Conceptualizing Science Identity: Its Nature and the Gendered Role It Plays in Early Secondary Students’ Science Choices

Research on the persistence of minoritized populations within science trajectories has often highlighted identity as a particularly important factor in those choices (Archer et al., 2010; Barton & Calabrese, 2007; Barton et al., 2013; Merolla & Serpe, 2013). However, identity has often been studied from a qualitative perspective or in college populations. To push the field forward by addressing several key open questions, this dissertation consists of three quantitative studies that I argue have deepened and broaden the field of science identity. A central underlying goal of this dissertation is to address the issue of equity in science, with a particular focus on patterns of marginalization through the lens of science identity that emerge in early secondary school, particularly gender. These results are consistent with the lack of representation and power of minoritized populations in science careers. The first empirical paper clarifies the nature of science identity as integrating internal and external recognition components and establishes it as different from other attitudinal variables. The second study provides the framework of topical identity complexes for studying the interaction of different topical identities. The empirical results reveal a surprising finding about which identity complexes involving science are (and are not) found in early secondary student as well as their impact of student’s choices. The third study focuses on understanding career affinities of early secondary school students and their relationship to science identity for both science and science-related careers. Finally, I also reflect on the use of quantitative methods in this work since such methods have been long critiqued for their inability to capture the nuance of everyday experience or further an equity agenda in education

The nature of science identity and its role as the driver of student choices

Abstract Background A major concern in science education involves the under-representation of many groups in science and technology fields, especially by gender (Brotman and Moore, J Res Sci Teach 45:971–1002, 2008; Clark Blickenstaff, Gend Educ 17:369–386, 2006), stemming from an intersection of systemic obstacles (Cantú, Equity Excell Educ 45:472–487, 2012; Rosa and Mensah, Phys Rev Phys Educ Res 12:020113, 2016). Research on persistence of minoritized populations within science trajectories has often highlighted identity as particularly important (Archer et al., Sci Educ 94:617–639, 2010; Barton and Calabrese, Am Educ Res J 50:37–75, 2007; Barton et al., Am Educ Res J 50:37–75, 2013; Merolla and Serpe, Soc Psychol Educ 16:575–597, 2013). Results This study quantitatively investigated the nature of science identity in over 1300 seventh and ninth grade students from a range of urban US public schools using survey data on science identity, choice preferences, and optional science experiences. Factor analyses validated this conceptualization of science identity as integrating perceived internal and external identity components. Regression analyses revealed the importance of this conceptualization of science identity for driving students’ choices at this crucial developmental period. Furthermore, science identity had a complex differential function in supporting students’ optional science choices by gender. Conclusions The novel contribution to the science identity field highlights the specific multi-component ways in which students endorse science identity in middle school and early high school. There was an important finding that science identity has a complex differential function in supporting student’s optional science choices by gender. Thus, at this age, developing a strong science identity is especially critical for girls

Activating discipline specific thinking with adaptive learning : A digital tool to enhance learning in chemistry

In tertiary science education, students are encouraged to engage in discipline specific thinking, to learn their chosen subject. The challenge for educators is engaging all students equitably, despite their educational backgrounds and depth of discipline specific knowledge. Personalising learning in the context of large-scale tertiary courses can only be achieved by using digital technologies. In the context of chemistry education, this project has investigated how an adaptive learning technology can effectively and consistently engage students in discipline specific thinking, by personalising their learning pathway. Adaptive learning has been integrated into a foundational chemistry subject and through quantitative analysis there is empirical evidence to support the benefit adaptive learning has on outcomes, in both the short and long term. This study shows adaptive learning can equitably meet the needs for all students and can lead to improvements in educational behaviour beyond grades. The evidence supports adaptive learning as one critical tool for chemistry educators, and educators in other disciplines of science, to include in their suite of pedagogical strategies to meet the needs of all their students.</p

Measuring the skills that predict learning in middle school science

<p>Poster presented at "Measuring Scientific Reasoning and Argumentation" Spring School 2015 at Munich. First results on how measuring scientific sense making predicts learning in a science classroom and firsts attempts at scale validation</p

Multivariate regression estimates comparing the effect of App Usage with Disciplinary Engagement.

Multivariate regression estimates comparing the effect of App Usage with Disciplinary Engagement.</p

Estimated marginal means for the final grade in CHEM102.

Predicted by their incoming CHEM101 grade and their level of engagement with adaptive learning.</p

Effect of opting-in adaptive learning intervention on CHEM102 scores.

Effect of opting-in adaptive learning intervention on CHEM102 scores.</p

Histogram showing the relationship between level reached on the Cerego app and number of students.

Histogram showing the relationship between level reached on the Cerego app and number of students.</p

A representation of the learning path in Cerego.

Pathways for two different concepts for a single student, showing how the software can adaptively modulate the time of review based on a student’s level of understanding.</p

GK<i>τ</i> across all categorical variables.

GKτ across all categorical variables.</p