Science achievement of U.S. students has lagged significantly behind other nations; educational reformers have suggested science engagement may enhance this critical measure. The 2006 Program for International Student Assessment (PISA) was science-focused and measured science achievement along with nine aspects of science engagement: science self-efficacy, science self-concept, enjoyment of science, general interest in learning science, instrumental motivation for science, future-oriented science motivation, general value of science, personal value of science, and science-related activities. I used multilevel modeling techniques to address both aspects of science engagement and science achievement as outcome variables in the context of student background and school characteristics. Treating aspects of science engagement as outcome variables provided tests for approaches for their enhancement; meanwhile, treating science achievement as the outcome variable provided tests for the influence of the aspects of science engagement on science achievement under appropriate controls. When aspects of science engagement were treated as outcome variables, gender and father’s SES had frequent (significant) influences, as did science teaching strategies which focused on applications or models and hands-on activities over-and-above influences of student background and other school characteristics. When science achievement was treated as the outcome variable, each aspect of science engagement was significant, and eight had medium or large effect sizes (future-oriented science motivation was the exception). The science teaching strategy which involved hands-on activities frequently enhanced science achievement over-and-above influences of student background and other school characteristics. Policy recommendations for U.S. science educators included enhancing eight aspects of science engagement and implementing two specific science teaching strategies (focus on applications or models and hands-on activities). Focused implementation of these research findings could enhance both science engagement and science achievement of U.S. students. I identified five key limitations of my research project: the age of the dataset, the lack of racial/ethnic identifiers, the low proportion of student-level variance accounted for by multilevel models with aspects of science engagement as outcome variables, the lack of class-level measures, and the lack of inclusion of students’ epistemological and fixed/flexible beliefs. These limitations provide opportunities for further investigations into these critical issues in science education.

The purpose of this study was to examine belonging at classroom and academic domain levels, extending research that has primarily investigated general school and classroom-level belonging. This examination accounts for the context-specific, instructional, and domain experiences of students’ belonging. More specifically, the goals of the research were to investigate the relations between belonging in science class with engagement, and to contrast students’ perspectives of science classroom belonging in traditional compared to inquiry curricular contexts. Middle school students from traditional and inquiry science contexts completed self-reported measures of science classroom belonging and science engagement. Semi-structured interviews were conducted to evaluate students’ experiences of belonging in science class. Science classroom belonging was correlated with science engagement, with students from inquiry contexts reporting higher belonging and engagement quality. In both contexts, students reported common social, academic and contextual sources of belonging, with additional emphasis on content-based and interpersonal interactions. In comparing justifications between contexts on the role of competence for experienced belonging, students in traditional contexts reflected on self-focused, intrapersonal competence, while students in inquiry contexts reflected on interpersonal forms of competence. Students’ differentiated reports and conceptualization of belonging were related to contextual supports for involvement in authentic disciplinary practice and peer responsiveness.

Given the concentration of economic growth and power in science fields and the current levels of racial stratification in schooling, this study examined (1) the effects of race on students’ connectedness to science and career aspirations, (2) the extent to which these effects were moderated by school racial composition and racialized tracking, and (3) the differences in modeling effects using separate variables for race and gender (i.e., White, Black, Hispanic, female) versus race/gender (e.g., White female, Black male, etc.). Using the lens of racial formation theory, this study situated access to science knowledge as a racial project, conferring and denying access to resources along racial lines. Reviews of the literature on science self-efficacy, identity, engagement, and career aspirations revealed an under-emphasis on school institutional factors, such as racial composition and racialized tracking (which are important in sociological literature), as shaping student outcomes. The study analyzed data from the nationally representative High School Longitudinal Study that surveyed students in 2009 during their freshman year in high school and again in 2012 during most students’ junior year (n = 6,998). Affective ratings (in self-efficacy, identity, engagement) and career aspirations for students measured in 2012 were examined as dependent variables and a variable for racialized tracking was estimated given schools’ placement of students in advanced science coursework in 2012. Although school racial composition was not found to moderate race on outcome effects, primary analyses demonstrated that the presence of racialized tracking in the students’ schools did moderate these effects. Overall these results suggested that the student subgroups most often at a disadvantage compared to White students for the science outcomes studied were Hispanic males and females; Black students’ ratings and aspirations were largely on par or exceeded those of their White counterparts. In addition, results indicated that racialized tracking served to exacerbate gaps for Hispanic students and may also diminish career aspirations for Black students. Finally, while examining effects by race/gender did provide some additional insight and nuance in the interpretation of these results, there were clear instances where these more detailed analyses were not needed or may have obscured results that were clearer when aggregated by race. Given these results, implications for policy, practice, and future research are discussed. / Urban Education

[ES] La percepción pública de la ciencia es un aspecto social ampliamente estudiado mediante encuestas a la población para evaluar la comprensión de la ciencia y las actitudes hacia la misma. Sin embargo, existen críticas robustas hacia los supuestos teóricos que sustentan el diseño de estos sondeos y hacia la metodología empleada. La presente tesis pretende aportar vías de análisis más innovadoras a la discusión. En primer lugar, se proporciona un marco introductorio que esboza las relaciones más destacables entre ciencia y sociedad en el mundo moderno, incluyendo los enfoques de participación, considerados más democráticos. En segundo lugar, se profundiza en el marco del nuevo escenario de la vida digital, en particular con la finalidad de complementar los estudios clásicos de percepción social de la ciencia con la propuesta de una herramienta metodológica adaptada a la sociedad digital que abra nuevas direcciones de investigación orientadas hacia los espacios de participación ciudadana que constituyen las redes sociales digitales. Para ello, se diseña un algoritmo capaz de analizar tendencias en el impacto de la comunicación de la ciencia en Twitter a partir de conjuntos representativos de tuits utilizando técnicas computacionales de minería de datos, combinadas con una valoración cualitativa de los tipos de contenido ¿categorizado como: «ciencia», «cultura», «político-social», «creencias», «medios» y «emocional»¿. Para probar la herramienta, se examina una variedad de discursos en abierto sobre temas científicos presentes en la plataforma, aplicando el algoritmo sobre perfiles de distinta naturaleza ¿científicos famosos, instituciones y otros¿ y sobre conversaciones no centralizadas en usuarios específicos, sino recabando la información relativa a cuestiones científicas de las que los medios se han hecho eco. El resultado es una herramienta de bajo coste fácilmente reproducible por otros investigadores que revela aspectos sobre las estrategias de comunicación científica que generan mayor impacto. Se requerirán estudios más profundos, a gran escala, para corroborar si las tendencias preliminares identificadas con el método de análisis propuesto pueden extrapolarse a un marco más general. / [EN] Public perception of science is a widely studied social aspect through population surveys to assess understanding of science and attitudes towards it. However, there are strong criticisms of the theoretical assumptions behind the design of these surveys and the methodology used. This thesis aims to provide more innovative ways of analysis to the discussion. Firstly, it provides an introductory framework outlining the most remarkable relationships between science and society in the modern world, including approaches to 'engagement' in science, which are considered to be more democratic. Secondly, it delves into the framework of the new scenario of digital life, in particular with the aim of complementing the classic studies of the social perception of science with the proposal of a methodological tool adapted to the digital society that opens up new directions of research oriented towards the spaces of citizen participation that constitute social networks. To this end, an algorithm is designed that is capable of analyzing the impact of science communication on Twitter from representative sets of tweets using computational data mining techniques, combined with a qualitative assessment of the types of content; categorized as «science», «culture», «political-social», «beliefs», «media» and «emotional». To test the tool, a variety of open discourses on scientific topics present in the platform are examined, applying the algorithm on profiles of different nature (famous scientists, institutions and others) and on conversations not centralized on specific users, but gathering information on scientific issues that have been echoed by the media. The result is a low-cost tool that can be easily reproduced by other researchers and that reveals aspects about the science communication strategies that generate the greatest impact. As a next step, more in-depth, large-scale studies are required to corroborate whether the preliminary trends identified with the proposed method of analysis can be extrapolated to a more general framework. / [CA] La percepció pública de la ciència és un aspecte social àmpliament estudiat mitjançant enquestes a la població per avaluar la comprensió de la ciència i les actituds de la ciutadania. No obstant això, hi ha crítiques robustes cap als supòsits teòrics que sustenten el disseny d'aquests sondejos i cap a la metodologia utilitzada. La present tesi pretén aportar vies d'anàlisi més innovadores a la discussió. En primer lloc, es proporciona un marc introductori que esbossa les relacions més destacables entre ciència i societat en el món modern, incloent els enfocaments de participació ¿o engagement¿, considerats més democràtics. En segon lloc, s'aprofundeix en el marc de el nou escenari de la vida digital, en particular amb la finalitat de complementar els estudis clàssics de percepció social de la ciència amb la proposta d'una eina metodològica adaptada a la societat digital que obri noves direccions de investigació orientades cap als espais de participació ciutadana que constitueixen les xarxes socials. Per a això, es dissenya un algoritme capaç d'analitzar l'impacte de la comunicació de la ciència a Twitter a partir de conjunts representatius de tuits utilitzant tècniques computacionals de mineria de dades, combinades amb una valoració qualitativa dels tipus de contingut ¿categoritzat com: «ciència», «cultura», «politicosocial», «creences», «mitjans» i «emocional»¿. Per provar l'eina, s'examina una varietat de discursos en obert sobre temes científics presents a la plataforma, aplicant l'algoritme sobre perfils de diferent naturalesa ¿científics famosos, institucions i altres¿ i sobre converses no centralitzades en usuaris específics, sinó recaptant la informació relativa a qüestions científiques de les que els mitjans de comunicació s'han fet ressò. El resultat és una eina de baix cost fàcilment reproduïble per altres investigadors que revela aspectes sobre les estratègies de comunicació científica que generen major impacte. Com següent pas, es requereixen estudis més profunds, a gran escala, per corroborar si les tendències preliminars identificades amb el mètode d'anàlisi proposat poden extrapolar-se a un marc més general. / Denia Navarro, E. (2020). Percepción social de la ciencia y participación digital: impacto de la comunicación científica en Twitter [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/153797 / TESIS