Numerous and increasing efforts over the past several decades have sought to introduce young people to key ideas in engineering and the practices of engineers. They have ranged from formal, classroom-based curricula aligned with state or national standards to informal, out-of-school initiatives, some with state, national, or even international reach. Some programs focus explicitly on the practices of engineering, using mathematics and science as necessary tools of design; others treat engineering as a context for teaching mathematics and science content; still others use engineering design–based activities primarily as a way to promote student interest and motivation to learn (Milto et al. 2016, p. 265).
The emergence of K–12 engineering programs in diverse contexts with different degrees of emphasis on the practices and disciplines of engineering underscores the need to address a very basic question: What is the goal of introducing engineering into K–12 education? Not surprisingly, there are multiple goals.
By examining extant curricula and programs and related research, the committee identified four goals for K–12 engineering education:
- Develop engineering literacy.
- Improve mathematics and science achievement through the integration of concepts and practices across the STEM fields.
- Improve college and career readiness.
- For a small percentage of students, prepare for matriculation in postsecondary engineering programs.
We consider each in turn, and then briefly discuss their implications for the preparation of K–12 teachers of engineering (this is addressed more fully in chapter 5).
The American educational system has a long history of promoting literacy. Perhaps the most foundational literacy concerns the ability to read and write. But even this measure of literacy has varied over time, from being able to write one’s name, to having completed the fourth grade (Clifford 1984), to being highly educated (Graff 1986). Although the definitions have varied, being literate has consistently referred to mastering knowledge and processes needed to interpret culturally significant information (de Castell et al. 1986). Desired levels of literacy have expanded beyond reading and writing to include reasoning and other higher-order cognitive skills (Clifford 1984). In addition, the number of those expected to be literate has grown to include virtually everyone, and it is generally recognized that formal schooling is not the sole means of acquiring literacy (Resnick 1990).
More recently, the idea of literacy has been applied to a person’s understanding of more specific areas of knowledge, such as science and mathematics. In the STEM fields, the earliest US efforts to define literacy focused on science. In Science for All Americans the American Association for the Advancement of Science proposed that scientific literacy should encompass “the knowledge, skills, and attitudes all students should acquire from their total school experience” (Rutherford and Ahlgren 1991, p. 220). The report describes the scientifically literate person as one who “is aware that science, mathematics, and technology are interdependent human enterprises with strengths and limitations; understands key concepts and principles of science; is familiar with the natural world and recognizes both its diversity and unity; and uses scientific knowledge and scientific ways of thinking for individual and social purposes” (p. xvii). A recent report from the National Academies of Sciences, Engineering, and Medicine (NASEM 2016), drawing on work from the health literacy community, argues that science literacy is relevant not only to individuals but also to communities and society as a whole. In the latter two contexts, the report notes, literacy
can “transcend the aggregation of individuals’ knowledge and accomplishments” (p. 4).
Engineering literacy involves understanding concepts such as constraints, specifications, optimization, and trade-offs, and being able to apply the engineering design process. It also involves recognizing the influence of engineering on society and how engineering is different from science in its application to personal, social, and cultural situations. In this way, engineering literacy can help address misconceptions people have about the field. Research has documented, for example, that many K–12 teachers and students have a limited understanding of what engineers do (e.g., Cunningham and Knight 2004; Cunningham et al. 2005, 2006). The goal of engineering literacy also represents an orientation and curriculum emphasis that values learning outcomes for all students.
Through the design and improvement of technology, engineers are largely responsible for the human-built world. Engineering and technology are thus intimately connected, so engineering literacy must address issues related to technology. Technologically literate citizens understand basic engineering concepts and terms as well as the nature and limitations of the engineering design process (box 3-1; NAE and NRC 2002).
Additional insight into the nature of engineering literacy is provided by the three “general principles” for K–12 engineering education identified in Engineering in K–12 Education: Understanding the Status and Improving the Prospects (NAE and NRC 2009, pp. 4–5):
- K–12 engineering education should emphasize engineering design.
- K–12 engineering education should incorporate important and developmentally appropriate mathematics, science, and technology knowledge and skills.
- K–12 engineering education should promote engineering habits of mind, including systems thinking, creativity, optimism, collaboration, communication, and attention to ethical considerations.
A slightly more expansive model of engineering literacy is presented in Standards for Professional Development for K–12 Teachers of Engineering (Farmer et al. 2014). Designed to guide the professional learning of K–12 educators, it broadens the concept to include literacy related to engineering careers. Specifically, the standards suggest that educators (and, by extension, their students) should understand that “Engineering includes multiple areas of specialization (e.g., mechanical, electrical, petroleum, civil, biomedical,
aerospace, environmental, industrial); and engineering career pathways are accessible via a variety of educational routes” (Farmer et al. 2014, p. 1). This document will be discussed further in chapter 5.
The idea that K–12 engineering education can serve a general literacy goal is supported by the National Assessment of Educational Progress assess-
ment of Technology and Engineering Literacy (TEL). This first-ever national assessment to target engineering concepts and skills has been administered twice, in 2014 and 2018, to large numbers of US eighth graders across three domains: technology and society, design and systems, and information and communication technology. The framework document used to design the assessment defined technology and engineering literacy as “the capacity to use, understand, and evaluate technology as well as to understand technological principles and strategies needed to develop solutions and achieve goals” (NAGB 2013, p. xi). In addition to asking traditional, multiple-choice questions, the TEL assessment includes a number of scenario-based tasks. One sample task in the 2014 assessment asked students to create a route for a safe bike lane in a city; in another, they had to troubleshoot and fix the habitat for a classroom iguana (Nation’s Report Card 2014).
Another goal for K–12 engineering education is to encourage and support learning in the other three STEM subjects. Engineering is seen as a vehicle for integrated STEM learning in part because design tasks can be highly engaging for students. Indeed, engagement is one of the most consistent and often-reported outcomes of doing engineering with students (Milto et al. 2016), including students not typically engaged in STEM subjects (Purzer et al. 2015). Design challenges also can provide real-world settings where engineering can clearly be seen as doing a “public good” (Hacker et al. 2017). The kinds of real-world problems that students are asked to solve invite both learning and applying concepts from multiple STEM disciplines.
Many approaches to integrated STEM education use the engineering design process as a context for exploring concepts and practices in science (e.g., Kolodner 2002; Kanter 2010) and mathematics (e.g., Huang et al. 2008). For example, student-designed rollercoasters can be used to demonstrate the science concept of potential energy, and mathematics can be used to calculate the average velocity of a ball on the coaster track. K–12 engineering activities, whether in the classroom or at museums or other out-of-school venues, can engage learners in doing scientific investigations (e.g., NASEM 2019) and in using mathematics to predict, model, and analyze the performance of prototypes. Connecting engineering design to concepts in science and mathematics can help students better grasp and frame the challenge,
gain insights from studying previous solutions to similar problems, choose among competing possible solutions to the problem, understand the needs of different users, and build better mental models of how prototypes are working and how they should work.
Although empirical evidence for engineering leading to learning or achievement in science and mathematics is mixed (NAE and NRC 2014, pp. 56–60) and the number of high-quality studies in this area is fairly limited, some promising results suggest that students can improve their understanding of science ideas through engineering design. When the learning goal is to apply (“transfer”) known science ideas to a design challenge, there is opportunity for students to develop more robust and flexible understandings of those concepts (Spiro et al. 2003). Learning and using mathematics concepts in the context of engineering design may be more challenging for students (e.g., Tran and Nathan 2010).
Beyond improving engagement and learning in science and mathematics, engineering education can enable STEM integration by helping students engage with engineering practices in informed ways rather than through trial-and-error or random guesswork. Informed engineering design involves instructional approaches where (1) learning is “central and inherent to designing” (Adams and Atman 2000, p. 3), whether the learning takes place while sketching, making a prototype, experimenting, or troubleshooting; (2) decisions are driven by both practical knowledge (McCormick 1994; Sternberg 1985) and knowledge of relevant science concepts (Crismond and Adams 2012); (3) design strategies are used effectively (Crismond and Adams 2012); and (4) ideas and practices from different STEM disciplines are used and reflected upon together (Kimbell et al. 1991, p. 156) via explicit connection making (NAE and NRC 2014, pp. 89–90) and the development of STEM associational fluency.1
While STEM integration is a stated goal of many educators, the cognitive and learning sciences point to certain challenges that may inhibit students’ ability to learn in integrated STEM contexts (NAE and NRC 2014, pp. 78–89). We discuss three challenges relevant to engineering-based STEM integration and possible ways to address them.
1 STEM associational fluency is an “integrated approach to STEM education (iSTEM) [that] includes instructional approaches and complex classroom interventions that interweave content and learning experiences among and between any of the STEM subjects or other school subjects” (de Miranda et al. 2016, p. 4).
Cognitive Limits of Attention and Memory
The cognitive load for beginning designers is much greater than for experienced designers. A study of expert designers found that most of their time was spent making routine design decisions, for which solutions from prior work were readily available and recalled from memory (Akin and Lin 1996). In contrast, “novel decisions,” where prior knowledge did not avail the designers of useful insight to the design problem, carried a “very large overhead” of time and attention for the experts to resolve. For beginning designers, almost all their design decisions are novel to them. Lack of familiarity with relevant disciplinary domains (e.g., science and mathematics), of knowledge of how devices or systems work, and of the skills needed to make and refine a prototype can overload the learner’s short-term memory. This leaves fewer mental resources for making connections to newly acquired abstractions—from two, three, even four distinct disciplines—as the learner moves among the details of the developing prototypes. Design challenges can also be difficult if the knowledge they draw on is “extensive and unpredictable” (McCormick 1993, p. 309) and if they require meeting multiple needs and requirements that may conflict with one another (Alexander 1964).
Educators can help by giving design challenges that vary in terms of how well they are defined (well defined, moderately ill defined, ill defined) (Jonassen 2000). A well-defined design problem might have only one or two variables that can be changed and could result in a single “best” answer. Materials-constrained design problems can be well defined, as when students use materials given to them and the problem framing has been done for them. Well-defined and moderately ill-defined tasks can help build domain knowledge or skills in design thinking when they are appropriately scaffolded (e.g., Crismond 2011), as with Burghardt and Hacker’s (2004) “knowledge skill builders” and the “resource tasks” in the Nuffield Design & Technology curricula (Barlex 1995). With such scaffolding, students grapple with some but not all aspects of extremely complex (“wicked”) design problems (Churchman 1967; Buchanan 1995). Selected ill-defined design challenges can be used as performance tasks, where students frame the problem to solve (Adams et al. 2003).
Learning from Real-World Situations
Design challenges typically have real-world connections and require making prototypes and physical models, activities with different types of challenges for different types of students. Students with extensive craft knowledge (e.g., mechanical/tool skills, experience making and constructing) and no training in science, for example, can often offer very workable solutions to such challenges that short-circuit the need to use and apply STEM concepts. Providing these students with just-in-time learning of relevant science and mathematics concepts (e.g., Burghardt and Hacker’s  “knowledge and skill builders”) can help in this situation. For students with limited craft knowledge, the “perceptual richness” (Goldstone and Sakamoto 2003) of real-world design tasks can draw attention away from acquisition of STEM ideas and practices. The challenge of making can be all-absorbing for these students and demand significant cognitive and attentional resources.
Making Connections among Multiple Representations
As indicated in the preceding two sections, integrated STEM learning involves making connections between concepts and their representations (NAE and NRC 2014, pp. 81–82), but in some cases representations of the same concept can mean different things in different STEM fields. For example, modeling is one of the most powerful activities and notions in all STEM subjects. In technology, it may involve building a physical artifact to scale. In science, models, which are simplifications of more complex phenomena, may be created in order to make predictions and refine explanations about facets of the natural world. Engineers may use mathematical models to predict the performance of key features of a design, such as how quickly a disk brake cools depending on its thickness and diameter, or how varying the length of the throw arm of a catapult affects how far its projectile travels.
Teachers can help students who struggle to reconcile different representations of similar phenomena by highlighting the STEM field the current discussion addresses and asking how models in this field and context are similar and different with examples of models from other fields and contexts. Cognitive flexibility theory (Spiro et al. 1995) suggests that using multiple examples of concepts in different contexts can lead to more flexible understanding and use of those ideas, especially in ill-structured contexts (Spiro et
al. 1995), such as those posed by engineering design challenges. Techniques, such as connecting past instructional moves to those in the past or future, have been found to support “cohesion” of important science and mathematics concepts in K–12 engineering education (Nathan et al. 2017).
As this brief review suggests, there may be challenges to learning STEM concepts and practices in an integrated way. However, repeated experience with ideas that cross STEM boundaries in the context of engineering design activities can reduce challenges related to cognitive limits, real-world problem solving, and multiple representations.
Data from a variety of sources suggest broad consensus on the types of skills and dispositions young people entering college or the workforce should have. For example, large majorities of respondents to a 2018 employer survey by the National Association of Colleges and Employers (NACE 2018) said they looked for evidence of written communication skills (selected by 82 percent of employers), problem-solving skills (selected by 81 percent), and ability to work in a team (selected by 79 percent) on a job candidate’s resume. The American Association of Colleges and Universities has commissioned multiple surveys of employers about the level and breadth of desired knowledge and skills they seek when hiring. The resulting data (e.g., Hart Research Associates 2015) suggest that for long-term career success, a job applicant’s demonstrated capacities for critical thinking, clear communication, and complex problem solving are more important than any specific undergraduate major. Of 17 outcome areas tested, employers valued most highly teamwork skills, written and oral communication, critical thinking, ethical decision making, and the ability to apply knowledge in real-world settings.
The Council of Chief State School Officers (CCSSO 2013), which represents public sector K–12 education administrators, has proposed a definition of college, career, and citizenship readiness that builds on these employer-identified traits (box 3-2). The definition overlaps significantly with visions of college and career readiness described by a number of states (Mishkind 2014).
The college and career readiness skills sought by postsecondary educators and employers are variously called 21st century skills, professional skills, new basic skills, and higher-order thinking. These terms typically refer to both cognitive and noncognitive skills—critical thinking, problem solving,
collaboration, effective communication, motivation, persistence, and learning to learn—that can be demonstrated in core academic content areas and are important to success in education, work, and other areas of adult responsibility. The labels also may include other important capacities—such as creativity, innovation, and ethics—that are important to later success and may also be developed in formal or informal learning environments (NRC 2012b, p. 17). College and career readiness competencies are particularly important to the extent that they encourage deeper learning, the ability to transfer understanding and capability between contexts within a single domain or from a context in one domain to another.
College and career readiness does not mean that K–12 students who experience engineering coursework are necessarily aiming for careers or further study in engineering, although this may be true for some (see the next section). But whether or not one majors in engineering, elements of engineering education align with the worker characteristics sought by many employers and with student traits desired by higher-education institutions. These include engineering’s orientation toward systematic identification and problem solving, integration of concepts and practices across multiple subject areas, communication skills, attention to ethical concerns, and teamwork.
There is limited empirical evidence that engineering coursework in grades K–12 can contribute to college readiness. A study of the Project Lead The Way (PLTW) program2 found higher levels of both mathematics proficiency and enrollment in institutions of higher education among PLTW students compared with a matched comparison group (Van Overschelde 2013). Other research on PLTW failed to document increased enrollments but did find that a larger proportion of PLTW students than non-PLTW students chose to major in a STEM subject (Pike and Robbins 2014).
A final goal of K–12 engineering education is to help prepare students who may wish to matriculate in postsecondary engineering programs. This preparation may involve the nurturing of interest in engineering, including as a possible career path; development of an engineering identity; and pursuit of science and mathematics coursework that provides a foundation for college-level engineering studies.
Nurturing Interest in Engineering
Students’ interest positively affects their attention, goals, and levels of learning (e.g., Hidi and Renninger 2006; Renninger and Hidi 2011). Interest is also related to identity: once interest has been triggered and develops, the student begins to identify “with the goals, actions and topics related to these interests” (Krapp 2007, p. 14; Renninger 2009).
Interest (and identity) development in K–12 education has been studied more extensively in science than in the other STEM disciplines; there is little research on interest development in engineering specifically. Nonetheless, studies show that various K–12 programs and activities in engineering enhance students’ interest.
As noted, many K–12 integrated STEM initiatives have an engineering design component. They may also share features with learning experiences known to support interest development. Ideally, such learning
2 Project Lead The Way is a nonprofit organization that develops STEM curricula, including in engineering, for use by US elementary, middle, and high schools and provides teacher professional development.
experiences (1) are open-ended enough to provide learners with a range of “triggers,” which may capture attention by promoting novelty, complexity, incongruity, uncertainty, or surprise, and (2) include interactions with others, such as educators, parents, and peers, who can model STEM problem solving (Renninger 2012).
A review of outcomes data from 11 afterschool STEM programs found that participation increased students’ interest in, capacity to engage productively with, and valuing of STEM (Krishnamurthi et al. 2014). And in one of the programs, TechBridge, 85 percent of girls reported finding engineering more interesting after participation. Similarly, a large survey of college students who participated in one or more engineering or robotics competitions during high school found a 5 percent greater interest in STEM careers by the end of high school compared with students who did not engage in such competitions (Miller et al. 2017). The study also found that participation in a robotics or engineering competition predicted interest in a career in engineering (but not in any other STEM subdiscipline). For example, participation in FIRST (www.firstinspires.org) robotics competitions influences not only student course selection in college but also choice of career. An ongoing longitudinal study of the program finds that these students show greater interest in STEM careers, gains in STEM identity, and improvements in STEM understanding (Melchior et al. 2018).
The committee found one study examining the potential impact of classroom engineering activities on choice of college major. According to Zarske et al. (2007), students in grades 3–12 who experience once-weekly engineering projects may be more likely to apply to engineering schools.
Developing an Engineering Identity
A fair amount is known about engineering identity development in college students and working professionals (e.g., Morelock 2017; NAE 2018, pp. 94–97; Tonso 2014). Few researchers have examined the development of engineering identity in K–12 students, but the foundation for STEM-related identity development at the K–12 level involves (1) getting young people interested in STEM topics and professions, (2) developing their competence and confidence, and (3) helping them envision themselves as contributors and participants in the STEM enterprise (Krishnamurthi et al. 2014, p. 8).
The Engineering Identity Development Scale (EIDS) is designed to measure engineering identity development in preadolescents (Capobianco
et al. 2012). It was tested among several hundred elementary students taking introductory engineering lessons, including a unit of the Engineering is Elementary curriculum, and showed that the interest levels of both girls and boys increased as a result of their learning experience (Douglas et al. 2014). Another study that also used the EIDS determined that lessons that integrated science, technology, and engineering were more likely to boost engineering identity among elementary students, compared to a matched control group (Yoon et al. 2014).
Pursuit of Science and Mathematics Coursework
Generally speaking, young people who aspire to be engineers need to pursue advanced-level courses in science and mathematics in high school to satisfy entry requirements for college engineering programs. Overall, the more science and mathematics courses a student takes in high school, the more likely they are to earn a STEM degree (Eagan et al. 2010). Although many individual and institutional factors affect whether a student completes an undergraduate engineering degree (Hughes et al. 2013; NAE 2018), some research has suggested that a student who takes several years of high school mathematics slightly increases their odds of earning an engineering degree within 5 years of matriculation (Hughes et al. 2013). Taking advanced high school mathematics and science courses predict grades in college calculus courses (Tyson 2011), which may affect whether a student continues in an engineering course of study. Students who did not complete calculus in high school were more likely to transfer out of engineering and into another STEM degree program than those who did (Tyson 2011).
Some of this preparation can come through dual-credit programs, dual-enrollment programs, Advanced Placement (AP) courses, or any other arrangement in which high school students take college-level courses. A new model involves a collaboration between the College Board, which oversees the AP program, and PLTW. AP + PLTW offers students recognition for completing a combination of AP and PLTW courses in engineering, biomedical science, or computer science. In the 2016–17 school year, over 2,300 students received recognition in engineering (Howell 2018), which PLTW says “demonstrates to colleges and employers that the student is ready for advanced course work and interested in careers in this discipline.”3 In addi-
tion, as noted in chapter 1, a consortium of universities are pilot testing an advanced high school course in engineering that may form the basis of an AP offering. However, unequal access to AP coursework, particularly for students at high-need schools (Handwerk et al. 2008) that also tend to have less experienced teachers and fewer science facilities (Smith et al. 2013), may compound the lack of diversity in engineering.
So far, this chapter has considered the four goals for K–12 engineering education separately. In classrooms and other learning environments, however, multiple goals may be relevant.
For example, the goal of literacy would seem a priority for younger students. And the structure of the elementary grades, where teachers are responsible for more than one subject, offers opportunities to help students begin to connect engineering to basic ideas and practices in science and mathematics as they tackle simple design challenges. Grades K–5 are also not too early for students to begin to develop qualities valued in college and career settings, which align with many of the essential qualities of engineering described in chapter 2. For example, acceptance of failure as a necessary part of the engineering design process can be nurtured beginning in elementary school (Lottero-Perdue 2015; Lottero-Perdue and Parry 2017).
In the middle and upper grades, where teachers are more likely to be subject-matter specialists, STEM integration may become more important, with students leveraging more and increasingly complex concepts from science and mathematics to address engineering design challenges. The goal of preparing for matriculation in college engineering programs, with their high-level science and mathematics coursework, will be relevant to some high school students, but all high school students will benefit from mastery of the skills and attributes valued by employers and postsecondary institutions. None of the goals suggests engineering is out of reach as a potential career path for any student.
The relative emphasis of the four goals and their overlap will vary depending on local and state educational goals as represented by standards and other policy documents, the curriculum or school, the number and expertise of engineering teachers, and other factors. Figure 3-1 shows how the goals might play out across K–12 in a particular setting.
Engineering plays a central role in the design of technologies, systems, and services that address human needs and wants. Engineering know-how is also required to address the inevitable unintended, sometimes negative, consequences associated with some of these innovations. It is thus fitting that the first goal of K–12 engineering education is engineering literacy. A person who is engineering literate has a basic understanding of the people and processes involved in creating the human-built world. With this foundation, she can think critically and make decisions about a variety of important issues important to her, her family, and her community. Similarly, the second and third goals of K–12 engineering education empower students in different ways to be competent, engaged members of society, whether or not they pursue an engineering degree. The fourth goal is important to students interested in an engineering career.
Accomplishing these laudable goals requires a knowledgeable and confident teacher corps. As we show in chapter 4, some of these educators are
already in the classroom, though there are uncertainties about their numbers and the extent of their engineering literacy.
As noted in chapter 2 (“Diversity in Engineering”), engineering has had historical difficulty attracting women and underrepresented minorities to the field. Chapter 4 (“Demographics and Diversity”) notes the paucity of these populations in the current workforce of K–12 teachers of engineering. This suggests that all of the goals for K–12 engineering education will be more impactful if informed by diversity considerations. A more diverse student population, given equitable access to engineering learning opportunities, will be the seed stock for future K–12 teachers, including teachers of engineering.
Adams RS, Atman CJ. 2000. Characterizing engineering student design processes: An illustration of iteration. Proceedings, Annual Meeting of the American Society of Engineering Education Conference, Session 2330. St. Louis, MO.
Adams RS, Turns J, Atman CJ. 2003. Educating effective engineering designers: The role of reflective practice. Design Studies 24(3):275–294.
Akin Ö, Lin C. 1996. Design protocol data and novel design decisions. In: Analysing Design Activity, eds Cross N, Christiaans H, Dorst K. Chichester, UK: John Wiley & Sons, Ltd.
Alexander C. 1964. Notes on the synthesis of form. Cambridge, MA: Harvard University Press.
Barlex D, Harrison B. 1995. Nuffield Design & Technology: Study Guide. Harlow: Longman.
Buchanan R. 1995. Wicked problems in design thinking. In: The Idea of Design: A Design Issues Reader, eds Margolin V, Buchanan R. Cambridge, MA: MIT Press.
Burghardt D, Hacker M. 2004. Informed design: A contemporary approach to design pedagogy as a core process in technology. Technology Teacher 63(1):6–8.
Capobianco BM, French BF, Diefes-Dux HA. 2012. Engineering identity development among pre-adolescent learners. Journal of Engineering Education 101(4):698–716.
CCSSO [Council of Chief State School Officers]. 2013. Knowledge, Skills, and Dispositions: The Innovation Lab Network State Framework for College, Career, and Citizenship Readiness, and Implications for State Policy. Washington. Available online at https://www.ccsso.org/sites/default/files/2017-10/ILN%20Knowledge%20Skills%20and%20Dispositions%20CCR%20Framework%20February%202013.pdf (accessed August 2, 2018)
Churchman CW. 1967. Wicked problems. Management Science 14(4):141–142.
Clifford GJ. 1984. Buch und Lesen: Historical perspectives on literacy and schooling. Review of Educational Research 54(4):472–500.
Crismond DP. 2011 Scaffolding strategies that integrate engineering design and scientific inquiry in project-based learning environments. In: Fostering Human Development through Engineering and Technology Education, eds Barak M, Hacker M (pp. 235-255). Rotterdam: Sense Publishers.
Crismond DP, Adams RS. 2012. The informed design teaching and learning matrix. Journal of Engineering Education 101(4):738–797.
Cunningham C, Knight M. 2004. Draw an engineer test: Development of a tool to investigate students’ ideas about engineering and engineers. Proceedings, ASEE Annual Conference and Exposition, June 20–23, Salt Lake City.
Cunningham C, Lachapelle C, Lindgren-Streicher A. 2005. Assessing elementary school students’ conceptions of engineering and technology. Proceedings, ASEE Annual Conference and Exposition, June 12–15, Portland, OR.
Cunningham C, Lachapelle C, Lindgren-Streicher A. 2006. Elementary teachers’ understandings of engineering and technology. Proceedings, ASEE Annual Conference and Exposition, June 18–21, Chicago.
de Castell S, Luke A, Egan K, eds. 1986. Literacy, Society, and Schooling. Cambridge: Cambridge University Press.
de Miranda MA. 2018. Pedagogical content knowledge for technology education. In: Springer International Handbooks of Education: Handbook of Technology Education, ed de Vries MJ. Dordrecht: Springer International Publishing.
de Miranda MA, Rambo-Hernandez KE, Hernandez PR. 2016. Measuring student content knowledge, iSTEM, self efficacy, and engagement through a long-term engineering design intervention. Proceedings, American Society for Engineering Education. Available online at https://peer.asee.org/measuring-student-content-knowledge-istem-self-efficacy-and-engagement-through-a-long-term-engineering-design-intervention (accessed September 12, 2019).
Douglas KA, Mihalec-Adkins BP, Diefes-Dux HA. 2014. Boys and girls engineering identity development in early elementary before and after hands-on engineering learning classroom experiences. Proceedings, American Society for Engineering Education Annual Conference and Exposition, Indianapolis, June 15–18. Available online at http://whitestarfoundations.org/wp-content/uploads/docs/3Boys_and_Girls_Engineering_Identity_2014.pdf (accessed August 2, 2018).
Eagan MK Jr, Hurtado S, Chang MJ. 2010. What matters in STEM: Institutional contexts that influence STEM bachelor’s degree completion rates. Proceedings, Annual Meeting of the Association for the Study of Higher Education, November 17–20, Indianapolis.
Farmer C, Klein-Gardner S, Nadelson L. 2014. Standards for preparation and professional development for K-12 teachers of engineering. American Society for Engineering Education. Retrieved from https://www.asee.org/documents/papers-and-publications/papers/outreach/Standards_for_Preparation_and_Professional_Development.pdf (accessed September 7, 2019).
Goldstone RL, Sakamoto Y. 2003. The transfer of abstract principles governing complex adaptive systems. Cognitive Psychology 46(4):414–466.
Graff H. 1986. The legacies of literacy: Continuities and contradictions in Western society and culture. In: Literacy, Society, and Schooling, eds de Castell S, Luke A, Egan K. Cambridge: Cambridge University Press.
Hacker M, Crismond D, Hecht D, Lomask M. 2017. Engineering for all: A middle school program to introduce students to engineering as a potential social good. Technology and Engineering Teacher, November. Available online at https://www.iteea.org/File.aspx?id=137376&v=a57b55da (accessed September 10, 2019).
Handwerk P, Tognatta N, Coley RJ, Gitomer DH. 2008. Access to Success: Patterns of Advanced Placement Participation in US High Schools. Princeton: Educational Testing Service Policy Evaluation and Research Center.
Hart Research Associates. 2015. Falling Short? College Learning and Career Success; Selected Findings from Online Surveys of Employers and College Students Conducted on Behalf of the Association of American Colleges & Universities. Available online at https://www.aacu.org/sites/default/files/files/LEAP/2015employerstudentsurvey.pdf (accessed September 12, 2019).
Hidi S, Renninger KA. 2006. The four-phase model of interest development. Educational Psychologist 41(2):111–127.
Howell S. 2018. 2016-17 AP + PLTW Student Achievement Results. Available online at https://www.pltw.org/blog/2016-17-ap-pltw-student-achievement-results (accessed August 7, 2018).
Huang W, Brizuela B, Wong P. 2008. Integrating algebra and engineering in the middle school classroom. Proceedings, American Society for Engineering Education Annual Conference. Available online at https://peer.asee.org/integrating-algebra-and-engineering-in-the-middle-school-classroom (accessed July 17, 2018).
Hughes BE, Garibay JC, Hurtado S, Eagan K. 2013. Examining the tracks that cause derailment: Institutional contexts and engineering degree attainments. Proceedings, American Educational Research Association Annual Forum, April 27–May 1, San Francisco.
Jonassen DH. 2000. Toward a design theory of problem solving. Educational Technology Research and Development 48(4):63–85.
Kanter DE. 2010. Doing the project and learning the content: Designing project-based science curricula for meaningful understanding. Science Education 94(3):525–551.
Kimbell R, Stables K, Wheeler T, Wozniak A, Kelly V. 1991. The assessment of performance in design and technology. London: Schools Examination and Assessment Council.
Kolodner JL. 2002. Facilitating the learning of design practices: Lessons learned from an inquiry into science education. Journal of Industrial Teacher Education 39(3). Available online at http://scholar.lib.vt.edu/ejournals/JITE/v39n3/kolodner.html (accessed September 9, 2019).
Krapp A. 2007. An educational–psychological conceptualization of interest. International Journal of Educational and Vocational Guidance 7(1):5–21.
Krishnamurthi A, Ballard M, Noam GG. 2014. Examining the impact of afterschool STEM programs. Paper commissioned by the Noyce Foundation. July 2014. Available online at https://files.eric.ed.gov/fulltext/ED546628.pdf (accessed September 16, 2019).
Lottero-Perdue PS. 2015. The engineering design process as a safe place to try again: Responses to failure by elementary teachers and students. Presented at the National Association for Research in Science Teaching Annual Conference, April 11–14, Chicago.
Lottero-Perdue PS, Parry EA. 2017 Elementary teachers’ reflections on design failures and use of fail words after teaching engineering for two years. Journal of Pre-College Engineering Education Research 7(1).
McCormick R. 1993. Design education and science: Practical implications. In: Design Methodology and Relationships with Science, eds deVries MJ, Cross N, Grant DP (pp. 309–319). Boston: Kluwer Academic Publisher.
McCormick R. 1994. Learning through apprenticeship. In: Technology Education in School and Industry: Emerging Didactics for Human Resource Development, eds Blandow D, Dyrenfurth MJ. Berlin: Springer-Verlag.
Melchior A, Burack C, Hoover M. 2018. Impacts of after-school robotics programming on STEM interests and attitudes. Paper presented at the American Educational Research Association 2018 Annual Meeting, April 13, New York. Available online at https://www.firstinspires.org/sites/default/files/uploads/resource_library/impact/impacts-ofafter-school-robotics-programming-on-stem-interests-and-attitudes.pdf (accessed on September 16, 2019).
Miller K, Sonnert G, Sadler P. 2017. The influence of students’ participation in STEM competitions on their interest in STEM careers. International Journal of Science Education, Part B: Communication and Public Engagement 8(2):95–114.
Milto E, Wendell K, Watkins J, Hammer D, Spencer K, Portsmore M, Rogers C. 2016. Elementary school engineering for fictional clients in children’s literature. In: Connecting Science and Engineering Education Practices in Meaningful Ways: Building Bridges, eds Annetta L, Minogue J. New York: Springer International Publishing.
Mishkind A. 2014. Overview: State Definitions of College and Career Readiness. Washington: College & Career Readiness & Success Center. Available online at: https://ccrscenter.org/sites/default/files/CCRS%20Defintions%20Brief_REV_1.pdf (accessed September 6, 2018).
Morelock JR. 2017. A systematic literature review of engineering identity: Definitions, factors, and interventions affecting development, and means of measurement. European Journal of Engineering Education 42(6):1240–1262.
NAE [National Academy of Engineering]. 2018. Understanding the Educational and Career Pathways of Engineers. Washington: National Academies Press.
NAE and NRC [National Academy of Engineering and National Research Council]. 2002. Technically Speaking: Why All Americans Need to Know More about Technology, eds Pearson G, Young AT. Washington: National Academy Press.
NAE and NRC. 2009. Engineering in K–12 Education: Understanding the Status and Improving the Prospects, eds Katehi L, Pearson G, Feder M. Washington: National Academies Press.
NAE and NRC. 2014. STEM Integration in K–12 Education: Status, Prospects, and an Agenda for Research, eds Honey M, Pearson G, Schweingruber H. Washington: National Academies Press.
NAGB [National Assessment Governing Board]. 2013. Technology and Engineering Literacy Framework for the 2014 National Assessment of Educational Progress. Washington. Available online at https://www.nagb.gov/content/nagb/assets/documents/publications/frameworks/technology/2014-technology-framework.pdf (accessed August 6, 2018).
NASEM [National Academies of Sciences, Engineering, and Medicine]. 2016. Science Literacy: Concepts, Contexts, and Consequences, eds Snow CE, Dibner KA. Washington: National Academies Press. Available online at https://www.nap.edu/catalog/23595/science-literacy-concepts-contexts-and-consequences (accessed September 21, 2018).
NASEM. 2019. Science and Engineering for Grades 6–12: Investigation and Design at the Center. Washington: National Academies Press. Available online at https://www.nap.edu/catalog/25216/science-and-engineering-for-grades-6-12-investigation-and-design (accessed September 9, 2019).
Nathan MJ, Wolfgram M, Srisurichan R, Walkington C, Alibali MW. 2017. Threading mathematics through symbols, sketches, software, silicon and wood: Teachers produce and maintain cohesion to support STEM integration. Journal of Educational Research 110(3):272–293.
Nation’s Report Card. 2014. Sample scenario-based tasks. 2014—Technology & Engineering Literacy. Available online at https://www.nationsreportcard.gov/tel_2014/#tasks/overview (accessed September 21, 2018).
NACE [National Association of Colleges and Employers]. 2018. Employers want to see these attributes on students’ resumes. Available online at https://www.naceweb.org/talent-acquisition/candidate-selection/employers-want-to-see-these-attributes-onstudents-resumes/ (accessed September 16, 2019).
NRC. 2012. Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century. Washington: National Academies Press.
Pike GR, Robbins K. 2014. Using propensity scores to evaluate education programs. Paper presented at the annual meeting of the Indiana Association for Institutional Research, Indianapolis.
Purzer Ş, Goldstein MH, Adams RS, Xie C, Nourian S. 2015. An exploratory study of informed engineering design behaviors associated with scientific explanations. International Journal of STEM Education 2:9. Available online at https://stemeducationjournal.springeropen.com/articles/10.1186/s40594-015-0019-7 (accessed September 21, 2018).
Renninger KA. 2009. Interest and identity development in instruction: An inductive model. Educational Psychologist 44(2):1–14.
Renninger KA. 2012. The development of interest and iSTEM education. Paper presented to the NAE-NRC Committee on Integrated STEM Education, Washington, April 25.
Renninger KA, Hidi S. 2011. Revisiting the conceptualization, measurement, and generation of interest. Educational Psychologist 46(3):168–184.
Resnick LB. 1990. Literacy in school and out. Daedalus 119(2):169–185.
Rutherford FJ, Ahlgren A. 1991. Science for All Americans. Washington: American Association for the Advancement of Science and Oxford University Press.
Smith PS, Nelson MM, Trygstad PJ, Banilower ER. 2013. Unequal distribution of resources for K–12 science instruction: Data from the 2012 National Survey of Science and Mathematics Education. Chapel Hill: Horizon Research.
Spiro RJ, Feltovich PJ, Jacobson MJ, Coulson RL. 1995. Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced acquisition in ill-structured domains. In: Constructivism in Education, eds Steffe LP, Gale J. Hillsdale, NJ: Lawrence Erlbaum Associates.
Spiro RJ, Collins BP, Thota JJ, Feltovich PJ. 2003. Cognitive flexibility theory: Hypermedia for complex learning, adaptive knowledge application, and experience acceleration. Educational Technology 43(5):5–10.
Sternberg RJ. 1985. Beyond IQ: A Triarchic Theory of Intelligence. Cambridge: Cambridge University Press.
Tonso KL. 2014. Engineering identity. In: Cambridge Handbook of Engineering Education Research, eds Johri A, Olds BM. New York: Cambridge University Press.
Tran N, Nathan MJ. 2010. An investigation of the relationship between precollege engineering studies and student achievement in science and mathematics. Journal of Engineering Education 99(2):143–157.
Tyson W. 2011. Modeling engineering degree attainment using high school and college physics and calculus coursetaking and achievement. Journal of Engineering Education 100(4):760-777.
Van Overschelde JP. 2013. Project Lead The Way students more prepared for higher education. American Journal of Engineering Education 4(1).
Yoon SY, Dyehouse M, Lucietto AM, Diefes-Dux HA, Capobianco BM. 2014. The effects of integrated science, technology, and engineering education on elementary students’ knowledge and identity development. School Science and Mathematics 14(8):380–392.
Zarske M, Yowell JL, Sullivan JF, Knight D, Wiant D. 2007. The TEAMS Program: A study of a grades 3–12 engineering continuum. Paper presented at the American Society of Engineering Education Annual Conference and Exposition, June 24–27, Honolulu. Available online at https://peer.asee.org/the-teams-program-a-study-of-a-grades3-12-engineering-continuum.pdf (accessed August 3, 2018).
This page intentionally left blank.