012 Wiley Periodicals, Inc. Sci Ed 96:411–427, 2012
In 1987, Hubert and Arabie proposed a randomization test of hypothesized order relations, and this has been operationalized in the Microsoft FORTRAN RANDALL program. This program enables the evaluation of the fit of any pattern model to a data matrix of similarities or dissimilarities. The exact probability of the model-data fit exceeding chance (as defined by a random relabeling of the rows and columns of the data matrix) is provided. This program is especially valuable in the evaluation of circumplex models of data as found in color perception, vocational interests, and interpersonal behavior.
This meta-analysis (114 studies, k = 157, N = 21,616) examined the relationship between self-efficacy and work-related performance. Results of the primary meta-analysis indicated a significant weighted average correlation between self-efficacy and work-related performance, G (r+) = .38, and a significant within-group heterogeneity of individual correlations. To account for this variation, the authors conducted a 2-level theory-driven moderator analysis by partitioning the k sample of correlations first according to the level of task complexity (low, medium, and high), and then into 2 classes according to the type of study setting (simulated–lab vs. actual–field). New directions for future theory development and research are suggested, and practical implications of the findings are discussed.
Despite early claims that vocational interests could be used to distinguish successful workers and superior students from their peers, interest measures are generally ignored in the employee selection literature. Nevertheless, theoretical descriptions of vocational interests from vocational and educational psychology have proposed that interest constructs should be related to performance and persistence in work and academic settings. Moreover, on the basis of Holland's (1959, 1997) theoretical predictions, congruence indices, which quantify the degree of similarity or person-environment fit between individuals and their occupations, should be more strongly related to performance than interest scores alone. Using a comprehensive review of the interest literature that spans more than 60 years of research, a meta-analysis was conducted to examine the veracity of these claims. A literature search identified 60 studies and approximately 568 correlations that addressed the relationship between interests and performance. Results showed that interests are indeed related to performance and persistence in work and academic contexts. In addition, the correlations between congruence indices and performance were stronger than for interest scores alone. Thus, consistent with interest theory, the fit between individuals and their environment was more predictive of performance than interest alone.
© The Author(s) 2012.
Samples of high school (
n = 370) and college (
n = 223) students completed the Vocational Preference Inventory (J. L. Holland, 1985) and the Inventory of Occupational Preference (IOP; T. J. Tracey & J. Rounds, in press). Their responses were examined with respect to whether they fit a uniform circular distribution. For both the high school and college samples, the individual interest items were uniformly arranged in a circle, indicating that there are no preferred points around the circle. Also, the 8 IOP octant scales and the 6 RIASEC scales (i.e., Realistic, Investigative, Artistic, Social, Enterprising, and Conventional) fit the data equally well, indicating that the 6 RIASEC scales are only one of many scale configurations that will fit a circular ordering. The results confirm that vocational interests have a uniform distribution along a circle and that the number of scales used is a matter of convenience. The relative utility of 6 or 8 scales and viewing interests as a set of concentric circles are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The purpose of this report is to offer social cognitive theory (SCT) and its derivative construct of self-efficacy as an extension of traditional management approaches, that will lead to both a better understanding in the modern workplace and more effective management of human performance. SCT explains organizational behavior in terms of the reciprocal causation among the employee (unique personality characteristics), the environment (perceived consequences from the organizational environment, such as pay for performance), and the behavior itself (previous successful performances). Because of these combined reciprocal influences, employees are at the same time both products and producers of their personality, their behaviors, and their respective environments. The authors suggest that the implications that self-efficacy may have for employee performance in organizations can no longer be ignored by practicing managers. They contend that while traditional motivational and behavioral management approaches are still relevant, expanding the behavioral management approach with SCT and self-efficacy will lead to the more comprehensive understanding and effective management of today's human resources. This article is offered as a point of departure for achieving this objective. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The present study examines whether vocational interests, measured by Holland’s RIASEC model,
and objectively assessed cognitive abilities, were useful in discriminating among various major
categories for a sample of 1990 German university students. Interests and specific abilities, in
combination, significantly discriminated among major categories and furthermore, ability measures
added incremental validity to prediction based on interest measures alone. Logistic regression
analyses revealed significant differences in predictor importance between women and men. Furthermore, overall gender differences in interests and cognitive abilities were identifiable within
major categories as well. Implications for career counseling are discussed.
This article presents a social cognitive framework for understanding three intricately linked aspects of career development: (a) the formation and elaboration of career-relevant interests, (b) selection of academic and career choice options, and (c) performance and persistence in educational and occupational pursuits. The framework, derived primarily from Bandura's (1986) general social cognitive theory, emphasizes the means by which individuals exercise personal agency in the career development process, as well as extra-personal factors that enhance or constrain agency. In particular, we focus on self-efficacy, expected outcome, and goal mechanisms and how they may interrelate with other person (e.g., gender), contextual (e.g., support system), and experiential/learning factors. Twelve sets of propositions are offered to organize existing findings and guide future research on the theory. We also present a meta-analysis of relevant findings and suggest specific directions for future empirical and theory-extension activity.
This study examines the underrepresentation of women faculty in science, technology, engineering, and mathematics (STEM) by
comparing the intentions of attrition and turnover between genders in Research and Doctoral universities. It is found that
the two genders did not differ in their intentions to depart from academia, but women faculty had a significantly higher likelihood
to change positions within academia. The indications are that women and men are equally committed to their academic careers
in STEM; nonetheless, women’s stronger turnover intentions are highly correlated with dissatisfaction with research support,
advancement opportunities, and free expression of ideas. The findings suggest that the underrepresentation of women is more
convincingly explained by an academic culture that provides women fewer opportunities, limited support, and inequity in leadership,
rather than by gender-based differences such as roles in family responsibilities. Changes in academic STEM culture are needed
in order to attract more women scientists and narrow the current gender gap.
Receiver operating characteristics (ROC) graphs are useful for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been used increasingly in machine learning and data mining research. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research.
Using longitudinal student data from 15 four-year (n = 3,072) and 13 (n = 788) two-year postsecondary institutions, the authors tested the effects of interest-major congruence, motivation, and 1st-year academic performance on timely degree completion. Findings suggest that interest-major congruence has a direct effect on timely degree completion at both institutional settings and that motivation has indirect effects (via 1st-year academic performance). The total effects of both interest-major congruence and motivation on timely degree completion underscore the importance of both constructs in understanding student adjustment and postsecondary success. Implications for theory and counseling practice are discussed.
This article celebrates the 50th anniversary of the introduction of John L. Holland's (1959) theory of vocational personalities and work environments by describing the theory's development and evolution, its instrumentation, and its current status. Hallmarks of Holland's theory are its empirical testability and its user-friendliness. By constructing measures for operationalizing the theory's constructs, Holland and his colleagues helped ensure that the theory could be implemented in practice on a widespread basis. Empirical data offer considerable support for the existence of Holland's RIASEC types and their ordering among persons and environments. Although Holland's congruence hypotheses have received empirical support, congruence appears to have modest predictive power. Mixed support exists for Holland's hypotheses involving the secondary constructs of differentiation, consistency, and vocational identity. Evidence of the continued impact of Holland's theory on the field of counseling psychology, particularly in the area of interest assessment, can be seen from its frequent implementation in practice and its use by scholars. Ideas for future research and practice using Holland's theory are suggested.
In confirmatory analysis of whether data have a circumplex structure, Browne's (1992) model has played a major role. However, implementation of this model requires a dedicated program, CIRCUM, because the analysis routine is not integrated in any of the most widely used statistical software packages. Hence, data entry and graphical representation of the results require the use of one or more additional programs. We propose a package for the R statistical environment, termed CircE, that can be used to enter or import data, implement Browne's confirmatory analysis, and graphically represent the results. Using this new software, we put forward a new approach to assess the sustainability of theoretical models when the analysis is carried out at the level of questionnaire items. The CircE package (for either Mac OS X or Windows) and additional files may be downloaded from http://brm.psychonomic-journals.org/content/supplemental.
This report was commissioned to update and extend the Background Data and Analysis component of the report, Australia's Teachers: Australia's Future - Advancing Innovation, Science, Technology and Mathematics (Committee for the Review of Teaching and Teacher Education, 2003a) that informed the Main Report (Committee for the Review of Teaching and Teacher Education, 2003b). In the five years since the 2003 review, there have been developments in science, technology and mathematics education that have been impacted on by initiatives in policy and practice as well by changes in the context. So that changes in science, technology and mathematics education can be properly measured the measures of participation that are used in this report parallel those that were used in the 2003 report wherever that is possible. In brief this report provides updated figures on: the performance of Australian school students in science and mathematics; participation in science, mathematics, and technology in the final year of secondary school; university participation in science and technology studies; and teachers, teaching and teacher education in science, technology and mathematics.
De overgang naar hoger onderwijs is een beproeving voor elke Vlaamse student. Inderdaad, omdat Vlaanderen een open toegang heeft tot hoger onderwijs, kan elke student met een diploma secundair onderwijs aan bijna elke opleiding beginnen. Om het vooropgestelde diploma te halen van de gekozen opleiding, dient een student twee taken tot een goed einde te brengen. De student dient een haalbare studiekeuze te maken. En de student dient te slagen in examens om op schema te blijven om het begeerde diploma te halen. Deze taken zijn niet zo eenvoudig als ze lijken. De data in deze dissertatie geven aan dat slechts 36% van de eerstejaarsstudenten erin slaagt om alle opleidingsonderdelen tot een goed einde te brengen om zo op schema te blijven om tijdig het beoogde diploma te behalen. Om dit onrustwekkende cijfer te verbeteren heeft de Universiteit Gent het SIMON-project (Study Skills and Interest MONitor) gestart. SIMON is erop gericht om studenten die dreigen te falen te (her)oriënteren naar een meer haalbaar studieprogramma vooraleer ze hun examens effectief falen, met verlies van tijd en middelen tot gevolg. In deze dissertatie worden de PAKSOC (praktisch, analytisch, kunstzinnig, sociaal, ondernemend en conventioneel) studie interesses van een student gebruikt om de impact van het SIMON project te vergroten door in de literatuur een aantal openstaande vragen te onderzoeken omtrent studiekeuze en studiesucces. Om dit te bewerkstelligen heb ik in deze dissertatie de uitvoering en resultaten besproken van vier empirische studies. Zo heb ik onder meer gevonden dat de fit tussen de interesses van een student en een set van studieprogramma’s kan worden benaderd via een uniforme distributie. Deze distributie kan dan worden gebruikt als de basis voor een Empirische Advies Set Engine, of ook wel EASE. EASE verstrekt gepersonaliseerde studieoriëntatie voor elke student, gebaseerd op een objectief criterium dat toelaat de lengte en de fit van de set met voorgestelde programma’s te balanceren. Deze balans is superieur aan deze die wordt gegenereerd door meer klassieke indices van interessefit, die trouwens ook worden gebruikt in SIMON. Dergelijke studieoriëntatie kan van cruciaal belang zijn in bepaalde gespecialiseerde gebieden. Als dusdanig heb ik ook onderzocht hoe de interessefit van studenten en studieprogramma’s kan bijdragen tot een economisch belangrijke STEM (wetenschap, technologie, ingenieur en wiskunde) studiekeuze. De resultaten hiervan laten duidelijk zien dat vrouwelijke studenten een betere interessefit hadden met hun gekozen (STEM en niet-STEM) programma in vergelijk met mannelijke studenten. Vrouwelijke STEM - studenten hadden ook een betere interessefit met het STEM veld in vergelijking met hun mannelijke collega’s. STEM studiekeuze en de genderkloof (mannelijke meerderheid) in het STEM veld werden verklaard door een model dat alle PAKSOC dimensies bevatte, naast wekelijkse uren wiskunde in het secundair onderwijs, en de fit met het STEM veld. Een mannelijke STEM keuze was meer gerelateerd aan uren wiskunde in het secundair, terwijl een vrouwelijke STEM keuze meer gerelateerd was aan de fit met het STEM veld. Naast studiekeuze behandelt de huidige dissertatie ook studiesucces. Omtrent dit studiesucces, heb ik ook een verandering voorgesteld in methodologie. Als dusdanig spitst de huidige dissertatie zich toe op identificeren van studenten die dreigen te falen in hun gekozen studieprogramma. Hiertoe heb ik mij vooral gericht op het voorspellen van resultaten van individuele studenten, en niet op het verklaren van populatievarantie in studiesucces, zoals het meestal gebeurt in de literatuur. Deze methodologie valideert ook een set (niet-) cognitieve predictoren voor identificatie van falende studenten. Wat betreft deze identificatie, heb ik ook de mogelijkheid onderzocht om minder strenge vals-positieve (succesvolle studenten die worden geïdentificeerd als falend) ratio’s te gebruiken. Specifiek voor studie-interesses heb ik een aanwezigheidsgraad gevonden van 24% in de identificatiemodellen. Dit betekent dat studie interesses voorkwamen in 24% van de (programma-) specifieke modellen om studiesucces te voorspellen. Dit was de derde meest impactvolle predictor, na studieantecedenten en cognitief vermogen. De relatie tussen studie-interesses en studiesucces wordt ook beïnvloed door de omgeving. Resultaten laten zien dat programma’s een lage diversiteit hebben in de studie interesses van studenten die het programma hebben gekozen. Populaties met een hogere diversiteit werden trouwens gelinkt aan hogere gemiddelde gecontroleerde motivatie en lagere gemiddelde autonome motivatie. In het algemeen was een hogere diversiteit over programma’s ook gelinkt aan betere gemiddelde studieresultaten. Bij een aantal programma’s met een zeer specifiek interessepatroon (hoge sociale dimensie, lage praktische dimensie) observeerde ik echter het omgekeerde effect. Ik vond ook dat de interessediversiteit in programma’s een sterkere invloed had op studiesucces dan individuele interessefit. Om te besluiten, stel ik dat in deze dissertatie, de empirische resultaten en de specifieke operationalisatie van de PAKSOC dimensies en interessefit een uniek perspectief (open toegang) bieden op studie-interesses en hun effect op studiekeuze en studiesucces. Oriëntatie naar een interessante studiekeuze wordt gebaseerd op een objectief criterium: hoe goed moet de fit zijn tussen de interesses van een student en het profiel van een programma? Oriëntatie naar haalbare studiekeuzes wordt gebaseerd op het identificeren van falende studenten door het voorspellen van studiesucces, terwijl er nog altijd wordt rekening gehouden met de specifieke set up van het onderwijssysteem met open toegang. Deze dissertatie stelt studieadviseurs ook in staat deze bevindingen onmiddellijk in de praktijk te brengen.
Social cognitive career theory (SCCT) consists of five interrelated models. Its original models focus on the determinants of educational and occupational interest, choice, and performance (including persistence) (Lent, Brown, & Hackett, 1994). A fourth model is aimed at satisfaction and other aspects of well-being in academic and career-related settings (Lent & Brown, 2006a, 2008), and the fifth model highlights processes whereby people manage common developmental tasks and uncommon challenges across the career lifespan (Lent & Brown, 2013). Each of the models seeks to integrate relevant streams of inquiry, with the larger goal of producing a unifying perspective on educational and career behavior. On the occasion of the 25th anniversary of SCCT's introduction, we consider the empirical status of the original three models as well as inquiry on the sources of self-efficacy and outcome expectations, which undergird the three models. Drawing primarily on meta-analytic findings, we examine the tenability of each of the models, observe the roles of particular social cognitive variables within and across model tests, note moderators of model relationships and anomalous findings, point to hypotheses that have been understudied, and suggest additional directions for future inquiry.
Purpose
Gender inequalities in higher education have attracted interest in the academic literature. The paper aims to discuss this issue.
Design/methodology/approach
The author uses standardized high school final exam results and probit regression analysis to contribute to this highly important discussion.
Findings
Based on secondary, non-survey data, female students tend to outperform males in subjects requiring creativity. Consistent with this comparative advantage, female students also tend to be more affected by their abilities in choosing and preferring the related field of humanities as a higher education. In line with female students’ choices, the results presented in the paper confirm that men are more inclined toward exact and natural sciences, even though they do not prove to have stronger abilities in related subjects. In addition, men are also more influenced by their abilities in obtaining a professional higher education. The choice of social sciences is quite similarly affected by the academic abilities of men and women. The paper also provides evidence that, on average, individuals choose their field of study according to their academic abilities.
Originality/value
For evidence, a data set that makes it possible to relate quantitative measures of very different academic abilities to all major academic disciplines is used in the paper. This unique approach has so far been lacking in the literature due to data limitations. In other words, instead of concentrating on a specific area, such as science, technology, engineering, and mathematics (STEM), the author takes a broader view.
Against the background of the increasing need for skilled scientists and engineers, the heterogeneous inflow of incoming students in science and engineering programs is particularly challenging in universities with an open-admission system. The prime objective of the present study is to determine the main academic and non-academic determinants of study success in a STEM study program in the largest university of Flanders (Belgium). The Learning and Study Strategies Inventory (LASSI), supplemented with additional background questions, was completed by 1521 first-year science and engineering students at the start of the academic year. To evaluate the incremental value of a particular predictor in explaining first-year GPA, a series of nested regression models were evaluated. Math level and math/science GPA in secondary school were strongly related to first-year GPA. Analysis of the LASSI questionnaire showed that students’ motivation/persistence, concentration, and time management skills at the start significantly influenced student achievement at the end of the first year, although the incremental value over prior achievement was small. Altogether, our results show that incoming students’ ability to regulate their study efforts has beneficial consequences in terms of achievement. Additionally, a negative recommendation by the secondary school teacher board was a clear indicator to identify at-risk students. In open-admission universities wherein new students cannot be formally denied access based on weak prior mathematics and science achievement, a focus on effort-related self-regulatory skills training (e.g., time management sessions) offers valuable opportunities for remedial interventions.
The concept of congruence, or the match between an individual and his or her environment, plays a major role in Holland's (1959, 1997) theory of vocational interests. Despite this emphasis, empirical research on the validity of congruence indices for predicting some outcomes has been somewhat disappointing (e.g. Assouline & Meir, 1987; Tinsley, 2000). Although recent research has found that congruence indices can provide meaningful improvements in validity (Nye, Su, Rounds, & Drasgow, 2017), it is widely recognized that these indices have a number of conceptual and methodological flaws (Camp & Chartrand, 1992; Edwards, 1993). To help address this issue, the present work demonstrates the potential benefits of operationalizing interest congruence using polynomial regression (Edwards, 1994) and discusses how such a method can yield more nuanced details about the importance of vocational interests for predicting work and academic outcomes.
Choosing a suitable study program is one of the factors that facilitates academic achievement and thus prevents drop-out in the first year of tertiary education. This requires adequate information on both the individual abilities and the environment during the study choice process. The SIMON (Study Skills and Interest MONitor) project of Ghent University, Belgium, provides this information to prospective students through an online tool that informs them a) on the match between their interests and study programs and b) about their personal chances of success in specific study programs. The current study intends to validate the prediction of program-specific chances of success by examining a) the (incremental) predictive validity of cognitive and non-cognitive variables of conscientiousness, motivation, self-efficacy, metacognition and test anxiety and b) the differential predictive power of variables within and across study programs. In addition, a path model with structural relations between variables was tested. The sample consisted of 2391 new incoming students. Results supported the incremental validity of non-cognitive factors. Achievement could be predicted by cognitive and background factors and by conscientiousness, self-efficacy and test anxiety. Moreover, the predictive power of variables varied across study programs, which suggests that research findings about the prediction of academic achievement might benefit from taking into account the specific program context. Practical implications for research and (educational program choice) counselling of students are discussed.
Choice is what enables each person to pursue precisely those objects and activities that best satisfy his or her own preferences within the limits of his or her resources. This chapter argues that choice, and with it freedom, autonomy, and self-determination, can become excessive, and that when that happens, freedom can be experienced as a kind of misery-inducing tyranny. Though one cannot be free without choice, it is arguable that choice-induced paralysis is a sign of diminished rather than enhanced freedom. Though policy initiatives can operate to minimize the negative effects of choice overload, they contain the danger that they will simultaneously undermine the positive effects of freedom of choice. The reason people can say anything and be understood is that they cannot say anything in any way they want. It is linguistic constraint, in the form of these rules, that makes linguistic freedom possible.
This study draws upon social cognitive career theory and higher education literature to test a conceptual framework for understanding the entrance into science, technology, engineering, and mathematics (STEM) majors by recent high school graduates attending 4-year institutions. Results suggest that choosing a STEM major is directly influenced by intent to major in STEM, high school math achievement, and initial postsecondary experiences, such as academic interaction and financial aid receipt. Exerting the largest impact on STEM entrance, intent to major in STEM is directly affected by 12th-grade math achievement, exposure to math and science courses, and math self-efficacy beliefs-all three subject to the influence of early achievement in and attitudes toward math. Multiple-group structural equation modeling analyses indicated heterogeneous effects of math achievement and exposure to math and science across racial groups, with their positive impact on STEM intent accruing most to White students and least to underrepresented minority students.
In this study, a theoretical model is tested to examine factors shaping the decision to pursue STEM fields of study among students entering community colleges and four-year institutions, based on a nationally representative sample of high school graduates from 2004. Applying the social cognitive career theory and multi-group structural equation modeling analysis, this research highlights a number of findings that may point to specific points of intervention along students’ educational pathway into STEM. This study also reveals important heterogeneity in the effects of high school and postsecondary variables based on where students start their postsecondary education: community colleges or four-year institutions. For example, while high school exposure to math and science courses appears to be a strong influence on four-year beginners’ STEM interest, its impact on community college beginners’ STEM interest, albeit being positive, is much smaller. In addition, college academic integration and financial aid receipt exhibit differential effects on STEM entrance, accruing more to four-year college students and less to those starting at community colleges.
In a replication and extension of earlier research, we examined the explanatory adequacy of the social cognitive choice model (Lent, Brown, & Hackett, 1994) in a sample of 1404 students majoring in a variety of computing disciplines at 23 historically Black and 27 predominantly White universities. Participants completed measures of self-efficacy, outcome expectations, interests, goals, and social supports and barriers relative to the pursuit of computing degrees. The social cognitive model generally provided adequate fit to the data across two academic year cohorts (2006, 2007), gender, institutional setting, racial/ethnic groups (European and African Americans), and educational level (beginning and advanced undergraduates). Outcome expectations, however, did not contribute uniquely to the predictive model. Implications for further research on social cognitive theory in the context of science and technology fields are discussed.
During adolescence, one important career-related decision is the choice of a study in higher education. In this article, a new set of measures for different tasks (i.e., orientation, exploration, commitment) that can be distinguished during this career decision-making process was constructed: the Study Choice Task Inventory (SCTI). A sample of 946 high school students (Grade 11 and Grade 12) participated in this study. Results provided support for the construct validity of the SCTI from (a) the examination of the internal structure of the SCTI (confirmatory factor analysis), (b) the investigation of the convergent validity through correlations between the new scales and alternative measures of decisional tasks, and (c) the comparison of the scores across samples in a known-groups validation.
We tested the fit of the social cognitive choice model [Lent, R.W., Brown, S.D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance [Monograph]. Journal of Vocational Behavior, 45, 79–122] to the data across gender, educational level, and type of university among students in a variety of computing disciplines. Participants were 1208 students at 21 historically Black and 21 predominantly White universities. They completed measures of self-efficacy, outcome expectations, interests, goals, and social supports and barriers with respect to computing majors. The SCCT model yielded adequate fit to the data across each of the grouping variables. Implications for future research on SCCT’s choice hypotheses in the context of science and engineering-related fields are discussed.
On the occasion of the 70th anniversary of the Strong Interest Inventory (1927–1997), earlier known as the Strong Vocational Interest Blank, this article reviews the history of this landmark inventory and the legacy of E. K. Strong, Jr.; specifically, his development of the inventorying method and use of criterion-related scale development. The recent trend of content-related scale development is also reviewed. Recent innovations in the Strong and future directions for predicting career behavior are discussed. Overall, the early empirical work conducted by Strong created a sound foundation for predicting vocational behavior and for later innovations in career assessment. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
This is a response to an article by H. E. A. Tinsley (2000), who concludes that J. L. Holland's (1997) well-known and widely used hexagon lacks validity. Tinsley reached the conclusion chiefly on the basis of the results of studies correlating hexagon-based person–environment (P–E) congruence (fit) scores with job satisfaction scores. This response focuses on the need for job satisfaction scores that are relevant to P–E fit studies involving vocational interests rather than the general (global) job satisfaction scores that are typically used. Several ways for refining interest–satisfaction studies are suggested. A brief summary of interest structure research supporting Holland's hexagonal model as an approximation of reality is provided, and some possible improvements in the portrayal of interest structure are discussed.
The terrain of gender inequalities in education has seen much change in recent decades. This article reviews the empirical research and theoretical perspectives on gender inequalities in educational performance and attainment from early childhood to young adulthood. Much of the literature on children and adolescents attends to performance differences between girls and boys. Of course, achievement in elementary and secondary school is linked to the level of education one ultimately attains including high school completion, enrollment in postsecondary education, college completion, and graduate and professional school experiences.We recommend three directions for future research: (a) interdisciplinary efforts to understand gender differences in cognitive development and noncognitive abilities in early childhood, (b) research on the structure and practices of schooling, and (c) analyses of how gender differences might amplify other kinds of inequalities, such as racial, ethnic, class, or nativity inequalities.
This paper looks at the ICT (information and communication technology) curriculum in New Zealand secondary schools and gendered participation patterns in different specialist ICT subjects. New Zealand has a permissive ICT curriculum, comprising a variety of subjects and characterised by choice and variation in the curriculum in practice at the local level. The data that are reported include results of (i) a national questionnaire survey of secondary schools, and (ii) a qualitative case study conducted in a large, co-educational New Zealand secondary school and involving classroom observations and interviews with teachers and students. It is suggested that the permissiveness of the curriculum, which ostensibly caters for the needs of students by providing choices, may, in some circumstances, effectively reinforce gender stereotypes relating to computer interests and practices. This is a paradox of choice. Questions are raised about the nature of the ICT curriculum in New Zealand and how it may contribute to or challenge gender stereotypes, future curriculum developments and, more broadly, how we can account for persistent gendered participation patterns in ICT subjects in schools.
Holland uses a hexagon to model relationships among his six types of vocational interests. This paper provides empirical evidence regarding the nature of the interest dimensions underlying the hexagon. Two studies are reported. Study 1 examines the extent to which two theory-based dimensions—data/ideas and things/people—fit 27 sets of intercorrelations for Holland's types. Three of the data sets involve the mean scores of career groups (total of 228 groups and 35,060 individuals); 24 involve the scores for individuals (total of 11,275). Study 2 explores the heuristic value of the data/ideas and things/people dimensions by determining whether they contribute to the understanding of why interest inventories work. Two data sets covering a total of 563 occupations are used to calculate correlations between the vocational interests of persons and the tasks which characterize the persons' occupations. Each occupation's principal work tasks are determined from job analysis data obtained from the U.S. Department of Labor. Study 1 results provide substantial support for the theory-based dimensions. Study 2 results suggest that interest inventories “work” primarily because they tap activity preferences which parallel work tasks. Counseling and research applications of the data/ideas and things/people dimensions are suggested and implications for interest assessment are noted.