(PDF) Argument-Driven Engineering in Middle School Science: An Exploratory Study of Changes in Engineering Identity Over an Acad

Journal of Pre-College Engineering Education Research (J-PEER) Volume 9 Issue 2 Article 6 2019 Argument-Driven Engineering in Middle School Science: An Exploratory Study of Changes in Engineering Identity Over an Academic Year Lawrence Chu The University of Texas at Austin,

Victor Sampson The University of Texas at Austin,

Todd L. Hutner The University of Alabama,

See next page for additional authors Follow this and additional works at: https://docs.lib.purdue.edu/jpeer Part of the Curriculum and Instruction Commons, Engineering Education Commons, Science and Mathematics Education Commons, and the Secondary Education Commons Recommended Citation Chu, L., Sampson, V., Hutner, T. L., Rivale, S., Crawford, R. H., Baze, C. L., & Brooks, H. S. (2019). Argument- Driven Engineering in Middle School Science: An Exploratory Study of Changes in Engineering Identity Over an Academic Year. Journal of Pre-College Engineering Education Research (J-PEER), 9(2), Article 6. https://doi.org/10.7771/2157-9288.1249 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact

for additional information. This is an Open Access journal. This means that it uses a funding model that does not charge readers or their institutions for access. Readers may freely read, download, copy, distribute, print, search, or link to the full texts of articles. This journal is covered under the CC BY-NC-ND license. Argument-Driven Engineering in Middle School Science: An Exploratory Study of Changes in Engineering Identity Over an Academic Year Abstract The goal of this study was to examine how the use of a new instructional model is related to changes in middle school students’ engineering identity. The intent of this instructional model, which is called argument-driven engineering (ADE), is to give students opportunities to design and critique solutions to meaningful problems using the core ideas and practices of science and engineering. The model also reflects current recommendations found in the literature for supporting the development or maintenance of engineering identity. This study took place in the context of an eighth-grade science classroom in order to explore how middle school students’ engineering identities change over time as they become more familiar with engineering core ideas and practices. One hundred students participated in this study. These students completed three design tasks during the school year that were created using the ADE instructional model. These students also completed a survey that was designed to measure two important aspects of an engineering identity (recognition and interest) at three different time points. The results of a hierarchical linear modeling analysis suggest that students’ ideas about how they view themselves and others view them in terms of engineering did not change over time and their reported interest decreased from one survey to the next. The difficulty of the design tasks and the ways teachers enacted the instructional model are proposed as potential explanations for this counterintuitive finding. Keywords engineering education, middle school, attitudes, science and engineering practices, argumentation, instructional model Document Type Invited Contributions: Best Papers from ASEE Pre-College Engineering Education Authors Lawrence Chu, Victor Sampson, Todd L. Hutner, Stephanie Rivale, Richard H. Crawford, Christina L. Baze, and Hannah S. Brooks This invited contributions: best papers from asee pre-college engineering education is available in Journal of Pre- College Engineering Education Research (J-PEER): https://docs.lib.purdue.edu/jpeer/vol9/iss2/6 Available online at http://docs.lib.purdue.edu/jpeer Journal of Pre-College Engineering Education Research 9:2 (2019) 72–84 Argument-Driven Engineering in Middle School Science: An Exploratory Study of Changes in Engineering Identity Over an Academic Year Lawrence Chu,1 Victor Sampson,1 Todd L. Hutner,2 Stephanie Rivale,3 Richard H. Crawford,1 Christina L. Baze,1 and Hannah S. Brooks1 1 The University of Texas at Austin 2 The University of Alabama 3 The University of Texas at San Antonio Abstract The goal of this study was to examine how the use of a new instructional model is related to changes in middle school students’ engineering identity. The intent of this instructional model, which is called argument-driven engineering (ADE), is to give students opportunities to design and critique solutions to meaningful problems using the core ideas and practices of science and engineering. The model also reflects current recommendations found in the literature for supporting the development or maintenance of engineering identity. This study took place in the context of an eighth-grade science classroom in order to explore how middle school students’ engineering identities change over time as they become more familiar with engineering core ideas and practices. One hundred students participated in this study. These students completed three design tasks during the school year that were created using the ADE instructional model. These students also completed a survey that was designed to measure two important aspects of an engineering identity (recognition and interest) at three different time points. The results of a hierarchical linear modeling analysis suggest that students’ ideas about how they view themselves and others view them in terms of engineering did not change over time and their reported interest decreased from one survey to the next. The difficulty of the design tasks and the ways teachers enacted the instructional model are proposed as potential explanations for this counterintuitive finding. Keywords: engineering education, middle school, attitudes, science and engineering practices, argumentation, instructional model Introduction An important first step in any effort to increase the number of people who pursue a science, technology, engineering, and mathematics (STEM) degree is to ensure that all students have access to a high-quality STEM education in grades K-12 (National Academies of Sciences, Engineering, and Medicine [NASEM], 2019). One way to ensure that all students have access to a high-quality STEM education is to develop and adopt new academic standards for grades K-12 that require teachers to help students learn to use the core ideas and practices of science, computer science, engineering, and mathematics to explain the world or develop solutions to problems. For example, the new Framework for K-12 Science Education, which was used to develop the Next Generation Science Standards (NGSS; NGSS Lead States, 2013), was written, in part, ‘‘to provide all students with a fair opportunity to learn’’ (National Research Council, 2012, p. 282). http://dx.doi.org/10.7771/2157-9288.1249 1 L. Chu et al. / Journal of Pre-College Engineering Education Research 73 Any effort to increase students’ access to a high-quality highlighting the implications of this study for future STEM education through the use of new academic stan- research and instructional design. dards, however, will not do much to increase the number of individuals who decide to pursue a STEM degree if the Theoretical Framework: Engineering Identity learning experiences that take place in grades K-12 put some students at a disadvantage or hinder the development Our theoretical framework starts with the assumption or maintenance of STEM interests, aspirations, or identity that choices regarding college major and career pathways (e.g., Penuel, 2016; Philip & Azevedo, 2017). It is therefore are influenced by the disciplinary identity of the student important to develop new curricular materials and instruc- (e.g., Godwin, Potvin, Hazari, & Lock, 2013; Jones, tional approaches that will not only increase access and Osborne, Paretti, & Matusovich, 2014). That is, when a opportunities to learn engineering core ideas and practices student holds a ‘‘strong’’ engineering identity, they are but also do so in a way that is equitable and inclusive likely to pursue engineering majors upon entering college (Moore, Stohlmann, Wang, Tank, & Roehrig, 2014; Natio- and to seek employment as an engineer upon entering the nal Academy of Engineering & National Research Council, workforce. Conversely, when students hold a ‘‘weak’’ or 2009; NASEM, 2019; Purzer, Moore, Baker, & Berland, non-existent engineering identity, they are less likely to 2014). major in engineering or to seek out an engineering or engi- With this goal in mind, our group has developed a new neering-related career. An engineering identity is shaped by instructional model, called argument-driven engineering experiences and repeated interactions with others. (ADE), that gives students an opportunity to use the core There are numerous ways to define engineering identity. ideas, crosscutting concepts, and the practices of science Morelock (2017), for example, described four perspectives and engineering to develop solutions to meaningful pro- that researchers often use to define engineering identity. blems. In order to ensure that all students have access to These perspectives include definitions that are based on: STEM experiences in middle school, we designed this 1. other aspects of individuals’ identities, instructional model so it can be used in science classrooms 2. individuals’ self-perceptions and perceptions of engi- rather than in an engineering course. In contrast to engi- neering as a profession, neering classes, which are typically offered as elective 3. a set of cognitive, affective, and performance-related courses, science courses are required for all students. As variables, and such, we decided to develop an instructional model that can 4. the agency of individuals within the engineering be used in science classrooms because it increases the profession. likelihood that all students enrolled in a school, and not just a select few, will have an opportunity to gain familiarity We situate our definition of identity in the third with the nature of engineering. We also designed this perspective, where identity comprises a set of cognitive, instructional model so that it reflects current recommenda- affective, and performance-related variables. For the tions found in the literature about ways to improve student purposes of the study, we define identity as comprising attitudes toward engineering (Committee on K-12 Engi- of two variables. These variables, which are adapted from neering Education, 2009) and ways to encourage young Godwin, Potvin, Hazari, and Lock (2016), include engi- people, particularly girls and under-represented minorities, neering recognition and engineering interest. to consider engineering as a career option (National Aca- We define engineering recognition as the degree to demy of Engineering [NAE], 2008). The purpose of this which students perceive their parents, teachers, and friends study was to explore how students’ engineering identity as recognizing them as an engineer. Such forms of external changed over time as they completed a series of design recognition have been shown to predict students’ identity in challenges following the ADE instructional model in order both mathematics and physics (Cass, Hazari, Cribbs, Sadler, to conduct an initial test of its potential and promise as a & Sonnert, 2011; Hazari, Sonnert, Sadler, & Shanahan, way to increase access and ensure opportunities to learn 2010) and have been shown to have a similar explanatory engineering core ideas and practices are equitable and impact in engineering as well (Godwin et al., 2013). Parents’ inclusive. perceptions of their students’ disciplinary abilities affect In the sections that follow, we first define engineering students’ self-perceptions of their own ability (Bleeker & identity in light of the frameworks most relevant to this Jacobs, 2004; Smith, 1991; Turner, Stewart, & Lapan, 2004). study. We then review the literature of the impact of K-12 Teachers, too, impact students’ eventual career choices, engineering experiences on student engineering identity. particularly in the physical sciences and for female students Thirdly, we provide the research question guiding our in high school (Ivie, Cuzjko, & Stowe, 2001). And even study. We then detail the methods for data collection and when parental influence on identity is absent, the perception analysis. Next, we provide the results of our study. Finally, of being recognized by friends for one’s ability in the domain we conclude the article by discussing the findings in light plays an important explanatory role in eventual interest in the of the literature on pre-collegiate engineering education and field (Speering & Rennie, 1996). http://dx.doi.org/10.7771/2157-9288.1249 2 74 L. Chu et al. / Journal of Pre-College Engineering Education Research We define engineering interest as the degree to which example, Beam, Pierrakos, Constantz, Johri, and Anderson students find interest in doing engineering. We postulate (2009) conducted focus group interviews with under- the more interested a person is in a domain (e.g., engi- graduate freshmen and utilized a case study approach to neering, quilting, hiking, etc.), the more frequently they better understand the development of professional engi- will spend time engaging with that domain. And, the more neering identity. They found that the strength of the time one spends engaging with a domain, the more one relationship between students’ engineering identities and identifies as a member of that community. In the context of the degree to which they related to the engineering pro- engineering, the more interested a student is in engineering, fession came from those students’ exposure to and the more they will choose to engage in engineering familiarity with engineering, particularly through formal experiences. And, the more time the student spends doing and informal engineering experiences during their pre- engineering, the stronger their engineering identity will college education. Their identities were also dependent on become. their knowing of or being introduced to an engineer during Engineering identity formation or maintenance is an that period of time. The study noted limitations of not important outcome to consider when attempting to increase having longitudinal data on identity development and of the number of girls and students of color who pursue lacking broader sampling across educational settings, as all engineering degrees upon entering college (McCave, participants came from a single institution. Additionally, Gilmore, & Burg, 2014) and to promote a more diversified while helpful in exploring some of the constructive factors engineering workforce (National Science Foundation, potentially contributing to the development of engineer- 2017). Individuals’ identities develop from the ways they ing identity, the methodological constraint of only using learn in different settings and based on the cultural beliefs case studies and solely sampling undergraduate students that result from participating in those environments does little to provide empirical evidence of the effective (Holland, 2001; Stevens, O’Connor, Garrison, Jocuns, & implementation of its findings among pre-college student Amos, 2008). Tonso (2014) explains how, at the post- populations. secondary level, engineering campuses frame the develop- Another study by Danforth, Lam, Mehrpouyan, and ment of students’ engineering identity, and the programs Hughes (2016) did focus on high school students and in which students participate serve as experiences which utilized a summer outreach program geared toward encou- influence their engineering identity. As a result, these raging college participation and the pursuit of engineering programs hold the power to influence which behaviors are degrees. Those authors found that, as a result of the perceived as desirable and which define what it means to be program, students’ interest in attending the university an engineer over others. In other words, certain behaviors associated with the study increased on a survey of student are viewed as ‘‘things engineers do’’ and, when a person attitudes. Also, students’ engineering content knowledge, exhibits these behaviors, they are perceived as being an as demonstrated on a self-developed instrument, increased engineer. For example, social skills, which are negatively from pre- to post-test. While the findings may provide perceived as being feminine qualities (Faulkner, 2007; useful information for the implementation of this specific Tonso, 2007), are often devalued in engineering commu- summer program, the study was limited by the use of non- nities. Yet, social skills are viewed as increasingly impor- validated instruments in the measurement of student atti- tant for engineers in the modern work environment. tudes and engineering knowledge. Also, given the nature of Given the importance of social forces such as these for the program, findings from the study may only be relevant the development or maintenance of engineering identity, to students who voluntarily selected to participate in the asset-based perspectives used early on in an individual’s summer outreach, limiting their application in formal K-12 education can serve to provide beneficial engineering learn- settings. ing experiences for girls and students of color (Llewellyn Using a different approach, Baldwin, Daniel, and et al., 2016). The use of educational experiences that value Williams (2016) developed an engineering design course the cultural and social capital of all students, along with the for middle school and high school students that met over various knowledges and backgrounds that students bring ten Saturdays for two hours each week. The course with them is a way to provide an environment that supports introduced students to the engineering design process and the positive development of all students’ engineering focused on the development of ‘‘teamwork, problem solv- identities. This is something that the ADE framework ing, and verbal communication skills’’ (p. 2). It involved seeks to emphasize in its design and implementation in five design projects that incorporated research components middle school science classrooms. and design criteria and constraints. The authors showed that students’ engineering interest and self-efficacy was main- Literature Review tained during the course and that students also improved their understanding of engineering and of what engineers Others have looked at identity as being influential in do. As noted by the authors, the study looked to eventually college and career choice relating to engineering. For implement the courses more broadly and to study the http://dx.doi.org/10.7771/2157-9288.1249 3 L. Chu et al. / Journal of Pre-College Engineering Education Research 75 particular aspects of the program associated with the using the ADE instructional framework—during a science attitudinal gains. As a weekend course, questions still course affect students’ engineering identity over time? remain with regards to what implementation at the formal classroom level would look like for all students. Methods Along these lines, Lachapelle and Cunningham (2017) used an engineering curriculum implemented across a ADE Overview number of participating elementary schools. Their ‘‘treat- ment’’ curriculum had students engage with design chal- The ADE instructional model is unique among efforts to lenges that required the use of scientific ideas. While the increase access to engineering experiences for students in treatment condition received a more open-ended, authenti- three important ways. First, it is intended to be implemen- cally based experience of engineering, the ‘‘comparison’’ ted in science classes and not as a standalone elective. curriculum lacked a design challenge context and was Thus, all students have an opportunity to participate in implemented in a more closed-ended, directed instruction engineering design. Second, ADE is different from what is format (p. 3). Results from the study showed that students generally seen in the literature in that the framework fits participating in the treatment curriculum demonstrated a within a two-week period, not an entire semester as prior higher enjoyment, desire to learn, and valuation of engi- design-based instructional frameworks require. Finally, neering than those in the comparison group. While this ADE places a unique emphasis on argumentation and study took place in elementary classrooms and utilized writing, in line with the NGSS engineering practices of instruments that were tested for reliability through the use arguing from evidence and obtaining, evaluating, and of factor models, it lacked discussion of the particular curri- communicating information (NGSS Lead States, 2013). cular and pedagogical elements that may have contributed The ADE model serves as a template for the implemen- to the gains seen on these attitudinal measures. tation of STEM design challenges (SDCs) that are This research, when taken together, suggests a need to compatible with middle school science courses. ADE study the identity formation of middle school students as specifies a sequence of activities that allow students to they participate in engineering design within a science engage in engineering design by incorporating disciplinary class. Prior work often focuses on identity formation in core ideas and mathematics principles, use evidence-based older students, yet career identity formation starts much argumentation to develop and critique design solutions, and earlier than high school (Turner & Lapan, 2005). Work participate in collaborative and individual learning through with younger students often is situated in out-of-school writing and discourse. An SDC is the context through contexts, thereby limiting the applicability of this work to which students participate in the ADE instructional frame- students who have access to such extracurricular opportu- work. That is, an SDC specifies the problem that students nities. Thus, research is needed on the formation of engi- need to solve (e.g., developing a highway crash safety neering identity in science classes when students participate barrier) and highlights ways that the solution to the problem in engineering design. benefits others. The ADE instructional framework consists of eight stages (see Table 1). These stages are introducing Purpose of the Study and Research Questions the problem, concept generation, concept selection, design argumentation, design testing, evaluation argumentation, The objective of this study is to examine participation in ADE in relation to changes in middle school students’ Table 1 STEM design challenge (SDC) stages. engineering identity over time. This study of engineering identity is important not only for developing new curricula SDC stage General components and pedagogy for engineering in science classrooms, but Introducing the problem N Provide design challenge also for addressing nationwide problems with diverse N Identify needs and constraints representation and participation in engineering degree Concept generation N Research the problem N Generate concepts programs and occupations. This current study contributes Concept selection N Determine criteria for evaluation to the current base of knowledge in that it takes place in the N Concept evaluation context of a middle school science classroom and provides Design argumentation N Concept design argument engineering experiences to all students in the class. It is N Critique and feedback predicted that, as students become more familiar with and Design testing N Iterations of the design N Testing and evaluation grow in their ability to participate in the practices that Evaluation argumentation N Design evaluation argument engineers use and apply in their professional work, those N Critique and feedback students will identify more as central members of the Report development N Written report scientific and engineering community. Given this objective, N Critique and feedback Reflection and discussion N Reflect on product and process the research question guiding this study is: How does N Develop plans for future work participation in three STEM design challenges—developed http://dx.doi.org/10.7771/2157-9288.1249 4 76 L. Chu et al. / Journal of Pre-College Engineering Education Research report development, and reflection and discussion. Imple- over 1,000 students. The student body is 39% Hispanic, mentation of all eight stages of the ADE instructional 36% White, 14% African American, and 5% Asian. In this framework involves active student engagement in science school, 32% are eligible for free or reduced-price lunch, and engineering practices. Depending on teacher imple- and 8.5% of the students are English language learners. mentation, each SDC takes 300–400 minutes to complete. It is located near a large metropolitan city known for being ADE provides teachers with a way to emphasize the use a major hi-tech center. of core ideas and practices of engineering, mathematics, Two teachers at the school agreed to participate in the and science to develop a solution to a problem. A key study. One teacher is a middle-aged African American feature of this instructional model is the provision of mul- woman who has been a teacher at the school for three years tiple opportunities for students to participate in argumen- and had previously worked as a researcher in a science tation. Here, ‘‘argumentation’’ is used to describe the industry. The other teacher is a middle-aged White male process of proposing, supporting, challenging, and refin- who taught for over 20 years in a private school prior to ing claims (Sampson & Clark, 2008). This focus on working at this school. argumentation during the engineering design process encourages students to focus on ‘‘how they know what Sample they know’’ as they develop, evaluate, and refine solutions to problems. Furthermore, this instructional model encourages A total of 103 students from the two teachers’ classes students to use evidence-based decision-making and exposes assented and received parental consent to participate in this students to the knowledge-building practices of the scientific study. All of these students participated in the SDCs in their and engineering community (Bricker & Bell, 2008; Duschl, classes. However, only 75 students completed all three Schweingruber, & Shouse, 2007). surveys and answered the demographic questions. Student ADE is unique in that it is intentionally developed to be demographics of this sample are available in Table 3. We an instructional model and not a specific curriculum. As an did not include a comparison group because our objective instructional model, it can be used as a template for other in this exploratory study was to examine changes in student curriculum developers, which is important since teachers engineering identity as a first test of promise and potential often adapt curricula in ways that deviate from the research- of this new approach. based principles with which those curricula initially aligned (Cronin-Jones, 1991; McLaughlin, 2006). The design of Data Collection the instructional model is intended to optimize widespread adoption, in light of teacher and classroom limitations, thus The survey instrument used for this study was adopted maximizing student learning of engineering. from the items developed by Godwin (2016) for the measurement of engineering identity. The three latent Context constructs tested in the original scale were recognition (e.g., ‘‘My parents see me as an engineer’’; Cronbach’s alpha 5 We developed four SDCs using the ADE instructional 0.77), interest (e.g., ‘‘I am interested in learning more about model, with each SDC corresponding to one of the four engineering’’; Cronbach’s alpha 5 0.89), and performance/ NGSS student performance expectations for middle school competence (e.g., ‘‘I am confident that I can understand that specifically incorporate engineering practices. The data engineering in class’’; Cronbach’s alpha 5 0.88). The author we report in this paper are related to three of the four SDCs: reported good model fit via overall fit indices (CFI 5 0.96; Developing a Passive Vaccine Storage Device, Developing TLI 5 0.95; RMSEA 5 0.077). a Hand Warmer for Homeless Individuals, and Developing The survey was administered at three time points. This a Biodiversity Monitoring Device. Table 2 lists each SDC first administration was before students started the first along with the NGSS disciplinary core ideas and engineer- SDC, the second administration of the survey took place ing standards covered by each. after the second SDC, and the final administration was after The three SDCs were implemented in all eighth-grade the students finished the third SDC. Although teachers science classes in two middle schools in a southern state were asked to give surveys as soon as possible after of the USA. These two schools were selected because of finishing an SDC, surveys were generally administered a pre-existing relationship between the researchers and the within two weeks of SDC completion. The period of time school district. The district recommended working with between Surveys 1 and 2 was eight weeks, and the time the selected schools because both the principals and the between Surveys 2 and 3 was twelve weeks. teachers were generally receptive to implementing novel and innovative instructional practices. Data from this study Data Analysis come from one of the two middle schools—Delorean Middle School (DMS). DMS is located in a city with a Responses on the survey were scored from 0 to 6, with population of just over 100,000. It has an enrollment of 0 representing strongly disagree, and 6 strongly agree. http://dx.doi.org/10.7771/2157-9288.1249 5 Table 2 Description of the four STEM design challenges (SDCs). SDC Performance expectations Disciplinary core ideas Science and engineering practices Developing a Passive Vaccine MS-PS3-3: Apply scientific Energy is spontaneously transferred out of N Designing solutions Storage Device principles to design, construct, hotter region or objects and into colder ones ˚ Undertake a design project to construct a solution that meets and test a device that either specific needs and constraints minimizes or maximizes thermal ˚ Evaluate potential designs based on prioritized criteria energy transfer N Planning and carrying out investigations ˚ Plan an investigation and identify independent and dependent variables and controls, what tools are needed to do the gathering, how measurements will be recorded, and how many data are needed Developing a Hand Warmer for MS-PS1-6: Undertake a design Some chemical reactions release energy, N Analyzing and interpreting data Homeless Individuals project to construct, test, and others absorb and store energy L. Chu et al. ˚ Apply concepts of statistics to analyze and use graphical displays modify a device that either to characterize trends or relationships in data releases or absorbs thermal energy N Designing solutions by chemical processes ˚ Optimize performance of a design by prioritizing criteria, making tradeoffs, and revising a design N Engaging in an argument from evidence ˚ Make a written argument that supports the performance of a device based on empirical evidence concerning whether or not the technology meets relevant criteria and constraints Developing a Biodiversity MS-LS2-5: Evaluate competing Biodiversity describes the variety of species N Analyzing and interpreting data Monitoring Device design solutions for maintaining found in Earth’s terrestrial and oceanic ˚ Apply concepts of statistics to analyze and use graphical displays biodiversity and ecosystem ecosystems. The completeness or integrity to characterize trends or relationships in data services of an ecosystem’s biodiversity is often used N Designing solutions as a measure of its health ˚ Optimize performance of a design by prioritizing criteria, making tradeoffs, and revising a design http://dx.doi.org/10.7771/2157-9288.1249 N Engaging in an argument from evidence ˚ Make a written argument that supports the performance of a device based on empirical evidence concerning whether or not the technology meets relevant criteria and constraints / Journal of Pre-College Engineering Education Research Developing a Highway Crash MS-PS2-1: Apply Newton’s third law For any pair of interacting objects, the force exerted N Designing solutions Safety Barrier to design a solution to a problem by the first object on the second object is equal ˚ Undertake a design project to construct a solution that meets involving the motion of two in strength to the force that the second object specific needs and constraints colliding objects exerts on the first, but in the opposite direction N Planning and carrying out investigations ˚ Evaluate potential designs based on prioritized criteria ˚ Plan an investigation and identify independent and dependent variables and controls, what tools are needed to do the gathering, how measurements will be recorded, and how many data are needed Note. Under ‘Science and engineering practices,’ solid bullets points denote relevant practices while open bullet points represent the components of the practices aligned to each SDC. 77 6 78 L. Chu et al. / Journal of Pre-College Engineering Education Research Prior to the main analysis, an exploratory factor analysis it addresses the effect of individual variables on the status was conducted for the original 11 items (using scores from of outcomes at time 5 0 (defined by the researcher). We Survey 1) to combine related items and create composite decided to use hierarchical linear modeling for the growth scores. The purpose of the exploratory factor analysis was curve analysis because it allows for unequal time intervals to confirm the constructs under which these items factored and nonsynchronous measurement of repeated measures in the original measurement tool (Godwin, 2016) and to (Raudenbush & Bryk, 2002). better understand how the latent constructs underlying the Student survey data were input into SPSS as two items were impacted by the addition of new items and the separate SPSS files, one for each level of analysis. Level 1 exclusion of certain others from the original tool. data comprise repeated measures, which are within-persons We identified six items that measure two different factors occasions, with time being the only predictor. Each student (see Table 4) that are aligned with our theoretical frame- was assigned a summarized rating score at each time point work. The first factor is engineering recognition. This for both recognition and interest, a score that equals the factor measures the degree to which students identify mean of the items factoring under each respective construct themselves and perceive their family, teacher, and friends (Carifio & Perla, 2008). Level 2 data include the student- as recognizing them as an engineer. Higher scores on level predictors which in this study included gender, coded this factor indicated a greater sense of recognition as an as female (dummy coded male 5 0, female 5 1); ethnicity, engineer. The second factor is engineering interest. This which included White, Hispanic/Latino, Black/African factor measures the degree to which students find interest in American, Native American/American Indian, Asian/Paci- doing engineering. Higher scores on this measure indicate fic Islander, other, and multiple, but which was recoded as greater degrees of interest in engineering. ethnicity_rec, dummy coded as 0 5 White, 1 5 all other We then conducted a growth curve analysis to examine ethnicities (Asian/Pacific Islander was originally grouped how engineering identity changed over time, specifically with White as a minority group over-represented in engi- on the factors of engineering recognition and engineering neering (National Science Foundation & National Center interest. We decided to use a growth curve analysis because for Science and Engineering Statistics, 2017). However, because the label included both Asian and Pacific Islander and the literature has shown the ‘‘Asian’’ label to be Table 3 problematic (Corwyn & Bradley, 2008; Kao, 1995), the Frequencies of student demographics. decision was made to keep Asian/Pacific Islander in a Demographic n % separate grouping); and knowing an engineer, coded as 0 5 knows an engineer, 1 5 does not know an engineer. The Sex Male 37 49% time variable was recoded (time_rec) such that the repeated Female 38 51% measures coded Survey 1 5 22, Survey 2 5 21, and Total 75 100% Survey 3 5 0. This way, the interpretation of the coefficient Race/ethnicity as associated with the expected outcome score when time 5 Asian/Pacific Islander 8 11% Black/African American 5 7% 0 represents time at Survey 3. The variables chosen at Hispanic/Latino 22 29% Level 1 included student IDs (recoded as integers from 1 Native American/American Indian 1 1% to 75), time_rec, recognition, and interest, and the variables White 29 39% chosen at Level 2 included the same recoded student IDs, Multiple 1 1% as well as female, ethnicity_rec, and KnowEngineer. Other 9 12% Total 75 100% Know an engineer Results Yes 34 45% No 41 55% Mean scores by each item on the survey for each Total 75 100% administration are shown in Table 5. Table 4 Survey items comprising the factors of interest. Factor Cronbach’s alpha Mean (pre-survey) Survey items 1: Engineering recognition 0.823 2.43 My family sees me as an engineer My teacher sees me as an engineer My friends see me as an engineer 2: Engineering interest 0.896 3.18 I want to learn more about engineering I enjoy engineering I see myself pursuing a career in engineering http://dx.doi.org/10.7771/2157-9288.1249 7 L. Chu et al. / Journal of Pre-College Engineering Education Research 79 Table 5 Frequencies of responses by survey items. Survey 1 Survey 2 Survey 3 Survey items Mean N SD Mean N SD Mean N SD a My family sees me as an engineer 2.73 74 1.80 2.78 72 2.00 2.83 75 1.85 b My teacher sees me as an engineer 2.50 72 1.38 2.69 72 1.74 2.53 75 1.66 c My friends see me as an engineer 2.01 74 1.85 1.90 72 1.86 1.85 75 1.84 d I want to learn more about 4.14 74 1.83 3.49 72 1.99 3.23 75 1.98 engineering e I enjoy engineering 3.71 75 1.92 3.46 72 1.92 3.25 75 1.89 f I see myself pursuing a career 2.54 74 2.01 2.31 72 2.07 2.45 75 1.93 in engineering Table 6 Output from unconditional model with recognition as outcome. Final estimation of fixed effects (with robust standard errors) Fixed effect Coefficient Standard error t-ratio Approx. d.f. p-value For INTRCPT1, p0 INTRCPT2, b00 2.402 0.180 13.348 74 ,0.001 For TIMEREC slope, p1 INTRCPT2, b10 20.020 0.076 20.262 74 0.794 Final estimation of variance components Random effect Standard deviation Variance component d.f. x2 p-value INTRCPT1, r0 1.449 2.100 74 504.113 ,0.001 TIMEREC slope, r1 0.471 0.222 74 149.287 ,0.001 level-1, e 0.655 0.430 Engineering Recognition Because variance in engineering recognition scores at Survey 3 and the growth rate varied across students in the An unconditional model for recognition was first set up. population, a conditional model was set up in an attempt The outcome variable was recognition, and time_rec was to explain this variance with predictors. In the Level 2 added as the predictor, uncentered. The residual (r1) was equations, Female, KnowEngineer, and Ethnicity_rec were selected to allow growth rate to vary across persons. The added as explanatory variables, all uncentered. The models models were as follows: were as follows: Level 1: RECOGNITIONti 5 p0i + p1i*(TIMERECti) + eti Level 1: RECOGNITIONti 5 p0i + p1i*(TIMERECti) + eti Level 2: p0i 5 b00 + r0i Level 2: p0i 5 b00 + b01*(FEMALEi) + b02* Level 2: p1i 5 b10 + r1i (KNOWENGIi) + b03*(Ethnicity_reci) + r0i After inspecting graphs of all student cases, the Level 2: p1i 5 b10 + b11*(FEMALEi) + b12* functional form, though varying, seemed to be linear. (KNOWENGIi) + b13*(Ethnicity_reci) + r1i Thus, a linear functional form was determined to be most Analysis of the conditional model yielded the results fitting. Analysis of the unconditional model yielded the shown in Table 7. results shown in Table 6. From the results in Table 7, it can be seen that, by From the results shown in Table 6, on average, the holding knowing an engineer and ethnicity constant, engineering recognition score at Survey 3 (b00) was 2.40. females have a recognition score that is 1.08 points less The t test result suggests that this recognition score is than that of males at Survey 3 (b01). This relationship different from zero in the population (p , 0.001). The between gender and recognition is statistically significant change in engineering recognition score from one survey to (t 5 23.271, p 5 0.002). After including Female, Know- the next (b10) was not different from zero in the population Engineer, and Ethnicity_rec in the model, the variance (t 5 20.262, p 5 0.794). The variance in recognition score remaining in engineering recognition score is 1.60. The at Survey 3 is 2.10. The statistical test result suggests that proportion of variance explained (PVE) for final status is the recognition score at the third survey differs across 0.24, which suggests that 24% of variation in Survey 3 students in the population (x2 5 504.113, p , 0.001). The recognition scores is due to the predictors included in the variance in engineering recognition growth rate is 0.22. model. The statistical test result suggests that variance The statistical test result suggests that recognition growth still remains in the population (x2 5 383.664, p , 0.001). rates vary across students in the population (x2 5 149.287, After including these explanatory variables in the model, p , 0.001). the variance remaining in the growth rates is 0.23. http://dx.doi.org/10.7771/2157-9288.1249 8 80 L. Chu et al. / Journal of Pre-College Engineering Education Research Table 7 Output of conditional model with recognition as outcome. Final estimation of fixed effects (with robust standard errors) Fixed effect Coefficient Standard error t-ratio Approx. d.f. p-value For INTRCPT1, p0 INTRCPT2, b00 3.500 0.281 12.433 71 ,0.001 FEMALE, b01 21.079 0.330 23.271 71 0.002 KNOWENGI, b02 20.671 0.338 21.985 71 0.051 ETHNICITY, b03 20.364 0.319 21.144 71 0.256 For TIMEREC slope, p1 INTRCPT2, b10 0.101 0.141 0.715 71 0.477 FEMALE, b11 20.203 0.140 21.453 71 0.151 KNOWENGI, b12 20.026 0.144 20.179 71 0.858 ETHNICITY, b13 20.007 0.154 20.049 71 0.961 Final estimation of variance components Random effect Standard deviation Variance component d.f. x2 p-value INTRCPT1, r0 1.265 1.601 71 383.664 ,0.001 TIMEREC slope, r1 0.478 0.229 71 145.457 ,0.001 level-1, e 0.656 0.430 Table 8 Output from unconditional model with interest as outcome. Final estimation of fixed effects (with robust standard errors) Fixed effect Coefficient Standard error t-ratio Approx. d.f. p-value For INTRCPT1, p0 INTRCPT2, b00 2.932 0.202 14.525 74 ,0.001 For TIMEREC slope, p1 INTRCPT2, b10 20.255 0.084 23.046 74 0.003 Final estimation of variance components Random effect Standard deviation Variance component d.f. x2 p-value INTRCPT1, r0 1.594 2.539 74 412.462 ,0.001 TIMEREC slope, r1 0.439 0.193 74 116.938 0.001 level-1, e 0.815 0.664 The statistical test result suggests that variance in the differs across students in the population (x2 5 412.462, growth rates remains in the population, after including p , 0.001). The variance in engineering interest growth Gender, KnowEngineer, and Ethnicity_rec (x2 5 145.457, rate is 0.19. The statistical test result suggests that interest p , 0.001). growth rates do vary across students in the population (x2 5 116.938 p 5 0.001). Engineering Interest Because variance in engineering interest scores at Survey 3 and in engineering interest growth rates varied across Next, an unconditional model for interest was set up. students in the population, a conditional model was set The outcome variable was changed to interest. The models up in an attempt to explain this variance with predictors. were as follows: In the Level 2 equations, Female, KnowEngineer, and Level 1: INTERESTti 5 p0i + p1i*(TIMERECti) + eti Ethnicity_rec were added as explanatory variables, all Level 2: p0i 5 b00 + r0i uncentered. The models were as follows: Level 2: p1i 5 b10 + r1i Level 1: INTERESTti 5 p0i + p1i*(TIMERECti) + eti Looking at graphs of all student cases, the functional Level 2: p0i 5 b00 + b01*(FEMALEi) + b02* form seemed to be linear. Thus, a linear functional form (KNOWENGIi) + b03*(Ethnicity_reci) + r0i was determined to be most fitting. Analysis of the uncon- Level 2: p1i 5 b10 + b11*(FEMALEi) + b12* ditional model yielded the results shown in Table 8. (KNOWENGIi) + b13*(Ethnicity_reci) + r1i From the results shown in Table 8, on average, students Analysis of the conditional model yielded the results decrease in engineering interest by 0.26 points from one shown in Table 9. survey to the next (b10). This decrease is greater than zero From the results in Table 9, it can be seen that, holding in the population (t 5 23.046, p 5 0.003). The variance constant ethnicity and knowing an engineer, engineering in interest score at Survey 3 is 2.54. The statistical test interest among females is less than males by 1.32 points result suggests that the interest score at the third survey at Survey 3 (b01). This relationship between gender and http://dx.doi.org/10.7771/2157-9288.1249 9 L. Chu et al. / Journal of Pre-College Engineering Education Research 81 Table 9 Output of conditional model with interest as outcome. Final estimation of fixed effects (with robust standard errors) Fixed effect Coefficient Standard error t-ratio Approx. d.f. p-value For INTRCPT1, p0 INTRCPT2, b00 3.993 0.303 13.166 71 ,0.001 FEMALE, b01 21.317 0.339 23.883 71 ,0.001 KNOWENGI, b02 21.159 0.341 23.398 71 0.001 ETHNICITY, b03 0.474 0.345 1.373 71 0.174 For TIMEREC slope, p1 INTRCPT2, b10 20.145 0.145 21.002 71 0.320 FEMALE, b11 20.196 0.148 21.319 71 0.191 KNOWENGI, b12 20.237 0.145 21.636 71 0.106 ETHNICITY, b13 0.236 0.156 1.511 71 0.135 Final estimation of variance components Random effect Standard deviation Variance component d.f. x2 p-value INTRCPT1, r0 1.316 1.731 71 292.317 ,0.001 TIMEREC slope, r1 0.423 0.179 71 109.233 0.003 level-1, e 0.816 0.666 interest is statistically significant (t 5 23.883, p , 0.001). and interest at Survey 3 aligns with prior research, as the Holding gender and ethnicity constant, students who do not need to support interest in engineering degrees and careers know an engineer have an interest score of 1.16 points less despite gender differences is well documented in the lite- than students who do know an engineer at Survey 3 (b02). rature (e.g., Bonous-Hammarth, 2000; Brainard & Carlin, This relationship between knowing an engineer and interest 1998; Eccles, 2007; Stevens, O’Connor, & Garrison, score is statistically significant (t 5 23.398, p 5 0.001). 2005). The more unexpected finding, however, is the sig- After including gender, knowing an engineer, and ethnicity nificant student decrease in engineering interest on average in the model, the variance remaining in engineering interest from one survey to the next. Given the effort to expose score is 1.731. The statistical test result suggests that students to engineering and the explicit inclusion of ways variance still remains in the population (x2 5 292.317, in which engineers and engineering help to improve society p , 0.001). Also, after including these explanatory variables, and make the world a better place within the ADE frame- the variance remaining in engineering interest growth rate is work, we expected student attitudes on this factor to improve 0.179, with variance still remaining in the population or, at the very least, remain unchanged (NAE, 2008). (x2 5 109.233, p 5 0.003). The PVE for final status is Classroom observations and speaking to the teachers 0.32, which suggests that 32% of variation in Survey 3 involved in the study, however, might help us understand interest scores is due to the predictors included in the model. this unexpected finding. For example, one teacher expli- Additionally, PVE in growth rates is 0.07, implying that 7% citly stated that they cut out the section of the framework of variation in change in interest scores across time is that has students write about and discuss the potential associated with these predictors. benefit of the task for addressing societal needs (e.g., the benefit of designing hand warmers for the homeless in Discussion the city in which the students live and go to school) after the first SDC. Such changes to the framework make it Over the course of the academic year, students’ difficult to test the promise and potential of this approach as engineering interest decreased on average from one survey a way to increase interest in engineering. This change does to the next, while their engineering recognition remained help explain the observed results. the same. On the third and final survey—administered after Another explanation for the decrease in engineering students had participated in their third SDC—females interest is that the SDCs which students were asked to scored lower on average than males in engineering complete were rigorous and difficult. For example, regard- recognition and engineering interest, controlling for student ing the design task ‘‘Developing a Biodiversity Monitoring ethnicity and knowing an engineer. Also, on the third Device,’’ in some of the classes at one of the schools, not survey, students who do not know an engineer had a lower one group of students was successful in accomplishing the average engineering interest score than those who do know design challenge within the constraints of the task. For this an engineer, holding constant gender and ethnicity. specific task, the research team has already made plans for The results from these analyses included both expected improving the feasibility of the challenge for the future. findings along with several unexpected and counterintuitive However, this points to another possible reason for the findings. The finding that female students have lower observed results, and to a research challenge in general, scores than male students in both engineering recognition which is the goal of integrating engineering core ideas and http://dx.doi.org/10.7771/2157-9288.1249 10 82 L. Chu et al. / Journal of Pre-College Engineering Education Research practices in the middle school science classroom and the average interest score by Survey 3. This may suggest that, potential unintended consequences of this goal. Another though students on average may show a dip in their feelings paper resulting from this study explores the tensions that of interest in engineering (over a period of about five science teachers express with teaching engineering during months), students who know an engineer and have some the school year, namely that of reconciling the amount idea of what an engineer’s work authentically looks like of time the design tasks take to complete, along with may recognize that the challenge ‘‘comes with the the perceived lack of overlap between the engineering territory.’’ As a result of this, along with an exposure for standards and those tested on state exams—which are a the first time to an engineering framework that explicitly high priority for the schools in which these teachers teach attempts to integrate engineering design, argumentation, (Brooks et al., 2018). Furthermore, given that the use of and scientific core ideas, these students may not decline in the ADE framework seems to be one of the first or early their interest as much as their counterparts who do not have attempts in the literature to integrate engineering directly this personal connection outside of the classroom. into the middle school science classroom, there is a need for further studies into the appropriateness or fit of engi- Limitations and Implications neering in middle school science contexts. The matter of teacher expertise in engineering may also This study faced a number of limitations, including a serve as an explanatory factor of the observed changes small number of time points (three), a lack of a comparison in students’ attitudes, given that neither of the teachers in group, and minimal collection of open-ended data. Looking the study have a degree or professional experience in an ahead, each of these issues will be addressed in future engineering field. A possible result is that the instruction studies. For example, we plan to collect data over a greater and guidance provided may not have facilitated the enga- number of time points, giving the students the space to gement of student interest or encouragement of students ‘‘rebound’’ from any changes in attitudes linked to not through difficult aspects of the design challenges. How- being accustomed to the framework. We also have plans to ever, interestingly, it was noted that while interest in include a comparison group in additional studies in order to engineering decreased over time, student attitude scores on look directly at the impact of student exposure to the ADE engineering recognition stayed the same, on average. Thus, framework. Finally, open-ended survey items will be inclu- while student attitudes toward wanting to learn more about ded and themed to increase the robustness of quantitative engineering, toward their enjoyment of engineering, and findings. toward their thoughts of pursuing an engineering career decreased over the period of these three surveys, their Acknowledgments perceptions of family, teacher, and friends seeing them as An earlier version of this article was previously an engineer remained unchanged. While the hope, undoub- published in the Proceedings of the 2018 ASEE Annual tedly, is that both interest in engineering and perceived Conference & Exposition, and was recognized as the 2018 recognition of students as engineers will increase, the Best Diversity Paper of the Pre-College Engineering Edu- unique and novel exposure to rigorous engineering design cation Division. tasks within the context of their middle school science classrooms may perhaps lead to a more accurate assessment References and appreciation of future coursework and experience in engineering. For students who had a successful personal Baldwin, T. B., Daniel, A., & Williams, B. (2016). Impact of an experience with the SDCs, their sense of preparedness for introductory engineering design course on minority middle and high work in engineering may have grown stronger. However, school students’ self-efficacy and interest in engineering. Paper presen- the research team will need to work to find ways of better ted at 2016 ASEE Annual Conference & Exposition, New Orleans, LA. 10.18260/p.25532. supporting students who may not have felt as successful Beam, T. K., Pierrakos, O., Constantz, J., Johri, A., & Anderson, R. in order to foster the same sense of preparedness across (2009). Preliminary findings on freshmen engineering students’ all groups of students, especially for girls and under- professional identity: Implications for recruitment and retention. represented minorities. Regardless, it is clear that much Paper presented at the 2009 ASEE Annual Conference & Exposition, work needs to be done to have engineering thoughtfully Austin, TX, June 14–17. Bleeker, M. M., & Jacobs, J. E. (2004). Achievement in math and integrated into the science classroom; simply inserting it science: Do mothers’ beliefs matter 12 years later? Journal of Edu- into a set of standards is not enough. cational Psychology, 96(1), 97–109. http://dx.doi.org/10.1037/0022- Other findings from the analyses point to the benefit of 0663.96.1.97 knowing an engineer on engineering attitudes and interest, Bonous-Hammarth, M. (2000). Pathways to success: Affirming opportu- which has also been documented in the literature (e.g., nities for science, mathematics, and engineering majors. Journal of Negro Education, 69(1/2), 92–111. Pierrakos, Beam, Constantz, Johri, & Anderson, 2009). Not Brainard, S. G., & Carlin, L. (1998). A six-year longitudinal study of knowing an engineer is shown to be associated with a undergraduate women in engineering and science. Journal of Engi- disadvantage in the factor of interest in engineering, namely neering Education, 87(4), 369–375. http://dx.doi.org/10.7771/2157-9288.1249 11 L. Chu et al. / Journal of Pre-College Engineering Education Research 83 Bricker, L. A., & Bell, P. (2008). Conceptualizations of argumentation Lachapelle, C. P., & Cunningham, C. M. (2017). Elementary engineering from science studies and the learning sciences and their implications for student interests and attitudes: A comparison across treatments. Paper the practices of science education. Science Education, 92(3), 473–498. presented at 2017 ASEE Annual Conference & Exposition, Columbus, Brooks, H. S., Hutner, T. L., Sampson, V., Chu, L., Crawford, R. H., OH. https://peer.asee.org/28211 Rivale, S., & Baze, C. L. (2018). Tensions arising when teaching Llewellyn, D. C., Pyke, P., Paterson, S., Landrum, R. E., Scarritt, A., scientific disciplinary core ideas via engineering practices. Proceedings Cullers, J. B. S., & Warner, D. L. (2016). Better together: Connecting of the 2018 Annual Meeting of the American Society for Engineering with other disciplines builds students’ own skills and professional Education, Salt Lake City, Utah. identity. Paper presented at 2016 ASEE Annual Conference & Carifio, J., & Perla, R. (2008). Resolving the 50-year debate around using Exposition, New Orleans, LA. 10.18260/p.26381 and misusing Likert scales. Medical Education, 42(12), 1150–1152. McCave, E. J., Gilmore, J., & Burg, K. (2014). Engineering and science Cass, C. A. P., Hazari, Z., Cribbs, J., Sadler, P. M., & Sonnert, G. (2011). student preparedness for research: Exploring the connections between Examining the impact of mathematics identity on the choice of student identity and readiness for research. Paper presented at the engineering careers for male and female students. Proceedings of the American Society for Engineering Education Annual Conference, 41st ASEE/IEEE Frontiers in Education Conference, Rapid City, SD. Indianapolis, IN. http://dx.doi.org/10.1109/FIE.2011.6142881 McLaughlin, M. W. (2006). Implementation research in education: Committee on K-12 Engineering Education. (2009). Engineering in K-12 Lessons learned, lingering questions, and new opportunities. In education: Understanding the status and improving the prospects. M. I. Honig (Ed.), New directions in education policy implementation: Washington, DC: National Academies Press. Confronting complexity (pp. 209–228). Albany, NY: State University Corwyn, R. F., & Bradley, R. H. (2008). The Panethnic Asian label and of New York Press. predictors of eighth-grade student achievement. School Psychology Moore, T. J., Stohlmann, M. S., Wang, H. H., Tank, K. M., & Roehrig, G. Quarterly, 23(1), 90–106. 10.1037/1045-3830.23.1.90 H. (2014). Implementation and integration of engineering in K-12 Cronin-Jones, L. L. (1991). Science teacher beliefs and their influence on STEM education. In S. Purzer, J. Strobel, & M. Cardella (Eds.), curriculum implementation: Two case studies. Journal of Research in Engineering in pre-college settings: Synthesizing research, policy, and Science Teaching, 28(3), 235–250. practices. West Lafayette, IN: Purdue University Press. Danforth, M., Lam, C., Mehrpouyan, H., & Hughes, R. (2016). Impact Morelock, J. R. (2017). A systematic literature review of engineering of a hands-on, exploratory engineering outreach program on knowl- identity: definitions, factors, and interventions affecting development, edge and attitudes of high school students. Paper presented at 2016 and means of measurement. European Journal of Engineering Educa- ASEE Annual Conference & Exposition, New Orleans, LA. 10.18260/ tion, 42(6), 1240–1262. https://doi-org.ezproxy.lib.utexas.edu/10.1080/ p. 25528. 03043797.2017.1287664 Duschl, A., Schweingruber, H. A., & Shouse, A. W. (2007). Taking National Academies of Sciences, Engineering, and Medicine. (2019). science to school: Learning and teaching science in grades K-8. Science and engineering for grades 6–12: Investigation and design at Washington, DC: National Academies Press. the center. Washington, DC: National Academies Press. https://doi.org/ Eccles, J. S. (2007). Where are all the women? Gender differences in 10.17226/25216 participation in physical science and engineering. In S. J. Ceci & W. M. National Academy of Engineering. (2008). Changing the conversation: Williams (Eds.), Why aren’t more women in science? Top researchers Messages for improving public understanding of engineering. debate the evidence (pp. 199–210). Washington, DC: American Washington, DC: National Academies Press. https://doi.org/10. Psychological Association. 17226/12187 Faulkner, W. (2007). Nuts and bolts and people: Gender-troubled National Academy of Engineering and National Research Council. (2009). engineering identities. Social Studies of Science, 37(3), 331–356. Engineering in K-12 education: Understanding the status and Godwin, A. (2016). The development of a measure of engineering identity. improving the prospects. Washington, DC: National Academies Paper presented at 2016 ASEE Annual Conference & Exposition, New Press. https://doi.org/10.17226/12635 Orleans, LA. 10.18260/p.26122. National Research Council. (2012). A framework for K-12 science edu- Godwin, A., Potvin, G., Hazari, Z., & Lock, R. (2013). Understanding cation: Practices, crosscutting concepts, and core ideas. Washington, engineering identity through structural equation modeling. Proceedings DC: National Academies Press. https://doi.org/10.17226/13165 of the ASEE/IEEE Frontiers in Education Conference, Oklahoma City, National Science Foundation. (2017). Broadening participation in engi- OK, pp. 50–56. http://dx.doi.org/10.1109/FIE.2013.6684787. neering (BPE). Directorate for Engineering. Godwin, A., Potvin, G., Hazari, Z., & Lock, R. (2016). Identity, critical National Science Foundation & National Center for Science and agency, and engineering: An affective model for predicting engineering Engineering Statistics. (2017). Women, minorities, and persons with as a career choice. Journal of Engineering Education, 105(2), 312–340. disabilities in science and engineering: 2017. Special Report NSF Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M. C. (2010). 17-310. Arlington, VA. Retrieved from www.nsf.gov/statistics/wmpd/ Connecting high school physics experiences, outcome expectations, NGSS Lead States. (2013). Next generation science standards: For states, physics identity, and physics career choice: A gender study. Journal of by states. Washington, DC: National Academies Press. Research in Science Teaching, 47(8), 978–1003. Penuel, W. R. (2016). Studying science and engineering learning in Holland, D. C. (2001). Identity and agency in cultural worlds. Cambridge, practice. Cultural Studies of Science Education, 11(1), 89–104. MA: Harvard University Press. 10.1007/s11422-014-9632-x Ivie, R., Cuzjko, R., & Stowe, K. (2001). Women physicists speak: Philip, T. M., & Azevedo, F. S. (2017). Everyday science learning and The 2001 International Study of Women in Physics. American Institute equity: Mapping the contested terrain. Science Education, 101, 526– of Physics Report. Retrieved from http://www.aip.org/statistics/trends/ 532. 10.1002/sce.21286 reports/iupap.pdf Pierrakos, O., Beam, T. K., Constantz, J., Johri, A., & Anderson, R. Jones, B. D., Osborne, J. W., Paretti, M. C., & Matusovich, H. M. (2014). (2009). On the development of a professional identity: Engineering Relationships among students’ perceptions of a first-year engineering persisters vs engineering switchers. 39th IEEE Frontiers in Education design course and their engineering identification, motivational beliefs, Conference, San Antonio, TX, pp. 1–6. course effort, and academic outcomes. International Journal of Engi- Purzer, S., Moore, T., Baker, D., & Berland, L. (2014). Supporting the neering Education, 30(6), 1340–1356. implementation of the Next Generation Science Standards (NGSS) Kao, G. (1995). Asian Americans as model minorities? A look at their through research: Engineering. Retrieved from https://narst.org/ academic performance. American Journal of Education, 121–159. ngsspapers/engineering.cfm http://dx.doi.org/10.7771/2157-9288.1249 12 84 L. Chu et al. / Journal of Pre-College Engineering Education Research Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Stevens, R., O’Connor, K., Garrison, L., Jocuns, A., & Amos, D. M. Applications and data analysis methods (Vol. 1). Thousand Oaks, CA: (2008). Becoming an engineer: Toward a three dimensional view Sage. of engineering learning. Journal of Engineering Education, 97(3), Sampson, V., & Clark, D. B. (2008). Assessment of the ways students 355–368. generate arguments in science education: Current perspectives and Tonso, K. L. (2007). On the outskirts of engineering: Learning identity, recommendations for future directions. Science Education, 92(3), gender, and power via engineering practice. Rotterdam, The 447–472. Netherlands: Sense. Smith, T. E. (1991). Agreement of adolescent educational expectations Tonso, K. (2014). Engineering identity. In A. Johri & B. Olds (Eds.), Cambridge Handbook of Engineering Education Research (pp. 267– with perceived maternal and paternal educational goals. Youth and 282). Cambridge, UK: Cambridge University Press. doi:10.1017/ Society, 23, 155–174. CBO9781139013451.019 Speering, W., & Rennie, L. (1996). Students’ perceptions about science: Turner, S., & Lapan, R. (2005). Evaluation of an intervention to increase The impact of transition from primary to secondary school. Research in non-traditional career interests and career-related self-efficacy among Science Education, 26(3), 283–298. middle-school adolescents. Journal of Vocational Behavior, 66, 516– Stevens, R., O’Connor, K., & Garrison, L. (2005). Engineering student 531. 10.1016/j.jvb.2004.02.005 identities in the navigation of the undergraduate curriculum. Turner, S. L., Steward, J. C., & Lapan, R. T. (2004). Family factors Proceedings of 2005 ASEE Annual Conference & Exposition (pp. associated with sixth-grade adolescents’ math and science career 5529–5536). interests. Career Development Quarterly, 53, 41–52. http://dx.doi.org/10.7771/2157-9288.1249 13