2
Engineering and K–12 Education
This chapter provides an overview of the essential elements of engineering; describes the important connections between engineering and the other three STEM subjects—science, technology, and mathematics; and reviews the different learning objectives for K–12 engineering. This background should be helpful to readers unfamiliar either with engineering or with engineering in K–12 settings.
WHAT IS ENGINEERING?
Engineering is both a knowledge of the creation and design of human-made products and processes and a problem-solving method called design under constraint.1 One such constraint is the laws of nature, such as the conservation of mass and energy, which are discoverable by science. Engineering cannot accomplish something that violates these laws. Other constraints include money, time, ergonomics, available materials, manufacturability, environmental regulations, and reparability. In addressing design challenges, engineering uses technological tools as well as concepts and practices from mathematics and science.
___________________
1 This definition is based on box 1-1 in NAE and NRC (2014).
In this section we provide an overview of three critical aspects of engineering: its essential qualities, the design process, and core concepts. We also briefly discuss engineering’s diversity challenge.
Essential Qualities of Engineering
Engineering exhibits a number of essential qualities (box 2-1) that help define the discipline and are shared with many other human endeavors.
Foremost among engineering’s essential qualities is that it is systematic and purposeful. The process of engineering design, described in the next section, is a systematic way of identifying needs, wants, and/or problems and then devising solutions to address them. The targets of engineering problem solving include complex, global-scale issues,2 such as providing access to clean water, as well as simple, everyday concerns, like controlling stoplights at a busy intersection. Engineering should not be confused with tinkering, a loosely structured process of trial and error that typically is not grounded in careful analysis or data collection.
Engineering is purposeful in that it is driven by explicit goals. This does not mean, however, that engineering problems have only one solution. In fact, engineering accommodates, emphasizes, and embraces multiple solutions, as long as they all satisfy the requirements and constraints set out at the beginning of the journey.
The journey of engineering is an iterative process involving repeated cycles of testing, data collection, analysis, and improvement to reach an optimal solution (the destination). This iterative approach to problem solving is necessary because early versions of a solution almost always fail to achieve the desired goal. It is much better for such failure to occur before a technology is introduced in the real world, while it can be addressed through improvements in the design. Engineering therefore embraces failure as an important and necessary element of technology development (Petroski 1992).
Modern engineering depends on teamwork. It relies on large, diverse, and often geographically dispersed groups of individuals. Most contemporary engineering challenges (e.g., NAE 2016) can be addressed only by combining expertise from multiple subdisciplines (e.g., mechanical, electrical, civil, and environmental) as well as the physical and life sciences, applied mathematics, and the humanities and social sciences. Turning an engineering solution
___________________
2 One framing of such issues is the National Academy of Engineering’s Grand Challenges for Engineering (engineeringchallenges.org).
into a commercially viable product requires even more diverse expertise, in areas such as marketing, finance, and patent and environmental law. Experts increasingly see this convergence among multiple fields to address important, complex societal challenges as a necessary condition for success in engineering research (NASEM 2017).
Engineering is creative, in the sense of being generative as well as involving imagination and flexible thinking, and inherently optimistic, in that it treats every problem as potentially solvable and every need as addressable (subject to the kinds of constraints described below). And although humans are not the only species capable of solving problems, the ability to engineer is quintessentially human. For all of recorded history, people have created and used tools to meet their needs and wants, using many of the techniques codified in modern engineering: identifying problems and building, testing, and refining solutions to them.
Finally, engineering is attentive to social and ethical concerns, for the simple reason that technology has positive and negative impacts on people, society, and the planet (e.g., NAE and NRC 2002). When designing a solution, engineers must take into account the needs and concerns of the populations to be served. This ensures that the culture and values of the end users inform technology development. Otherwise, even effective “solutions” may not be accepted or implemented.
The ethical dimension of engineering is relevant in the professional behavior of engineers as well as societal concerns about technological development. Like physicians following the Hippocratic Oath, engineers follow
codes of practice to ensure public safety, which is one of the reasons there are large margins of safety in engineered products and systems. More broadly, the ethical obligations of the engineer call for consideration of both those whom technology will benefit and those it may potentially harm. These obligations must account for the possibility that some benefits and harms may have been unanticipated in the original design. Ethical concerns arise in areas such as big data, climate change, emerging technologies such as synthetic biology and artificial intelligence, human-enhancement technologies, military technology, and sustainability.
Engineering Design
Engineering design is the problem-solving process used by engineers (box 2-2).
While the engineering design process always aims to address human wants and needs, there is no single model for describing it. Models vary in detail and structure, but all consist of a similar set of distinct steps (box 2-3).
Importantly, these steps rarely if ever occur in a linear fashion from start to finish. One might expect that the step of problem identification always comes first. However, other steps in the process, such as prototype development and testing, can lead engineers to discover information that changes the
very nature of the problem to be solved. Revisiting the initial design based on data from testing likewise might change thinking about which of the generated concepts is optimal. In addition, as noted in the earlier discussion on iteration, there can be many cycles of redesign and testing before engineers determine that a solution is acceptable. The nonlinear nature of engineering design is evident in the example models shown in figure 2-1.
Core Engineering Concepts
The engineering design process encompasses a number of core concepts, skills, and habits of mind.3 For example, in framing a problem engineers must understand the design requirements—the physical and functional needs that the design must satisfy—and use these to develop detailed specifications against which the success of the design will be measured. Equally important are the constraints within which the engineer must work; these may include available materials, time, money, and economical, legal, political, social, ethical, and aesthetic limitations inherent to or imposed on the design.
To select the best solution from among a number of competing alternatives, engineers engage in a process called optimization. When competing design requirements make it very difficult to select the most appropriate solution, engineers must decide to prioritize (and optimize) one attribute over another, a process of trade-off. A simple example might involve choosing to optimize low weight over cost savings in the design of an airplane wing, which might necessitate the use of lighter but more expensive materials.
___________________
3 A more detailed explication of these ideas appears in NAE and NRC (2009, pp. 82–92).
SOURCES: (Left to right) NGSS Lead States (2013, volume 2, appendix I), EiE (2019), Guerra et al. (2012). Reprinted with permission by the Museum of Science, Boston and the EiE® team.
Once a design enters the build-test-redesign (or create-improve) phase, engineers may use modeling—and must perform analysis—to evaluate and refine their solution. Modeling involves representing the essential features of processes or systems that facilitate engineering design and can contain graphical, physical, or mathematical representations. Analysis, typically involving data collection of some kind, is a systematic and detailed review that can inform design decisions, define or clarify problems, predict or assess performance, evaluate alternatives, determine economic feasibility, and/or investigate failures. Returning to the airplane case, engineers might use modeling software to simulate the effects of fast-moving air on the stability of one of the wing’s flaps, analyzing data from dozens of simulations of different flap configurations to determine which is most likely to behave reliably in flight. The chosen design might then be further modeled with a physical prototype, whose performance could be tested in a wind tunnel.
A final key idea in the engineering design process, and a central focus for engineering more broadly, is systems. A system is any organized collection of discrete elements (e.g., parts, processes, people) that work together in interdependent ways to fulfill one or more functions. To be effective designers, engineers must have a good grasp of how systems work and the factors that influence their performance.
Diversity in Engineering
No discussion of engineering would be complete without mentioning the field’s diversity challenge. Degree earning and employment in engineering are characterized by very limited gender, ethnic, and racial diversity (table 2-1). White and Asian males earn the vast majority of undergraduate degrees and hold the bulk of faculty positions in the field, and they hold the lion’s share of jobs in engineering. Women, African Americans, American Indians/Alaska Natives, and Hispanics of any race are significantly underrepresented in engineering education and occupations.
The relevance of diversity to the preparation and support of K–12 teachers of engineering will be discussed later in the report. Here the committee notes the value of diversity to the engineering design process, the subject of the preceding two sections, and to ensuring that all citizens have the opportunity to pursue an engineering career, a matter of social justice. Regarding the first point, research (e.g., Chubin et al. 2005; Corbett and Hill 2015; Emerson 2014; NAE 2002; Phillips 2014) finds that a more diverse workforce is more
| White | Hispanic | African American | Asian | American Indian/Alaska Native | Female | |
|---|---|---|---|---|---|---|
| Tenured/tenure-track engineering facultya | 55.9 | 3.8 | 2.4 | 28.3 | n/a | 17.4 |
| 4-year engineering degree recipientsb | 61.5 | 9.6 | 3.8 | 10.9 | 0.3 | 19.8 |
| Employed in engineering occupationsc | 69.2 | 8.3 | 3.6 | 16.3 | 0.2d | 15.6 |
| US populatione | 76.5 | 18.3 | 13.4 | 5.9 | 1.3 | 50.8 |
a Tenured/tenure-track faculty comprise full, associate, and assistant professors. Data for 2018 from Engineering by the Numbers (Roy 2019) based on a survey of 4-year, ABET-accredited institutions that awarded at least one degree that year.
b Calculations from the 2014 Integrated Postsecondary Education Data System; population of institutions from the NCES (NAE 2017, table 3-6).
c Data from the 2017 National Survey of College Graduates (NSF 2019, table 9-7).
d Includes males only; data for females suppressed by NSF for confidentiality reasons.
e Estimates for 2018 from US Census Bureau (2018).
creative and innovative than a homogeneous one. Given the critical role of engineering design and teamwork to engineering problem solving, it may be, as suggested by former NAE president Wm. A. Wulf, that without diversity “we limit the set of life experiences that are applied, and as a result, we pay an opportunity cost—a cost in products not built, in designs not considered, in constraints not understood, in processes not invented” (Wulf 1998, p. 9). Regarding the second, the abilities gained during an engineering education are versatile and relevant to a variety of occupations and fields, which helps explain the higher median lifetime earnings (NAE 2018, pp. 42–47) and lower unemployment rates (NAE 2018, pp. 47–48) of those with engineering degrees compared with those with other STEM and non-STEM degrees. For a variety of reasons, earnings are significantly lower for women and, especially, underrepresented groups who hold a BS engineering degree, compared with those for whites (Carnevale et al. 2011). Even taking this into account, an engineering degree offers significant socioeconomic benefits.
ENGINEERING’S RELATIONSHIP TO SCIENCE, TECHNOLOGY, AND MATHEMATICS
Engineering, science, and mathematics are interdependent disciplines, and advances in one often enable progress in another. For example, the basic scientific understanding of DNA’s structure and the discovery of chemical methods of decoding strands of genetic material led engineers to create genome-sequencing machines that generated massive amounts of data whose analysis required algorithms developed by mathematicians (Talesnik 2015). Gene sequencing led in turn to additional scientific discoveries and the potential for a new generation of computers that use principles of information storage in DNA (e.g., Extance 2016; Service 2017).
Although not strictly defined as a discipline, technology encompasses the entire system of knowledge, processes, devices, people, and organizations involved in the creation and operation of technological artifacts, as well as the artifacts themselves.4 In the example above, the process of decoding genetic information and the machines developed to do this work are technologies. Much of modern technology is a product of engineering, science, and mathematics, and people in all three fields use technological tools.
Science shares many of the essential characteristics of engineering described earlier in this chapter. Like engineering, science is a creative, systematic, and purposeful endeavor that pays heed to social and ethical concerns. Science develops models and theories to explain and predict phenomena. Like engineering, this process occurs through recursive and iterative testing and refinement. Failure of a model- or theory-based prediction is an expected step that indicates the direction for needed improvement of the model or theory, just as failure of a design prototype provides information that guides improvement of an engineering solution. While science seeks to eventually find a singular best theory to explain and predict phenomena in a particular domain, multiple competing ideas can coexist when there is no evidence that differentiates between them.
While engineering and science share many qualities, the disciplines also exhibit differences. The Framework for K–12 Science Education (NRC 2012), for example, highlights eight practices that underlie the work of both engineers and scientists while pointing out that three of them—developing and using models, planning and carrying out investigations, and analyzing and interpreting data—play out differently in the two disciplines (table 2-2).
___________________
4 This definition of technology is based on box 1-1 in NAE and NRC (2014).
TABLE 2-2 Notable Differences in the Shared Practices of Engineering and Science
| Engineering | Science |
|---|---|
|
Asking questions and defining problems |
|
| Engineering begins with a problem, need, or desire that suggests an engineering problem that needs to be solved. Engineers ask questions to define the engineering problem, determine criteria for a successful solution, and identify constraints. | Science begins with a question about a phenomenon and seeks to develop theories that can provide explanatory answers to such questions. A basic practice of the scientist is formulating empirically answerable questions about phenomena, establishing what is already known, and determining what questions have yet to be satisfactorily answered. |
|
Developing and using models |
|
| Engineering uses models and simulations to analyze flaws, strengths, and limitations in existing and proposed new systems. | Science uses models and simulations to develop explanations about natural phenomena. |
|
Planning and carrying out investigations |
|
| Engineers use investigations both to gain data essential for specifying design criteria or parameters and to test their designs. | Scientists use investigations to test existing theories and explanations or to revise and develop new ones. |
|
Analyzing and interpreting data |
|
| Engineers analyze data collected in the tests of their designs and investigations; this allows them to compare different solutions and determine how well each one meets specific design criteria. Engineers use a variety of tools to identify major patterns and interpret the results. | Scientific investigations produce data that must be analyzed in order to derive meaning and to identify significant patterns and features in the data. |
|
Constructing explanations and designing solutions |
|
| The goal of engineering is to design solutions to engineering problems using scientific knowledge and models of the material world. There is usually no single best solution but rather a range of solutions. Which one is the optimal choice depends on the criteria used for making evaluations. | The goal of science is the construction of theories that can provide explanatory accounts of features of the world. Scientific explanations are explicit applications of theory to a specific situation or phenomenon, perhaps with the intermediary of a theory-based model for the system under study. |
Adapted from NRC (2012), box 3-2.
LEARNING OBJECTIVES FOR K–12 ENGINEERING EDUCATION
The preceding sections reviewed key concepts and practices of engineering and suggested how engineering relates to the other three STEM subjects. With that background, we now consider how researchers and practitioners have translated these ideas into learning objectives for K–12 students. Learning objectives prioritize and organize a discipline’s content in a way that makes clear what students are expected to know and be able to do as a result of their educational experiences. Many times, learning objectives are presented in the form of curriculum standards.
K–12 engineering education efforts generally situate engineering among STEM subjects in one of two ways: engineering in the foreground, with science, mathematics, or both subjects in a supporting role; or science or mathematics, or both, in the foreground, with engineering in a supporting role. As might be expected, the line between these two perspectives is often blurry.
In the first case, science and mathematics serve engineering, with the primary goal of improving understanding of engineering and the quality of engineering design solutions. Students may apply scientific knowledge or engage in scientific experimentation—gathering, analyzing, and interpreting data—in order to better understand the design challenge and potential solutions. The focus, which is prevalent in standalone engineering courses or programs, is on using science and mathematics as tools of engineering.
In the second case, engineering serves science and mathematics, with the primary goal of improving student understanding of science and mathematics concepts and practices. This is a prevalent approach in many K–12 engineering education programs. In the committee’s survey of teacher preparation and professional development in engineering, for example, 70 percent of respondents indicated that one of their top three program goals was to improve science instruction, and 38 percent indicated a top goal was to improve mathematics instruction. The focus in this case is less on building student understanding of engineering than on enhancing student interest, motivation, and learning of science and/or mathematics.
Although the two framings of K–12 engineering education share characteristics, their different emphases can lead to different learning objectives for students and, by implication, their teachers. The next two sections present examples of both framings.
Science and Mathematics in the Service of Engineering
One high-level conception of the engineering knowledge and skills that K–12 students should acquire is presented by Moore and colleagues (2014, 2015), who developed a framework for “quality in engineering education” (table 2-3). The framework developers started with the student outcomes criteria developed by ABET to accredit undergraduate engineering programs.5 Using a design research methodology, Moore and colleagues initially compared the ABET criteria to Massachusetts state standards for K–12 science and technology/engineering education (MDOE 2006)6 to identify potential omissions or content inappropriate for K–12 students. A second iteration compared the evolving set of indicators to a larger group of state K–12 engineering standards. Altogether, the document underwent six cycles of revision, involving a mix of expert evaluations and comparisons with other presentations of K–12 engineering knowledge, skills, and habits of mind.
The framework considers the application of mathematics and science knowledge to be of central importance, but the document’s clear emphasis is on engineering. However, because the framework is very general, it is not directly usable as a guide to curriculum developers or providers of professional learning experiences for educators.
By comparison, the Standards for Technological Literacy: Content for the Study of Technology (STL), developed by the International Technology and Engineering Educators Association7 (ITEEA 2007),8 is a much more detailed effort to describe learning objectives for K–12 engineering. ITEEA developed STL with the help of advisory committees appointed by the National Research Council (NRC 1999) and National Academy of Engineering and received comments on various drafts from hundreds of reviewers, including teachers working at field test sites in schools around the country.
The STL, which are widely used by the technology education community, address engineering in three ways: what students should know about the attributes of design, what they should know about the engineering design process, and the abilities that students should have related to the design pro-
___________________
5 A 2017 revision of the ABET document (ABET 2017) combined and reworked the language of portions of the previous version’s 13 student outcomes.
6 Massachusetts published a revised version of these standards in 2016 (MDESE 2016).
7 In 2010, the organization changed its name from the International Technology Education Association to ITEEA, reflecting the field’s turn toward engineering education.
8 ITEA first published its standards in 2000 and has published two minor updates since then.
TABLE 2-3 Framework for Quality K–12 Engineering Education
| Key Indicator | Description | ||
| Central Aspects of Engineering | |||
| Processes of Design (POD) | Design processes are at the center of engineering practice. Solving engineering problems is an iterative process involving preparing, planning and evaluating the solution. Students should understand design by participating in each of the sub-indicators (POD-PB, POD-PI, POD-TE) below. | ||
| POD Sub-Indicators | |||
| Problem and Background (PB) | Identification or formulation of engineering problems and research and learning activities necessary to gain background knowledge. | ||
| Plan and Implement (PI) | Brainstorming, developing multiple solutions, judging the relative importance of constraints and the creation of a prototype, model or other product. | ||
| Test and Evaluate (TE) | Generating testable hypotheses and designing experiments to gather data that should be used to evaluate the prototype or solution, and to use this feedback in redesign. | ||
| Apply Science, Engineering, Mathematics Knowledge (SEM) | The practice of engineering requires the application of science, mathematics, and engineering knowledge and engineering education at the K-12 level should emphasize this interdisciplinary nature. | ||
| Engineering Thinking (E Think) | Students should be independent and reflective thinkers capable of seeking out new knowledge and learning from failure when problems arise. | ||
| Understand Engineering | |||
| Conceptions of Engineers and Engineering (CEE) | K-12 students not only need to participate in an engineering process, but understand what an engineer does. | ||
| Engineering Tools, Techniques, and Processes (E Tool) | Students studying engineering need to become familiar and proficient in the processes, techniques, skills, and tools engineers use in their work. | ||
| Professional Skills | Issues, Solutions, and Impacts (ISI) | To solve complex and multidisciplinary problems, students need to be able to understand the impact of their solutions on current issues and vice versa. | |
| Ethics (Ethics) | Students should consider ethical situations inherent in the practice of engineering. | ||
| Teamwork (Team) | In K-12 engineering education, it is important to develop students’ abilities to participate as a contributing team member. | ||
| Communication Related to Eng (Comm-Engr) | Communication is the ability of a student to effectively take in information and to relay understandings to others in an engineering context. | ||
SOURCE: Adapted with permission from Moore et al. (2015), figure 1.
cess. For illustrative purposes, we present the learning objectives associated with this third standard, Standard 11, in table 2-4.
In effect, STL Standard 11 attempts to operationalize learning associated with key elements of engineering design (box 2-2 and figure 2-1). One feature of STL, not present in Moore et al. (2015), is the separation of learning objectives into grade bands. This aspect reflects the idea that student learning should build from grade to grade over a student’s school career. Considerable evidence points to the fact that depth of knowledge and reasoning ability can build over the course of one’s education, in children as well as adults (NASEM 2018).
While work to delineate learning outcomes in K–12 engineering, like Moore et al. (2015) and STL, have acknowledged the importance of connecting engineering design to appropriate content in science and mathematics, few efforts have been made to specify the concepts from these two STEM domains with which students should be familiar. In part, this is because every engineering design challenge makes unique demands on students’ science and mathematics knowledge. Some problems may require little or no application of ideas from these disciplines, while others may demand significant conceptual understanding as well as ability to apply the concepts. Even within a particular design challenge scenario, there is likely to be considerable variation in expectations based on a student’s age or grade, prior coursework, and (as applicable) career and college goals.
Grubbs and colleagues (2018) have proposed specific science and mathematics learning objectives in different areas of engineering for high school students, using sources such as a taxonomy of fields and subfields developed for a review of STEM doctoral programs9 and elements of the Fundamentals of Engineering exam (NCEES 2017). Their proposed taxonomic structure calls out science and mathematics core and subconcepts relevant to mechanical, civil, electrical, and chemical engineering. The researchers have begun to consider what learning progressions in these content areas might look like (Huffman et al. 2018). (This research is discussed more fully in Chapter 5, Science and Mathematics for Engineering.)
___________________
9 Taxonomy of Fields and Their Subfields, revised 7/31/06. A resource of the Research Doctorate Programs of the NASEM Board on Higher Education and Workforce, available at https://sites.nationalacademies.org/PGA/Resdoc/PGA_044522.
| K–2 grade band | 3–5 grade band | 6–8 grade band | 9–12 grade band |
|---|---|---|---|
|
|
|
|
SOURCE: ITEA (2007). Permission granted by ITEEA. www.iteea.org.
Engineering in the Service of Science and Mathematics
As noted in chapter 1, the Next Generation Science Standards (NGSS; NGSS Lead States 2013) present a new vision for K–12 science education that includes connections to concepts and practices in engineering. The title alone suggests the primacy of science in the standards, as is obviously appropriate. A Framework for K–12 Science Education (NRC 2012, p. 12), on which NGSS is based, provides further clarification of the role of engineering vis-à-vis science:
[E]ngineering and technology provide a context in which students can test their own developing scientific knowledge and apply it to practical problems; doing so enhances their understanding of science—and, for many, their interest in science—as they recognize the interplay among science, engineering, and technology. We are convinced that engagement in the practices of engineering design is as much a part of learning science as engagement in the practices of science.
Like STL, NGSS presents progressions10 in student learning goals for K–12 engineering (table 2-5). NGSS terms its learning goals “performance expectations,” and each combines at least one science and engineering practice, one disciplinary core idea, and one crosscutting concept from the 2012 NRC Framework.11 In addition to serving as standalone standards, the per-
___________________
10 Technically, according to NRC (2014, p. 37), “The progressions in the NGSS are not learning progressions as defined in science education research because they neither articulate the instructional support that would be needed to help students achieve them nor provide a detailed description of students’ developing understanding. (They also do not identify specific assessment targets, as assessment-linked learning progressions do.) However, they are based on the perspective that instruction and assessments must be designed to support and monitor students as they develop increasing sophistication in their ability to use practices, apply crosscutting concepts, and understand core ideas as they progress across the grade levels.”
11Practices are “the major practices that scientists employ as they investigate and build models and theories about the world and . . . a key set of engineering practices that engineers use as they design and build systems.” Crosscutting concepts “have application across all domains of science.” A disciplinary core idea must meet “at least two” of the following four criteria: (1) Have broad importance across multiple sciences or engineering disciplines or be a key organizing principle of a single discipline; (2) Provide a key tool for understanding or investigating more complex ideas and solving problems; (3) Relate to the interests and life experiences of students or be connected to societal or personal concerns that require scientific or technological knowledge; or (4) Be teachable and learnable over multiple grades at increasing levels of depth and sophistication. That is, the idea can be made accessible to younger students but is broad enough to sustain continued investigation over years (NRC 2012, pp. 30–31).
TABLE 2-5 Grade-Band Performance Expectations in NGSS for Engineering Design
| K–2 grade band | 3–5 grade band | Middle school grade band | High school grade band |
|---|---|---|---|
| Ask questions, make observations, and gather information about a situation people want to change to define a simple problem that can be solved through the development of a new or improved object or tool. | Define a simple design problem reflecting a need or a want that includes specified criteria for success and constraints on materials, time, or cost. | Define the criteria and constraints of a design problem with sufficient precision to ensure a successful solution, taking into account relevant scientific principles and potential impacts on people and the natural environment that may limit possible solutions. | Analyze a major global challenge to specify qualitative and quantitative criteria and constraints for solutions that account for societal needs and wants. |
| Develop a simple sketch, drawing, or physical model to illustrate how the shape of an object helps it function as needed to solve a given problem. | Generate and compare multiple possible solutions to a problem based on how well each is likely to meet the criteria and constraints of the problem. | Evaluate competing design solutions using a systematic process to determine how well they meet the criteria and constraints of the problem. | Design a solution to a complex real-world problem by breaking it down into smaller, more manageable problems that can be solved through engineering. |
| Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs. | Plan and carry out fair tests in which variables are controlled and failure points are considered to identify aspects of a model or prototype that can be improved. | Analyze data from tests to determine similarities and differences among several design solutions to identify the best characteristics of each that can be combined into a new solution to better meet the criteria for success. | Evaluate a solution to a complex real-world problem based on prioritized criteria and trade-offs that account for a range of constraints, including cost, safety, reliability, and aesthetics, as well as possible social, cultural, and environmental impacts. |
| K–2 grade band | 3–5 grade band | Middle school grade band | High school grade band |
|---|---|---|---|
| Develop a model to generate data for iterative testing and modification of a proposed object, tool, or process such that an optimal design can be achieved. | Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem. |
SOURCE: NGSS Lead States (2013), pp. 183, 207, 244, 291.
formance expectations for engineering design are integrated with a number of NGSS’s disciplinary core ideas in science.
Both NGSS12 and STL13 propose learning goals related to how engineering affects and is affected by society, influences the environment, connects to disciplines other than those in STEM, and embodies ethical decision making. These topics are critical components of engineering literacy, which is discussed in chapter 3.
CONCLUSION
For many prospective K–12 teachers of engineering, the core ideas and practices of the discipline will be unfamiliar. Many educators, whose own experiences, education, and professional learning have emphasized the notion of getting a single “right” answer, initially may be uncomfortable with the open-ended nature of the engineering design process. For similar reasons,
___________________
12 This area is called Science, Technology, Society, and the Environment and is composed of two core ideas: (1) the interdependence of science, engineering, and technology and (2) the influence of engineering, technology, and science on society and the natural world (NRC 2013, pp. 442–446).
13 These are (1) the cultural, social, economic, and political effects of technology; (2) the effects of technology on the environment; (3) the role of society in the development and use of technology; and (4) the influence of technology on history (ITEA 2007, pp. 57–64).
they may be hesitant to accept and treat failure as a normal and expected part of student learning. Beyond these specific potential hurdles, educators may harbor a general fear that engineering is too different or difficult and, as a result, not something they could become skilled at teaching. It is thus encouraging, as the rest of the report will discuss, that K–12 teachers across the country—supported by peers, professional development providers, and others—are introducing students to the concepts, practices, and habits of mind of engineering.
REFERENCES
ABET [Accreditation Board for Engineering and Technology]. 2017. EAC Mapping C3: A-K to C3: 1-7. Available online at www.abet.org/wp-content/uploads/2018/03/C3_C5_mapping_SEC_1-13-2018.pdf (accessed June 15, 2018).
ABET. 2018. EAC Mapping C3: A-K to C3 1-7. Engineering Design. Available online at https://www.abet.org/wp-content/uploads/2018/03/C3_C5_mapping_SEC_1-132018.pdf (accessed December 19, 2018).
Carnevale A, Strohl J, Melton M. 2011. What’s It Worth? The Economic Value of College Majors. Washington: Georgetown University Center on Education and the Workforce.
Chubin DE, May GS, Babco EL. 2005. Diversifying the engineering workforce. Journal of Engineering Education 94(1):73–86.
Corbett C, Hill C. 2015. Solving the Equation: The Variables for Women’s Success in Engineering and Computing. Washington: AAUW.
Crawley EF, Brodeur DR, Soderholm DH. 2008. The education of future aeronautical engineers: Conceiving, designing, implementing and operating. Journal of Science Education and Technology 17(2):138–151.
EiE [Engineering is Elementary]. 2019. The Engineering Design Process. Museum of Science, Boston. Available online at https://www.eie.org/overview/engineering-design-process (accessed August 19, 2019).
Emerson CJ. 2014. Increasing Women in SETT: The Business Case. Newfoundland: WinSETT Centre.
Extance A. 2016. How DNA could store all the world’s data. Nature 537:22–24. Available online at www.nature.com/polopoly_fs/1.20496!/menu/main/topColumns/topLeftColumn/pdf/537022a.pdf (accessed August 19, 2019).
Grubbs ME, Strimel GJ, Huffman T. 2018. Engineering education: A clear content base for standards. Technology and Engineering Teacher 77(7):32–38.
Guerra L, Allen DT, Crawford RH, Farmer C. 2012. A unique approach to characterizing the engineering design process. Proceedings, ASEE Annual Conference and Exposition, June 10–13, San Antonio.
Huffman T, Strimel GJ, Grubbs M. 2018. Determining the engineering knowledge dimension: What all high school students should know to be engineering literate (fundamental). Proceedings, 2018 American Society for Engineering Education Annual Conference, Salt Lake City. Available online at https://www.asee.org/public/conferences/106/papers/21953/download (accessed December 21, 2018).
ITEA [International Technology Education Association]. 2007. Standards for Technological Literacy: Content for the Study of Technology, 3rd ed. Available online at https://www.iteea.org/File.aspx?id=67767&v=b26b7852 (accessed June 15, 2018).
MDESE [Massachusetts Department of Elementary and Secondary Education]. 2016. 2016 Massachusetts Science and Technology/Engineering Curriculum Framework. Available online at www.doe.mass.edu/frameworks/scitech/2016-04.pdf (accessed March 14, 2019).
MDOE [Massachusetts Department of Education]. 2006. Massachusetts Science and Technology/Engineering Curriculum Framework. Malden, MA.
Moore TJ, Glancy AW, Tank KM, Kersten JA, Smith KA, Stohlmann MS. 2014. A framework for quality K–12 engineering education: Research and development. Journal of Pre-College Engineering Education Research 4(1): Article 2.
Moore TJ, Tank KM, Glancy AW, Kersten JA. 2015. NGSS and the landscape of engineering in K–12 state science standards. Journal of Research in Science Teaching 52(3):296–318.
NAE [National Academy of Engineering]. 2002. Diversity in Engineering: Managing the Workforce of the Future. Washington: National Academy Press.
NAE. 2016. Grand Challenges for Engineering: Imperatives, Prospects, and Priorities: Summary of a Forum. Available online at https://www.nae.edu/Publications/Reports/152253.aspx (March 13, 2019).
NAE. 2017. Engineering Technology Education in the United States. Washington: National Academies Press.
NAE. 2018. Understanding the Educational and Career Pathways of Engineers. Washington: National Academies Press.
NAE and NRC [National Research Council]. 2002. Technically Speaking: Why All Americans Need to Know More about Technology. Washington: National Academies Press.
NAE and NRC. 2009. Engineering in K–12 Education: Understanding the Status and Improving the Prospects. Washington: National Academies Press.
NAE and NRC. 2014. STEM Integration in K–12 Education: Status, Prospects, and an Agenda for Research. Available online at https://www.nap.edu/catalog/18612/stem-integration-in-k-12-education-status-prospects-and-an (accessed September 10, 2019).
NASEM [National Academies of Sciences, Engineering, and Medicine]. 2017. A New Vision for Center-Based Engineering Research. Washington: National Academies Press.
NASEM. 2018. How People Learn II: Learners, Contexts, and Cultures. Washington: National Academies Press.
NCEES [National Council of Examiners for Engineering and Surveying]. 2017. FE Exam Specifications. Available online at http://ncees.org/engineering/fe/ (accessed December 21, 2018).
NGSS [Next Generation Science Standards] Lead States. 2013. Next Generation Science Standards: For States, By States. Washington: National Academies Press. Available online at https://www.nap.edu/catalog/18290/next-generation-science-standards-for-states-by-states (accessed March 28, 2018).
NRC [National Research Council]. 1999. Final Letter Report of the International Technology Education Association Standards Review Committee. Washington: National Academy Press. Available online at https://www.nap.edu/catalog/9765/final-letter-report-of-the-international-technology-education-association-standards-review-committee (accessed June 25, 2018).
NRC. 2012. A Framework for K–12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington: National Academies Press. Available online at https://www.nap.edu/catalog/13165/a-framework-for-k-12-science-education-practices-crosscutting-concepts (accessed March 28, 2018).
NRC. 2014. Developing Assessments for the Next Generation Science Standards. Washington: National Academies Press.
NSF [National Science Foundation]. 2019. National Survey of College Graduates: 2017. Available online at https://www.nsf.gov/statistics/srvygrads/#tabs-2 (accessed December 31, 2019).
Petroski H. 1992. To Engineer Is Human: The Role of Failure in Successful Design. New York: Vintage Press.
Phillips KW. 2014. How diversity makes us smarter. Scientific American, September 16.
Roy J. 2019. Engineering by the Numbers. Washington: American Society for Engineering Education. Available online at www.asee.org/documents/papers-and-publications/publications/college-profiles/2018-Engineering-by-Numbers-Engineering-StatisticsUPDATED-15-July-2019.pdf (accessed December 31, 2019).
Service RF. 2017. DNA could store all of the world’s data in one room. Science, March 2. Available online at https://www.sciencemag.org/news/2017/03/dna-could-store-all-worlds-data-one-room (accessed August 20, 2019).
Talesnik D. 2015. “Doing the math” adds up to big genomic discoveries. NIH Record 67(10). Available online at https://nihrecord.nih.gov/newsletters/2015/05_08_2015/story3.htm (accessed March 11, 2019).
US Census Bureau. 2018. Quick facts. Available online at https://www.census.gov/quickfacts/fact/table/US/IPE120217 (accessed December 31, 2019).
Wulf WA. 1998. Diversity in engineering. The Bridge 28(4):8–13.
This page intentionally left blank.
