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Building Capacity for Teaching Engineering in K-12 Education (2020)

Chapter: 5 Professional Learning

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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Suggested Citation:"5 Professional Learning." National Academies of Sciences, Engineering, and Medicine. 2020. Building Capacity for Teaching Engineering in K-12 Education. Washington, DC: The National Academies Press. doi: 10.17226/25612.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

PREPUBLICATION COPY, UNCORRECTED PROOFS 5 Professional Learning The goals for teaching engineering in US classrooms are both ambitious and varied, but, as explained in chapter 4, the majority of K–12 educators do not currently teach engineering and have little preparation to do so. Whether they are to teach for engineering literacy, integrate engineering in STEM education more generally, prepare students to be college and career ready, or educate future engineering majors, teachers will need certain knowledge and skills as well as opportunities to acquire those competencies. This chapter explores two questions: 1. What are teachers’ learning needs for teaching engineering? 2. What learning opportunities will teachers require to meet those needs? The first question explores the professional knowledge and skills built from and for teaching. The second focuses on the opportunities for teacher learning that lead to the development and growth of the knowledge and skills. The committee sought evidence related to both questions. LEARNING NEEDS FOR TEACHING ENGINEERING To understand the potential learning needs of K–12 teachers of engineering, we begin by looking at what researchers believe are important learning needs of K–12 teachers generally, which has been the focus of considerable scholarship, analysis, and policymaking. In part this is because of the assumed causal connections between specific aspects of professional knowledge, teaching behaviors, and student outcomes. Unfortunately, there is little consistent evidence that elementary teachers need specific mathematical knowledge or that science teachers who use a particular instructional strategy always produce learning gains in students (e.g., NRC 2010). This may be because a great deal of research on teaching and learning focuses on singular aspects of education, whereas teachers work on multiple fronts at once. Alternatively, the contextual, situated nature of teaching and learning may thwart efforts to identify simple causal connections. Nonetheless, various groups have attempted to delineate what K–12 teachers need to know and be able to do, with the belief that certain approaches are more likely to lead to student success than others. These efforts include handbooks (e.g., Cochran-Smith and Zeichner 2005; Darling-Hammond and Bransford 2005); state and professional organization standards for teachers (e.g., NBPTS 2016; NCTM 2017; NSTA 2012); the content of teacher preparation and professional programs, teacher licensure, and certification examinations (e.g., Praxis content knowledge and teaching examinations); teacher development and evaluation systems (e.g., Danielson 2014); teacher assessments developed for research purposes (Ball et al. 2008; Hill and Ball 2004; Hill et al. 2004); and teacher and program accreditation and teacher certification requirements. Across these different documents and contexts, teacher knowledge and skill are parsed in different ways. It was beyond the scope of the committee’s work to synthesize the many different conceptualizations of teacher learning needs. However, readers may benefit by seeing two better- known efforts to define the body of knowledge for K–12 educators. The Danielson (2014) Framework (box 5-1), the basis for a widely used teacher development and evaluation system, parses teacher professional knowledge into four domains with 22 subdomains that are further 94

PREPUBLICATION COPY, UNCORRECTED PROOFS subdivided into 76 smaller elements. The framework is based on logical analyses of what the work of teaching entails, a broad reading of relevant research, and feedback from educators across the country who have used various iterations of the document. Notably, the framework is subject-matter agnostic; that is, its guidance is independent of the subject taught. BOX 5-1 Danielson Framework Domain 1: Planning and Preparation 1a. Demonstrating Knowledge of Content and Pedagogy 1b. Demonstrating Knowledge of Students 1c. Setting Instructional Outcomes 1d. Demonstrating Knowledge of Resources 1e. Designing Coherent Instruction 1f. Designing Student Assessments Domain 2: Classroom Environment 2a. Creating an Environment of Respect and Rapport 2b. Establishing a Culture for Learning 2c. Managing Classroom Procedures 2d. Managing Student Behavior 2e. Organizing Physical Space Domain 3: Instruction 3a. Communicating with Students 3b. Using Questioning and Discussion Techniques 3c. Engaging Students in Learning 3d. Using Assessment in Instruction 3e. Demonstrating Flexibility and Responsiveness Domain 4: Professional Responsibilities 4a. Reflecting on Teaching 4b. Maintaining Accurate Records 4c. Communicating with Families 4d. Participating in the Professional Community 4e. Growing and Developing Professionally 4f. Showing Professionalism SOURCE: Danielson (2014). Reprinted with permission. Copyright. 2014. All rights reserved. Sykes and Wilson (2015), in their review of research on teaching, nominate two domains of professional knowledge with a number of associated subdomains (table 5-1). Like Danielson, this framework is subject-matter agnostic. TABLE 5-1 Sykes and Wilson Framework Domain I: Instruction Domain II: Professional Role Responsibilities Planning Collaborating with other professionals  Using professional networks 95

PREPUBLICATION COPY, UNCORRECTED PROOFS  Preparing and planning for high quality  Communicating professionally, both in instruction person and via technology  Drawing on students’ cultural, family,  Collaborating in professional learning intellectual, and personal experiences and communities and on teams resources  Exercising leadership, both formally and  Promoting community participation as informally opportunity to explore core values  Setting long- and short-range learning goals and objectives  Mastering lesson content for instructional purposes  Selecting and adapting resources for use in instruction  Selecting/designing instructional tasks, activity structures, and formats  Planning assessments Relational aspects Working with families and communities  Attending to relational aspects of instruction  Developing caring and respectful  Fostering two-way, respectful relationships with individual students communication with parents and guardians  Attending to and promoting student social  Using family- and community-related and emotional needs and learning information as a resource for learning  Building positive classroom climate Social/academic life Fulfilling ethical responsibilities  Establishing and maintaining the social and  Enacting the basic moral principles and academic culture duties associated with the role of teacher  Implementing organizational routines, and exercising diligence and prudence in norms, strategies, and procedures to support observing these duties a learning environment  Responding to ethical dilemmas with sound  Managing the physical and material reasoning and actions environment  Detecting and correcting biases of various  Managing instructional groupings kinds via reflection and feedback  Using time productively  Advocating appropriately for students Interactive teaching Meeting legal responsibilities  Attending to instructional purposes  Complying with all relevant laws and  Enacting instructional tasks and activities regulations  Engaging students with subject matter  Creating and maintaining accurate records  Orchestrating productive discourses of student progress and related matters  Providing strategy instruction  Assessing and responding to student learning during instruction Improvement  Engaging in instructional improvement  Improving instructional routines  Engaging in deliberate practice SOURCE: Sykes and Wilson (2015). © 2015 Educational Testing Service. Reprinted by permission of Educational Testing Service, the copyright owner. All other information contained within this 96

PREPUBLICATION COPY, UNCORRECTED PROOFS publication is provided by National Academies Press and no endorsement of any kind by Educational Testing Service should be inferred. 97

PREPUBLICATION COPY, UNCORRECTED PROOFS The Interstate Teacher Assessment and Support Consortium (InTASC) model core teaching standards and learning progressions offer yet another, similar conceptualization (box 5-2). BOX 5-2 InTASC Core Teaching Standards The Learner and Learning Standard 1: Learner Development—The teacher understands how learners grow and develop, recognizing that patterns of learning and development vary individually within and across the cognitive, linguistic, social, emotional, and physical areas, and designs and implements developmentally appropriate and challenging learning experiences. Standard 2: Learning Differences—The teacher uses understanding of individual differences and diverse cultures and communities to ensure inclusive learning environments that enable each learner to meet high standards. Standard 3: Learning Environments—The teacher works with others to create environments that support individual and collaborative learning, and that encourage positive social interaction, active engagement in learning, and self motivation. Content Standard 4: Content Knowledge—The teacher understands the central concepts, tools of inquiry, and structures of the discipline(s) he or she teaches and creates learning experiences that make the discipline accessible and meaningful for learners to assure mastery of the content. Standard 5: Application of Content—The teacher understands how to connect concepts and use differing perspectives to engage learners in critical thinking, creativity, and collaborative problem solving related to authentic local and global issues. Instructional Practice Standard 6: Assessment—The teacher understands and uses multiple methods of assessment to engage learners in their own growth, to monitor learner progress, and to guide the teacher’s and learner’s decision making. Standard 7: Planning for Instruction—The teacher plans instruction that supports every student in meeting rigorous learning goals by drawing upon knowledge of content areas, curriculum, cross-disciplinary skills, and pedagogy, as well as knowledge of learners and the community context. Standard 8: Instructional Strategies—The teacher understands and uses a variety of instructional strategies to encourage learners to develop deep understanding of content areas and their connections, and to build skills to apply knowledge in meaningful ways. Professional Responsibility Standard 9: Professional Learning and Ethical Practice—The teacher engages in ongoing professional learning and uses evidence to continually evaluate his/her practice, particularly the effects of his/her choices and actions on others (learners, families, other professionals, and the community), and adapts practice to meet the needs of each learner. Standard 10: Leadership and Collaboration—The teacher seeks appropriate leadership roles and opportunities to take responsibility for student learning, to collaborate with learners, families, colleagues, other school professionals, and community members to ensure learner growth, and to advance the profession. SOURCE: CCSSO 2013. 98

PREPUBLICATION COPY, UNCORRECTED PROOFS Despite some differences, these two conceptions of the professional knowledge base of K–12 educators align in a number of ways. They treat similarly aspects of teaching practice (planning or reflection, for example); strategies for teaching and for enabling learning; approaches to organizing and managing the spaces in which learning takes place; and how teachers’ work with students, parents, administrators, and colleagues inside and outside of classrooms. Certainly, many elements of these general frameworks will be relevant to the preparation of K–12 teachers of engineering, but these educators also have unique learning needs. Unfortunately, there has been little direct scholarship on the specific professional knowledge base for teachers of engineering. Despite this limitation, researchers have drawn on studies and the experience of practitioners to create guidelines, such as the Standards for Preparation and Professional Development of Teachers for Engineering (Farmer et al. 2014; box 5-3), to help support teacher professional learning in this domain. Because they focus on teacher professional learning rather than on teaching as in the previous frameworks, these standards highlight not only what teachers need to know but how they might learn it. BOX 5-3 Standards for the Preparation and Professional Development for Teachers of Engineering Standard A: Engineering Content and Practices: Professional development for teachers of engineering should address the fundamental nature, content, and practices of engineering as defined above. To promote literacy in the category of engineering design, it should: 1. Engage teams of participants in authentic engineering practices and processes (i.e., participating in the engineering design process as initiated by a design challenge statement, through at least one improvement cycle, and involving communication of results); 2. Introduce participants to tools that enable success in engineering; such tools include engineering notebooks, simple tools (e.g., rulers), and more sophisticated technologies (e.g., computer probeware and software, digital multimeters); 3. Introduce participants to strategies that enable success in engineering; key strategies include engaging in teams, asking questions, communication about design, and carefully documenting work; 4. Encourage participants to reflect on multiple experiences with the engineering design process, whether these have occurred within or outside the context of the current professional development opportunity, to reinforce learning about engineering content and practices; and 5. Enable participants to compare design in engineering to design in other fields (e.g., fashion, architecture, art). To promote literacy in the category of engineering careers, such professional development should: 1. Provide opportunities for participants to learn about engineering fields and professions; 2. Engage participants in comparing engineering with non-engineering content areas (e.g., mathematics, science, social studies, English language arts, the arts, technology education); 3. Engage participants in comparing classroom-based engineering experiences with professional engineering practice; and 4. Provide opportunities for educators to learn about the pre-collegiate and collegiate academic preparation required for engineering careers. To promote literacy in the category of engineering and society, such professional development should: 99

PREPUBLICATION COPY, UNCORRECTED PROOFS 1. Provide opportunities for participants to explore the work of engineers and their contributions to society, as well as ways in which some engineered solutions have caused societal challenges. Standard B: Pedagogical Content Knowledge for Teaching Engineering: Professional development for teachers of engineering should emphasize engineering pedagogical content knowledge. It should: 1. Engage participants in exploring teaching and learning in engineering and how it is similar to, and different from, teaching and learning in science and/or mathematics; 2. Introduce participants to effective classroom management strategies for enabling learning in engineering; 3. Foster participants’ ability to develop design challenges that are appropriate for their student population, teaching environments, and/or local community; 4. Facilitate participants’ reflection upon their own teaching practice and encourage participants to seek feedback from others to refine and optimize their engineering teaching practice; and 5. Promote and support participants’ engagement with engineering mentors who can, in turn, support participants’ teaching of engineering through a variety of approaches (e.g., field experiences, field trips, internships, collaborations, classroom visits). Standard C: Engineering as a Context for Teaching and Learning: Professional development for teachers of engineering should make clear how engineering design and problem solving offer a context for teaching standards of learning in science, mathematics, language arts, reading, and other subjects. It should: 1. Enable participants to explore research that demonstrates how using engineering design and problem solving as a context for learning improves students’ critical thinking skills and academic achievement; 2. Engage participants in engineering design challenges that require horizontal integration with non-engineering content (e.g., mathematics, science, social studies, English language arts, the arts, technology education); 3. Draw attention to the way in which engineering design and problem solving reinforce skills (e.g., 21st century skills such as creativity, communication, critical thinking, and collaboration) and practices (e.g., modeling, data analysis, and presentation) that are relevant to many fields; and 4. Encourage participants to integrate engineering into the existing curriculum. Standard D: Curriculum and Assessment: Professional development for teachers of engineering should empower teachers to identify appropriate curriculum, instructional materials, and assessment methods. It should: 1. Enable participants to identify engineering curriculum that is developmentally, instructionally, and cognitively appropriate for their students; 2. Engage participants in evaluating the potential of engineering curriculum to address one or more sets of student learning standards (e.g., ITEEA learning standards, Next Generation Science Standards, state standards); 3. Engage participants in evaluating the potential of engineering curriculum to support a particular set of engineering learning objectives; 4. Engage participants in evaluating the adaptability of engineering curriculum to local conditions (e.g., scheduling/timing, emphasis on content/methods, cultural context, similarity to other activities in an existing curriculum); 100

PREPUBLICATION COPY, UNCORRECTED PROOFS 5. Engage participants in evaluating the available teacher support for a particular engineering curriculum; 6. Engage participants in examining the authenticity and appropriateness of formative and summative assessments embedded in a curriculum; and 7. Demonstrate connections and alignment between engineering curriculum, instruction, learning, and assessment. Standard E: Alignment to Research, Standards, and Educational Practices: Professional development for teachers of engineering should be aligned to current educational research and student learning standards. It should: 1. Be developed and refined in collaboration with experts in the fields of engineering, engineering pedagogy, and teacher professional development; 2. Be developed and refined in collaboration with stakeholders (e.g., state education agency personnel, school administrators, teachers); 3. Enable participants to experience the curriculum that they will teach; 4. Model effective engineering teaching practices; 5. Employ differentiated instruction techniques; 6. Be guided by formative assessment; 7. Encourage risk-taking by participants; 8. Be longitudinal; and 9. Evolve through a process of continuous improvement that employs ongoing evaluation, assessment and revision. SOURCE: Farmer et al. (2014). Reprinted with permission. In developing the standards, Farmer and colleagues turned to a previous, similar effort in science education, the National Science Education Standards (NSES; NRC 1996). They took the general principles for teacher professional development (PD) described in NSES and incorporated ideas from the emerging consensus on learning goals for K–12 engineering education (e.g., NAE and NRC 2009). They also reviewed relevant research in science education, teacher preparation and development, and adult learning. (Reimers et al. 2015 summarize the research base underlying the standards.) Stakeholders in K–12 and postsecondary education provided input on drafts of the standards. Farmer and Klein-Gardner (2014) then used the final version of the document to create a matrix that providers of PD for K–12 teachers of engineering could use to map their efforts to elements in the standards. Ten providers of K–12 engineering professional development beta-tested the matrix before it was published by the American Society for Engineering Education. Although the focus of the standards is on providing high-level guidance to teacher education and PD programs, not on the desired competencies of K–12 engineering teachers per se, normative guidance for high-quality programs can suggest the professional knowledge required for high-quality engineering instruction. And while some elements of the standards are consistent with the general guidance in the Danielson and Sykes/Wilson frameworks, they also differ in significant ways, particularly Standard A, which addresses engineering content and practices, and Standard B, which addresses pedagogy. Because K–12 technology or science teachers may teach engineering (see chapter 4), the committee also reviewed standards for professional learning in those subjects for additional insights into the learning needs of K–12 teachers of engineering. Advancing Excellence in 101

PREPUBLICATION COPY, UNCORRECTED PROOFS Technological Literacy: Student Assessment, Professional Development, and Program Standards (AETL; ITEA 2003) is a companion volume to the Standards for Technological Literacy: Content for the Study of Technology (STL) developed by the technology education community (ITEA 2000). As noted in chapter 2, STL expects students to understand and be able to apply the engineering design process. Presumably, the same should be true for technology teachers. Although AETL does not call out these engineering-specific learning goals for teachers, they are implied in Standard PD-1, which expects teacher education programs to provide prospective teachers with “knowledge, abilities, and understanding consistent with” STL (p. 42). As noted in chapter 4 (box 4-2), new standards for science teacher preparation programs (Morrell et al. 2019) include elements of engineering. For example, Standard 1, on content knowledge, calls on prospective teachers to “connect important disciplinary core ideas, crosscutting concepts, and science and engineering practices for their fields of licensure” (p. 1). Standard 2c, on content pedagogy, specifies that teachers should be able to “Us[e] engineering practices in support of science learning wherein all students design, construct, test and optimize possible solutions to a problem” (p. 1). And Standard 5a, related to impacts on student learning, expects prospective teachers to “implement assessments that show all students have learned and can apply disciplinary knowledge, nature of science, science and engineering practices, and crosscutting concepts in practical, authentic, and real-world situations” (p. 3). However, the Standards for the Preparation and Professional Development of Teachers of Engineering is by far the most detailed and most relevant to the committee’s statement of task. With the exception of Goal 4’s expectations related to preparation for matriculation in postsecondary engineering programs, the standards provide a reasonable, if aspirational, outline of the knowledge and skills needed by K–12 teachers of engineering. They also address a number of the general concerns in the Danielson and Sykes/Wilson frameworks related to such issues as classroom management, assessment, working with diverse populations, and the need for continuous improvement. Engineering Content and Practices We now turn from the general guidance provided by teacher PD standards to more specific ideas about the knowledge base for K–12 teachers of engineering in three critical areas of engineering content and practice: engineering design, STEM integration, and science and mathematics for engineering. This section draws on a limited number of scholarly publications, nearly all of which are descriptive in nature, and sources such as teacher preparation course descriptions and frameworks for teacher certification. As noted in chapter 1, descriptive research may provide a basis for developing additional testable hypotheses about causes, and it may offer some testable insights about potential mechanisms, but it cannot be used to make causal claims. Engineering Design It seems logically sound to assert that all engineering teachers should have a foundational level of engineering literacy. A key aspect of such literacy is to understand the engineering design process, which includes both content (the concepts embedded in the process) and practices (carrying out the process itself). Research suggests that practicing the process of engineering design enables K–12 teachers to (1) develop their content knowledge in engineering (Custer and Daugherty 2009; Donna 2012; English et al. 2013; Moore et al. 2014) and (2) increase their 102

PREPUBLICATION COPY, UNCORRECTED PROOFS comfort and proficiency with the skills and strategies of engineering design (Brophy et al. 2008; Hsu et al. 2011). A potential pitfall of working toward new models of instruction, especially for those who have little or no experience with a given subject area, is reducing complex instructional tasks in an effort to simplify implementation without attention to the underlying intellectual work in which students need to engage. For instance, teachers who do not have a full grasp of the engineering design process may reduce it to a sequence of steps that students must memorize and follow exactly (McCormick 2004) rather than teaching it as an iterative, collaborative, and creative process as described in chapter 2. One study found that teachers implementing an engineering lesson for the first time focused on the activity’s logistics (e.g., specific steps in the design process) rather than the connections to engineering work, science, or mathematics (Diefes-Dux 2014). It is only once teachers gain a comfort level with the logistics that they begin to consider connections with other subjects and achieve deeper understanding of engineers and engineering. In addition, teachers with little exposure to engineering design may adopt a deficit model of failure, seeing failure as negative and something to be avoided (Lottero-Perdue and Parry 2014). In contrast, those with experience delivering curriculum that treats failure as an opportunity for student growth come to see failure as an important element of instruction (Lottero-Perdue 2015; Lottero-Perdue and Parry 2017). A multiple case study that examined five engineering PD programs associated with curriculum development projects for high school teachers found that the programs emphasized the process of design rather than disciplinary knowledge needed for engineering work or pedagogical content knowledge (Daugherty and Custer 2012). Professional learning experiences that delved more deeply into the engineering process—for example, by exploring the roles of analysis, systems, and modeling—helped educators not only develop deeper understanding of these concepts and practices but also integrate engineering activities in their classrooms to promote student science learning (Custer et al. 2014). For purposes of assessment, it may be important for K–12 teachers of engineering to understand and have experience with the many forms that student design solutions can take (Brophy et al. 2008). Assessing student design activities differs in many ways from the grading of activities with clear right and wrong answers (e.g., addition and subtraction, naming the parts of a cell), and this suggests a need for professional learning experiences that explicitly target assessment (Hynes et al. 2014). Studies have called for the development of frameworks to support teachers as they create and use their own tools to assess student learning in engineering design (Diefes-Dux et al. 2012; Hjalmarson and Diefes-Dux 2008). STEM Integration The different goals for K–12 engineering education suggest that many teachers of engineering will need to master concepts and practices that go beyond engineering design. Chapter 3 (“The Goal of Improving Mathematics and Science Achievement through Integrated STEM Learning”) discusses the potential benefits to students of experiencing STEM education in a more integrated way. For this to occur, teachers must be able to create learning opportunities that leverage connections between and among STEM concepts and practices. This capability would be important not only for technology and engineering educators, who need to support students’ use of science and mathematics ideas to address engineering challenges, but also for science and 103

PREPUBLICATION COPY, UNCORRECTED PROOFS mathematics teachers tasked with integrating engineering concepts and practices into their instruction, as called for in the Next Generation Science Standards (NGSS Lead States 2013). One potential benefit of STEM integration that involves engineering is that students may achieve deeper learning of science and mathematics concepts when exploring them in the context of engineering design. In addition, learning science and mathematics through relevant, real-world design challenges may boost student interest and motivation to learn. The committee again acknowledges that, as noted in chapter 3, the evidence for engineering leading to learning or achievement in science and mathematics is mixed (NAE and NRC 2014, pp. 56–60), the number of high-quality studies in this area is limited (e.g., Fortus et al. 2004; Klein and Sherwood 2005; Kolodner et al. 2003), and there is similarly limited evidence of the potential of STEM integration to affect student engagement. However, some major education reform efforts, such as the Next Generation Science Standards (NGSS Lead States 2013), are moving in the direction of integration and, as noted in the framework for NGSS (NRC 2012, p. 12): [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. Science and Mathematics for Engineering Student learning goals in engineering, technology, and science and teacher preparation standards in these subjects all note the importance of being able to use appropriate concepts and practices from science and mathematics to inform engineering problem solving. Despite interest among practitioners and policymakers in the idea of K–12 STEM integration, however, researchers have made few attempts to identify the specific ideas and practices from science and mathematics that students or teachers need in order to support their engineering learning or teaching. Although there is limited empirical evidence in this area, there are at least three ways of thinking about the science and mathematics knowledge that K–12 teachers of engineering require. Teachers might be expected to have a baseline of knowledge of key concepts/practices across several subdisciplines in mathematics (i.e., in keeping with the Common Core State Standards [NGA Center for Best Practices, Council of Chief State School Officers 2010]) and science (i.e., in keeping with NGSS [NGSS Lead States 2013]), regardless of when it is applied. They might need to know concepts and/or practices that are directly relevant to a particular design problem or context. Or they might need both a general baseline of knowledge and specific knowledge relevant to a particular design activity. Logically, the breadth and depth of science and mathematics knowledge needed by K–12 teachers of engineering will vary according to grade, the specific curriculum, and the goals of instruction. Many elementary teachers already teach basic science and mathematics, so the question for this group may be how and under what circumstances this baseline of knowledge might be supplemented. For example, the Engineering is Elementary curriculum includes an engineering challenge based on construction of a solar oven: 3rd and 4th grade students need to learn science ideas related to heat transfer in order to complete the project (Cunningham 2018, pp. 34–35), and use mathematical skills to calculate rates of change. In a curriculum developed at the Hofstra Center for STEM Research, middle school students tasked with designing a 104

PREPUBLICATION COPY, UNCORRECTED PROOFS bedroom1 complete a set of “knowledge and skill builders,” short, focused activities to help them identify the variables that affect the performance of the design (Burghardt and Krowles 2006). The students learned mathematical ideas related to geometric shapes, factoring, percentage, and scale. As teachers become more specialized at the middle school and, especially, high school levels, those who teach engineering will likely need deeper understanding about a greater number of science and mathematics ideas, as well as knowledge of how to help students apply them in service to engineering. Research finds some technology teacher preparation programs include few if any higher-level mathematics and science courses (Litowitz 2014), suggesting a possible weakness in this source of K–12 teachers of engineering. Beyond these kinds of context-specific examples, there are very few places to turn for guidance on what science and mathematics concepts are most relevant to K–12 engineering education. One exception is a taxonomic structure for high school engineering (Huffman et al. 2018) that may in part address the needs of teachers of more advanced engineering classes (Goal 4 from chapter 3). To create the taxonomy, the researchers used a three-round Delphi study to identify initial content and expert focus groups to provide more detailed concept development. The taxonomy spells out core concepts and subconcepts in science and mathematics that students exploring different subdisciplines of engineering should understand (table 5-2). For example, core concepts in many disciplines of engineering are statics, dynamics, mechanics of materials, and electrical power, each of which have several subconcepts. Some of these require mathematics understanding (e.g., stress-strain analysis, force acceleration), while others implicate science understanding (e.g., materials characteristics, properties, and composition, magnetism). TABLE 5-2 Abbreviated sample of core concepts and subconcepts of engineering for secondary school students. Core Concept of Engineering Subconcepts Resultants of force systems Statics Equivalent force systems Equilibrium of rigid bodies Kinematics (e.g., particles and rigid bodies) Dynamics Mass moments of inertia Force acceleration (e.g., particles and rigid bodies) Stress types and transformations Material characteristics, properties, and composition (e.g., heat Mechanics of Materials treating) stress-strain analysis Motors and generators Electrical Power Transmission and distribution Magnetism SOURCE: Huffman et al. (2018). Reprinted with permission. 1 https://www.hofstra.edu/academics/colleges/seas/ctl/itea/itea_activity_bedroomdesign.html 105

PREPUBLICATION COPY, UNCORRECTED PROOFS One limitation of this work for the committee’s purposes is that the taxonomy targets student learning, not teacher learning. However, it is reasonable to expect that teachers of engineering, especially those teaching more advanced classes, would need at least the same level of subject- matter knowledge in science and mathematics as the students they teach. Given the broader literature on teacher professional knowledge, it is also likely that that minimal knowledge would be inadequate and teachers would probably need more extensive content knowledge, as well as relevant pedagogical content knowledge (discussed below). In any case, this is one of the few examples the committee could find that attempts to describe the landscape of mathematics and science concepts relevant for higher-level work in K–12 engineering. Another possible approach to determining the requisite knowledge in science and mathematics needed by K–12 teachers of engineering is to examine the content frameworks for state teacher certification tests in this area. An analysis of all such frameworks was beyond the committee’s scope of work, but examination of a small number of such documents shows considerable variation in their content. One detailed certification framework for prospective engineering teachers is the Texas TExES Mathematics/Physical Science/Engineering 6–12 teacher examination,2 which covers 12 domains, two of which (Engineering Method and Engineering Profession) specifically address engineering (table 5-3). (Questions based on content from these two domains account for 30 percent of credit on the exam.) TABLE 5-3 Engineering-Related Domains and Standards in Texas’s Certification Exam for Grade 6–12 Teachers of Mathematics/Physical Science/Engineering. Permission Pending SOURCE: Texas Education Agency (2018). 2 Information about the exam is available at https://www.tx.nesinc.coTm/TestView.aspx?f=HTML_FRAG/TX274_TestPage.html, and a preparatory manual is available here: https://www.tx.nesinc.com/Content/Docs/274PrepManual.pdf. 106

PREPUBLICATION COPY, UNCORRECTED PROOFS Each domain has standards with associated competencies that broadly define the knowledge and skills that beginning teachers should possess and include details about what specific knowledge and skill the certification exam will cover. Most relevant to this study is Competency 044,3 which spells out the knowledge of engineering fundamentals that the “beginning teacher” should have: A. Applies principles related to statics (e.g., moment, stress, strain) to analyze systems and solve problems. B. Applies principles of dynamics (e.g., force, acceleration, moment of inertia) to model and solve problems. C. Understands terminology (e.g., analog, digital) and concepts related to electric circuits (e.g., circuit analysis, digital logic circuits). D. Applies principles of fluid mechanics (e.g., Pascal’s law, Bernoulli’s law) to solve problems in fluid flow. E. Understands the applications of thermodynamics (e.g., heat transfer, energy conversions, efficiency) to engineering systems. F. Understands terminology and concepts related to control systems (e.g., input, output, feedback). G. Understands and applies the concepts of sketching and skills associated with computer- aided drafting and design. H. Applies mathematical principles of pneumatic pressure and flow to model and solve problems. I. Applies mathematical principles of manufacturing processes in lathe operations and computer numerical control mill programming to model and solve problems. J. Applies mathematical principles of material engineering to model and solve problems. K. Applies mathematical principles for mechanical drives to model and solve problems. L. Applies mathematical principles of quality assurance (e.g., using precision measurement tools) to model and solve problems. M. Applies mathematical principles of robotics and computer programming of robotic mechanisms to model and solve problems. The framework does not explain the process used to select the specific concepts. As is the case more generally, this list is likely the result of a normative analysis of the relevant content to be taught, not a list of aspects of teacher knowledge that have been found to empirically correlate with high-quality engineering teaching or student learning. To a considerable degree, this list of science and mathematics concepts accords with the major course-content buckets of traditional postsecondary engineering programs: statics, dynamics, fluids, thermodynamics, and circuits. This is not surprising, since many of the reference documents cited in the framework appear to be course textbooks. Whether this is the most appropriate selection of such ideas for prospective secondary teachers of engineering, the committee cannot say, given the lack of empirical evidence. That said, the list offers a hypothesis about requisite teacher knowledge that could be tested in future research. Pedagogical Content Knowledge for K–12 Engineering 3 https://www.tx.nesinc.com/content/docs/274PrepManual.pdf, page 36. 107

PREPUBLICATION COPY, UNCORRECTED PROOFS In addition to content knowledge of the subject they are teaching and general understanding of pedagogical methods, teachers need pedagogical content knowledge (PCK), which involves subject-specific aspects of student learning, curriculum, and the most effective ways to teach about particular subject-matter ideas. PCK has been described as “the blending of content and pedagogy into an understanding of how particular topics, problems, or issues are organized, represented, and adapted to the diverse interests and abilities of learners, and presented for instruction” (Shulman 1987, p. 8). The concept has gained considerable traction in research on K–12 science and mathematics teaching and teacher development, as well as evolved over time as research and practice point to strengths and weaknesses in both the concept and its operationalization in practice and research (e.g., Gess-Newsome and Carlson 2013). A three-part definition of PCK based on both logical analysis and empirical assessments of teacher knowledge (Ball et al. 2008) can be adapted to engineering to yield three PCK domains:  knowledge of how students think about, experience, and understand engineering;  knowledge of engineering curricula; and  knowledge of instructional strategies that are particularly powerful in teaching engineering. All three domains are important, and we now consider research that touches on one or more of them. Sun and Strobel (2014) conducted observations and interviews with elementary teachers who participated in a weeklong PD summer institute using the Engineering is Elementary (EiE) curriculum. The researchers found that teachers uncovered numerous student misconceptions about engineering and technology, a finding well documented by other researchers (e.g., Cunningham 2008) and very important to the development of PCK. Participating teachers also learned that many students lacked teamwork abilities, which, although important in many school settings, is a particularly important element of the engineering design process. They also confronted problems with assessing their students’ engineering work and learning. The teachers tried several classroom techniques to manage both teaching engineering and assessing student outcomes, and in the course of trying different strategies developed engineering PCK. Sun and Strobel suggest that teachers who learn engineering content in professional learning situations need the experience of teaching in real-world settings to enable their PCK development. Further research would inform the development of the specifics of what engineering PCK might include. Another potential resource for conceptualizing PCK is Crismond and Adams’ (2012) “informed design teaching and learning matrix” (p. 741). The matrix (table 5-4) is a use-inspired framework (Turns et al. 2006) that aims to describe the PCK needed to teach with design tasks. It was developed using a scholarship-of-integration approach, a synthesis of literature on design- based learning and performances across a range of contexts. The authors describe eight design strategies (table 5-4, column 1) and associated behaviors of beginning and informed designers (columns 2 and 3), and link these descriptions to both learning objectives and teaching behaviors (last two columns). The few developmental research studies in engineering design did not enable the authors to describe the performances at different grade levels, which would have enhanced the matrix’s utility. The matrix has not been tested empirically as a tool for teacher professional development. TABLE 5-4 The Informed Design Teaching and Learning Matrix 108

PREPUBLICATION COPY, UNCORRECTED PROOFS Design Beginning vs. Informed Designers Learning goals Teaching strategies Strategies Beginning Informed where students… where students… designers… designers… Understand Pattern A. Problem Solving vs. Define criteria and State criteria and the Challenge Problem Framing constraints of constraints from design Treat design task as Delay making challenge. Delay brief in one’s own a well-defined, design decisions in decisions until words. Describe how straightforward order to explore, critical elements of preferred design solution problem that they comprehend and challenge are should function and prematurely frame the problem grasped. behave. Reframe attempt to solve. better. understanding of problem based on investigating solutions. Build Pattern B. Skipping vs. Enhance background Do info searches and Knowledge Doing Research knowledge, and build read case studies. Write Skip doing research Do investigations understandings of product history report. and instead pose or and research to users, mechanisms Do studies and research build solutions learn about the and systems. on users. Reverse immediately. problem, how the engineer existing system works, products. Conduct relevant cases, and product dissections. prior solutions. Generate Pattern C. Idea Scarcity vs. Generate range of Do brainstorming and Ideas Idea Fluency design ideas to avoid related techniques to Work with few or Practice idea fixation. Know achieve idea fluency. just one idea, fluency in order to guidelines and Relax real-world which they can get work with lots of reasons for various constraints or alter fixated or stuck on, ideas by doing divergent thinking original task to see it in and may not want divergent thinking, approaches. new ways. Do generative to change or brainstorming, etc. database searches. discard. Represent Pattern D. Surface vs. Explore and “Mess about” with given Ideas Deep Drawing & Modeling investigate different models. Use words, Propose superficial Use multiple design ideas via gestures, artifacts to ideas that do not representations to sketching, modeling scaffold visualizing support deep explore and solutions, and solutions. inquiry of a system, investigate design making simple Do rapid prototyping and that would not ideas and support prototypes. using simple materials or work if built. deeper inquiry into various drawing tools. how system works. Conduct structured review of ideas. Weigh Pattern E. Ignore vs. Balance Consider both the Give explanations for Options and Benefits & Tradeoffs benefits and tradeoffs design choices. Describe 109

PREPUBLICATION COPY, UNCORRECTED PROOFS Make Make design Use words and of all ideas before and portray pros and Decisions decisions without graphics to display making design cons for all design weighing all and weigh both decisions. options under options, or attend benefits and consideration. Articulate only to pros of tradeoffs of all design values and advice favored ideas, and ideas before picking like KISS (Keep It Super cons of lesser a design. Simple) and human- approaches. centered design. Conduct Pattern F. Confounded vs. Valid Run valid “fair test” Create design advice for Experiments Tests & Experiments experiments to learn others and Do few or no tests Conduct valid how proto- types generalizations based on on prototypes, or experiments to behave and to valid tests. Do run confounded learn about optimize their investigate-and-redesign tests by changing materials, key performance. and product comparisons multiple variables design variables tasks. in a single and the system Do tests to optimize experiment. work. performance. Troubleshoot Pattern G. Unfocused vs. Diagnostic Diagnose and Follow troubleshooting Troubleshooting troubleshoot ideas or steps: observe, name, Use an unfocused, Focus attention on prototypes based on explain, and remedy. Do nonanalytical way problematic areas simulations or tests. troubleshooting to view prototypes and subsystems stations/videos. Do during testing and when modeling or cognitive troubleshooting of troubleshooting training in ideas. devices and troubleshooting. proposing ways to fix them. Revise and Pattern H. Haphazard or Linear vs. Manage project Use design storyboards Iterate Managed & Iterative Designing resources and time to record progression of Design in Do design in a well. their work. Give haphazard ways managed way, Use iteration to instruction and where little where ideas are improve ideas based scaffolding for project learning gets done, improved on feedback. Employ management & design or do design steps iteratively via design strategies steps. Encourage taking once in linear feedback, and repeatedly in any risks, learning while order. strategies are used order as needed. iterating, and reflecting multiple times as on how the design needed, in any problem is framed. order. Reflect on Pattern I. Tacit vs. Reflective Periodically reflect Keep design diaries and Process Design Thinking while designing and portfolios. Do tacit designing Practice reflective keep tabs on Compare/contrast with little self- thinking by keeping strategies used. design cases of monitoring while tabs on design Review to check how approaches used by working or strategies and well solutions met different groups. Do reflecting on the thinking while goals. computer-supported process and working and after structured reflections product when done. finished. about design work. 110

PREPUBLICATION COPY, UNCORRECTED PROOFS SOURCE: Crismond and Adams (2012). Adapted with permission. Crismond and colleagues (Crismond 2013; Crismond and Adams 2012; Crismond et al. 2013; Crismond and Peterie 2017) have described activities that teachers can do to increase their design PCK and help their students become informed designers. One example is the area of troubleshooting. Teachers are likely already familiar and experienced with troubleshooting their own technology when it does not work properly (e.g., shutting down programs to see if the phone or computer will improve its performance), but troubleshooting for design involves more specialized knowledge and behaviors. Teachers can develop this PCK during prototype testing by following a procedure of observing the behavior of the prototype, diagnosing and describing unexpected performance, hypothesizing explanations for that behavior, and proposing redesign solutions (Crismond and Peterie 2017). Crismond and Peterie describe a Troubleshooting Portfolio that Peterie, a high school physics and engineering teacher, has used to both help him improve his engineering PCK and help his students develop their own skills. Using the informed design teaching and learning matrix, the Standards for the Preparation and Professional Development of Teachers of Engineering (Farmer et al. 2014), and other resources related to the teaching and learning of engineering, Lomask and colleagues (2018) developed design teaching standards within the dimensions of informed design practices, engineering themes, and classroom instructional practices. The standards, which underwent validity but not reliability testing, describe what teachers using engineering tasks need to know and do in the classroom to provide their students opportunities to learn. For example, in order to address the dimension of informed design practices, teachers should allow students to frame the challenge, do research, generate alternatives, make decisions, prototype, test, iterate on and improve the design, and communicate and reflect on the process. Engineering themes encompass design, models, systems, resources, and human values and the impact on users. Classroom instructional practices incorporate STEM concepts, appropriate lesson plans, academic learning (e.g., literacy, information technology), practical learning (e.g., safe use of tools), team work, and assessments (Lomask et al. 2018). Hynes (2012) also examined how teachers come to understand and teach students about the engineering design process. The study involved six middle school science, mathematics, and computer science teachers who had participated in a 15-hour PD workshop designed to support use of a specific engineering curriculum, the LEGO robotics toolset, and ROBOLAB programming language. The project took place in Massachusetts, which has articulated an eight- step engineering design process for K–12 education (Massachusetts Department of Education 2006), and Hynes rated teachers on their explanations of those eight steps using a locally developed measure. Teachers’ abilities to explain the steps varied from low to high across the eight steps, indicating that teachers were at different stages of understanding the design process. The analyses also revealed that teachers were beginning to develop relevant pedagogical content knowledge, including real-world examples or familiar analogies that they could use to help students understand design concepts like “prototype.” As a small-scale study, the Hynes research is useful in helping us theorize about teachers’ learning needs: even in a well-developed program with a great deal of support, middle school teachers charged with integrating engineering into their curriculum needed more than a summer PD opportunity and a well-developed curriculum. They needed time to experiment, to reflect, and to build a classroom-based knowledge of how to adapt the lessons for their students. They also did not proceed in lock-step fashion but rather were more successful implementing some of 111

PREPUBLICATION COPY, UNCORRECTED PROOFS the materials than others. It seems prudent to presume that all middle and high school teachers, even those who have studied engineering extensively, will face challenges in building the knowledge and skills necessary to integrate engineering in their curricula. This observation, if it holds true for a broader set of teachers, has implications for the infrastructure necessary to support teachers’ learning over time, an issue that we address in chapter 6. The results of these studies resonate with the broader research literature on professional development and teacher education. That literature suggests that teachers benefit by reflecting on both the professional learning experience itself and how to use new information in teaching (e.g., Penuel et al. 2007; Rogers et al. 2007; Thompson and Zeuli 1999). This includes examining student work, engaging in capstone projects that enhance reflection, and having multiple opportunities to experiment in classrooms and reflect on the experience (e,g, Boyd et al. 2009, 2012; Cohen and Hill 2001; Darling-Hammond et al. 2017; Heller et al. 2012; Little 2003; Roth et al. 2011). Teachers may not always have adequate time to develop PCK, however. This was the case in the five high school engineering PD programs documented by Daugherty and Custer (2012). The researchers suggest that this may have been because the programs had started as curriculum development projects, and program leaders viewed professional development as a way to introduce teachers to the curricula. But curricula alone do not ensure that instruction is transformed. Although the educators followed the same hands-on activities they would then use with students, thus engaging in active learning, the low level of reflection and discussion, coupled with limited time devoted to ongoing practice using the materials in their classrooms, did not allow them to think about how best to implement what they were learning in the classroom, and thus they missed an opportunity to build PCK. Knowledge of Diverse Students An important aspect of PCK is understanding and leveraging student perspectives and needs across contexts and grade levels. This is particularly relevant given the diversity of backgrounds and experiences US K–12 students bring to the classroom. This diversity argues for the use of inclusive pedagogies (box 5-4) that can make education more culturally, linguistically, and socially relevant. BOX 5-4 Permission Pending 112

PREPUBLICATION COPY, UNCORRECTED PROOFS Among their potential benefits, inclusive teaching methods may help reduce longstanding achievement gaps between white and African American and Hispanic students, and between low-income students and students of higher income, which have been documented in K–12 engineering (box 5-5). More broadly, inclusion approaches hold the promise of potentially interesting students from all backgrounds in the study of engineering, a field with a poor track record of attracting and retaining women and people of color (table 4-4). At their core, such approaches are “based on the idea that underrepresented students’ cultural and linguistic practices are assets rather than deficits or barriers to the learning process” (Wilson- Lopez 2016, p. 1). For example, Jordan and colleagues (2017), working to create an engineering curriculum for Navajo Nation middle school students, note the “similarities between the Navajo way of life, which is a holistic cycle of thinking, planning, living, and assuring/testing” and the engineering design process. In a specific instance of curriculum design for greater inclusivity, researchers (Kern et al. 2015) at the University of Idaho developed middle school curriculum in which students designed and tested fish weirs, a traditional Native American technology for catching fish whose basic principles are still in use today. As an extension activity, students worked with community members to build a full-scale, functional weir in a local stream. Wilson- Lopez and colleagues (2016) explored engineering-related funds of knowledge among a group of 25 Latino/a middle and high school students as they designed and implemented engineering projects in their communities. According to the researchers, the students gained significant insights into problem definition from aspects of their daily lives, such as work experiences, familiarity with injury-related health issues of family members, and their perspectives as “transnationals” in regular contact with relatives in other countries. BOX 5-5 Achievement Gaps in the National Assessment of Technology and Engineering Literacy (TEL) The share of eighth-grade students performing at or above the proficient level in TEL, a national assessment given to large samples of 8th graders, rose from 43 in 2014 to 47 percent in 2018. According to National Assessment Governing Board, these students demonstrate solid academic performance and competency in challenging subject matter. The percentages of Black students performing at or above proficient was just 18 percent in the 2014 administration; it rose to 24 percent in 2018. Among Hispanic students, 28 and 31 percent tested at this level in 2014 and 2018, respectively. By comparison, 56 percent of both White and Asian students attained this level of achievement in 2014, and in 2018 their scores rose to 59 and 66 percent, respectively. Reflecting the influence of household wealth on academic performance, 25 and 30 percent of students eligible for school lunch programs, an indicator of low income, achieved at or above proficient on TELS in 2014 and 2018, respectively, compared with 60 and 61 percent of students ineligible for assistance in those two years, respectively. SOURCE: Calculations done using the NAEP Data Explorer, https://www.nationsreportcard.gov/ndecore/landing, August 5, 2019. As part of the effort to adopt more inclusive pedagogies, teachers may also need to recognize and overcome some of their own views about who “belongs” in engineering. Research using the 113

PREPUBLICATION COPY, UNCORRECTED PROOFS Engineering Beliefs and Expectation Instruments for Teachers (EEBEI- T) provides insights into how teachers’ think about which students should enroll in engineering classes and which would be most likely to succeed in an engineering career. EEBEI-T asks teachers to respond to survey questions and evaluate a series of fictional student vignettes. EEBEI-T was validated in a study involving 144 high school STEM teachers in an urban city in the Midwestern United States (Nathan et al. 2009). In answering the survey questions, study participants indicated academic performance in mathematics, science, and technology was the most important factor in judging a student’s suitability for future study or a career in engineering. Family background was deemed somewhat important, and socioeconomic status was not a factor. However, in the vignettes, academic performance (engineering course grade and GPA) was unequally applied. It was a major factor for fictional students with a privileged background but much less important for students with low socioeconomic status (SES), suggesting that, despite explicitly ruling out SES as a factor in their decision making in their survey responses, the teachers implicitly used SES status in judging the vignettes. Nathan et al. 2011 documented similar findings in research involving teachers participating in professional development associated with Project Lead The Way. TEACHER LEARNING OPPORTUNITIES We now turn to the second question of this chapter: “What learning opportunities will teachers need in order to teach engineering?” Like research on the professional learning needs of engineering teachers, the research base related to professional learning opportunities for K–12 engineering teachers is limited. This is both because there are very few teacher education programs in engineering (see chapter 4, “Programs for Prospective Teachers”) and because the number of education researchers working in this domain is quite small. Thankfully, there is a fair amount known from research about effective approaches to teacher preparation more generally, including in science and mathematics. Thus, we begin by examining relevant research, best practices, and standards that apply across multiple fields and then turn to the literature on engineering specifically. In keeping with contemporary models of teacher professional learning, we conceptualize teacher learning over the arc of an educator’s career, starting with quality preparation, followed by quality early-career support, and extending to quality professional development (figure 5-1). 114

PREPUBLICATION COPY, UNCORRECTED PROOFS quality teacher professional development quality teacher induction quality teacher preparation FIGURE 5-1 The Arc of Teacher Professional Learning. SOURCE: Wilson (2011). Used with permission. Quality Teacher Preparation US teacher preparation has been the target of much discussion, debate, and experimentation. The committee’s goal is to understand the characteristics of teacher preparation programs associated with producing “well-launched” beginners. A reasonable starting point is the Council for the Accreditation of Educator Preparation (CAEP) standards (box 5-6), which represent a synthesis of evidence (e.g., Cochran-Smith and Zeichner 2005; Darling-Hammond and Bransford 2005; NRC 2010) about effective teacher preparation and serve as high-level guidance to programs engaged in this work. BOX 5-6 Permission Pending All five CAEP standards are important. However, given the nascent state of US K–12 engineering educator preparation, we focus on Standards 1 and 2, which relate most directly to 115

PREPUBLICATION COPY, UNCORRECTED PROOFS development of educator knowledge and skills. A great deal of research has investigated the causal relationship between teacher subject matter knowledge, pedagogical knowledge, and pedagogical content knowledge. Across grade levels and subject areas, it has been difficult to find evidence that teachers with specific levels of content knowledge, PCK, or pedagogical knowledge have students with higher achievement. Problems with accurate measures of teacher content and pedagogical knowledge have plagued the field, and questions remain about whether there are ceiling effects for the amount of content knowledge teachers need. Nonetheless, many studies have demonstrated associations between teachers’ qualifications in their content domains and student achievement. For example, teacher preparation in specific subjects (e.g., earning a mathematics degree before teaching mathematics) correlates positively with student scores in that subject on the National Assessment of Educational Progress (Ingersoll et al. 2014). Similarly, there is general agreement that clinical partnerships between K–12 and postsecondary institutions and high-quality student-teaching experiences are essential to learning to teach. To be effective, these experiences require highly skilled mentors who have learned to support new teachers and who have sufficient time to observe and work with them, as well as systems for providing feedback on the types of instruction that research suggests can increase student learning and engagement (Clift and Brady 2005; Grossman 2010). Preparation of Teachers of Engineering The opportunity to take engineering or engineering-related coursework would seem to be an important element of any program preparing K–12 teachers of engineering. Yet the committee could find no research that explicitly explored the relationship between such course taking and effective teaching of engineering at the K–12 level. Fantz and colleagues (2011) found that newly minted teachers from a program that conferred both an undergraduate engineering degree and a technology education teacher license included more engineering concepts in lesson and assignment planning than current technology teachers who had not studied engineering. But this finding, though encouraging, does not tie teacher preparation to student performance in the way Ingersoll and colleagues (2014) do nor shed light on the impacts of one or multiple engineering courses, rather than an engineering degree, on teacher preparation or effectiveness. We know from Rogers (2012) and Litowitz (2014) that most technology teacher education programs provide very little in the way of engineering content or higher-level mathematics, and the situation in science is similar. Banilower and colleagues (2018) found that just 13 percent of high school science teachers, 10 percent of middle school science teachers, and 3 percent of elementary school teachers had taken at least one engineering course during their undergraduate education. And only 9 percent of middle school and 18 percent of high school math teachers had taken an engineering course. Given these statistics, it is not surprising that prospective teachers of engineering may view the subject as a trial-and-error activity rather than a clearly defined design process (Culver 2012). However, the literature does describe several programs that allow prospective elementary teachers to learn about engineering, including a single course that is required for all majors (e.g., a problem-based engineering course, as described in Brady et al. 2016); a team-taught course that brings together education and engineering students for a design experience (e.g., Littell and Harman 2017); and a concentration of several engineering-related courses that the student chooses from among other elective topics (Rose et al. 2017). Other institutions offer a certificate program, a minor, a bachelor’s degree program, or a combined undergraduate and master’s 116

PREPUBLICATION COPY, UNCORRECTED PROOFS program (O’Brien et al. 2014; Rose et al. 2017). One institution implemented a collaborative project for elementary education majors in a science methods course and biomedical engineering students. The students worked on teams to design and provide afterschool science club, which provided the prospective teachers with both content and perspectives on engineering (Keshwani and Adams 2016; Melander and Adams 2015). As described in chapter 4, the College of New Jersey’s Technology Education and Integrative STEM Education K–5 major includes 60 credits of STEM courses, including a required specialization in engineering/technology, mathematics, biology, chemistry, or physics. St. Catherine’s University expects all elementary education majors to earn a 3-course (engineering, chemistry, biology) STEM certificate and also offers a STEM minor, and the University of St. Thomas has an engineering education minor for prospective K–8 teachers (O’Brien et al. 2014). Another model for building capacity for K–12 teachers of engineering involves collaboration between education and engineering departments and faculty during prospective teachers’ undergraduate programs. North Carolina State University’s bachelor of science in elementary education includes a required course in engineering design methods taught by engineering faculty. Prospective teachers learn to integrate engineering in their elementary teaching activities, specifically connecting to math and science instruction, and graduate with positive attitudes about engineering (DiFrancesca et al. 2014). Hofstra University offers a K–5 STEM education major with four engineering-related courses taught by an engineering professor (O’Brien et al. 2014). The University of St. Thomas offers a course jointly taught between engineering and education faculty that is a required capstone course for both the undergraduate engineering education minor and a graduate certificate in engineering education. The course objectives include demonstrating engineering knowledge and designing an activity that integrates engineering in the topic they teach (Besser and Monson 2014). The University of South Florida offers a capstone course in Contemporary STEM Issues for mathematics and science prospective middle school teachers. The course is taught by a faculty member from engineering with help from faculty from education, engineering graduate students, and individuals working in a local public school district (Thomas et al. 2019). And at Iowa State University, engineering and education faculty offer a Toying with Technology literacy course for elementary and secondary education majors (Genalo et al. 2001). All of these options might serve as important sites for investigating the potential effects of such coursework on prospective teachers’ knowledge and effectiveness. At least one teacher education program, at the University of Maryland Baltimore County, has taken steps to address the lack of diversity in the K–12 STEM teacher workforce. The Sherman STEM Teacher Scholars Program provides a host of supports for prospective STEM teachers who will work in urban and high-needs schools, including a summer bridge program that prepares students for the program; advising, coaching, and mentoring on professional, academic, and personal topics; and fellowships or summer internships in diverse academic settings under the guidance of teacher-mentors (Hrabowski and Sanders 2015). About 40 percent of graduates from the program have been students of color, but is it not clear how many earned degrees in engineering versus other STEM subjects. One NSF-funded program, the Robert Noyce Teacher Scholarship Program4 aims to encourage STEM majors to become K–12 teachers, including teachers of engineering. Because Noyce scholarship graduates are required to teach in school districts defined as high need (i.e., with high turnover rates for teachers, where many teachers teach outside their content area, 4 https://www.nsfnoyce.org/ 117

PREPUBLICATION COPY, UNCORRECTED PROOFS and/or that serve a high proportion of children from families living below the poverty line5), this program has the potential to improve both the preparation and diversity of K–12 teachers of engineering. Some Noyce scholar programs have included partnerships between engineering and education schools (e.g., Villa and Golding 2014) or provided internships with current teachers for engineering and other STEM majors (e.g., Kennedy et al. 2017; Yousuf et al. 2016). Quality Teacher Induction Like many professions, teaching is complex work that requires learning over time to master, and teachers acquire a great deal of the necessary knowledge and skill on the job (e.g., Feiman- Nemser 2001; Gold 1999). Ingersoll and colleagues (2014) found that mathematics and science teachers are more likely to leave teaching after their first year than teachers of other subjects; and across all school subjects, teachers with less pedagogical training and practice teaching were more likely to leave teaching after their first year. In recognition of this, many schools and districts provide some type of formal early-career support, often referred to as “induction.” Induction can take many forms: the assignment of coaches or mentors, orientation sessions, reduced workloads, workshops on particular topics, and meeting times to enable teacher collaboration. Banilower and colleagues (2018) found that over two-thirds of schools across all grades surveyed have formal teacher induction programs, most lasting two or fewer years. Despite the interest in early career support programs, there is a very small research literature documenting the content and character of effective teacher induction. In a systematic review of the literature, Ingersoll and Strong (2011) located 500 research papers that they whittled down to 15 studies with sufficiently rigorous empirical evidence. The preponderance of evidence from these studies indicated that support and assistance for beginning teachers can have positive effects on their commitment, retention, and instructional practices. There was modest evidence that students of teachers who participated in early-career support programs demonstrated higher gains on academic achievement tests. Ingersoll and Strong also found, however, that the strength of the relationship between an induction program and positive effects varied depending on the program’s intensity and robustness. For example, teachers in programs with supports such as mentors in the same content area, common planning time with other teachers in their content area, and regularly scheduled times to collaboratively plan with colleagues were more likely to stay in teaching than those without such supports (Smith and Ingersoll 2004; Strong 2009). Similarly, Rockoff (2008) found that new teachers who worked with mentors based in their school had lower attrition rates than those with mentors from a different school, and teachers who received more hours of mentoring had higher student achievement scores than those with fewer mentoring hours. Glazerman and colleagues (2010) conducted a large-scale study of the impact of comprehensive teacher induction relative to typical early-career support. The research involved randomized experiments in a set of districts that were not already implementing comprehensive induction. Schools were assigned either to (1) a treatment group whose beginning teachers were offered comprehensive teacher induction or (2) a control group whose beginning teachers received the district’s usual induction services. The researchers found no significant effects of comprehensive teacher induction on teacher retention or teachers’ instructional practices. In addition, they documented no significant effects on student achievement in years one and two. In 5 https://www.law.cornell.edu/uscode/text/20/1021 118

PREPUBLICATION COPY, UNCORRECTED PROOFS year three, in districts and grades in which students’ test scores from the current and prior year were available, students of treatment teachers outperformed students of the control teachers. Clearly, research on comprehensive induction programs is inconclusive. Nonetheless, comprehensive induction programs typically include the following components:  formal or informal orientation that reviews school and district policies and procedures;  mentoring that includes regular observations and formative feedback with supports; and  ongoing PD opportunities that may include study groups, professional learning communities, coteaching, collaborative planning, and/or workshops. Induction for Teachers of Engineering The committee found no research on early-career support programs for engineering teachers. This is likely due to the scarcity of teacher preparation programs that graduate teachers equipped to teach engineering and the limited research in the domain of engineering teacher development. A summary of a convocation on the roles of teachers in policymaking for K–12 engineering education included the suggestion that teacher leaders in engineering could design mentoring programs for beginning teachers of engineering (NASEM 2017). This idea is consistent with studies, cited above, showing the value of mentors in teacher induction. The committee found no research on how content knowledge plays out in the development of an early career engineering teacher. Research in other fields suggests that early career teachers’ content and pedagogical content evolves significantly over time (e.g., Adams and Luft 2018; Davis et al. 2006; Nixon et al. 2017). Quality Professional Development Teachers need opportunities to acquire new knowledge, adapt to shifting policies, and hone their craft, even after their entry into the profession. In the past 30 years there have been considerable investments in developing and conducting research on effective professional development. It was beyond the scope of the committee to synthesize all of that research and best practice, so as elsewhere we relied on several syntheses of relevant literature. For example, a National Academies report on science teacher learning (NASEM 2015) discussed a “consensus model of effective professional development” with the following characteristics: • active participation of teachers who engage in the analysis of examples of effective instruction and student work, • a content focus, • coherence and alignment with district policies and practices, • sufficient duration to allow repeated practice and/or reflection on classroom experiences, and • collective participation (e.g., by multiple teachers from one grade, school, or department). The Learning Policy Institute (Darling-Hammond et al. 2017, p. 4) enumerated a similar list of characteristics: • is content focused, • incorporates active learning, 119

PREPUBLICATION COPY, UNCORRECTED PROOFS • supports collaboration, • uses models of effective practice, • provides coaching and expert support, • offers feedback and reflection, and • is of sustained duration. A more recent meta-analysis of nearly 100 studies of K–12 science and mathematics instructional improvement efforts (Lynch et al. 2019) found the following factors most strongly linked to improvements in student outcomes:  The use of professional development along with new curriculum materials,  A focus on improving teachers' content/pedagogical content knowledge, or understanding of how students learn, and  Specific formats, including: o meetings to troubleshoot and discuss classroom implementation of the program; o the provision of summer workshops to begin the professional development learning process; and o same-school collaboration. These views of professional development highlight the importance of active teacher engagement, which can take many forms, including study groups, collaborative group work, and collective engagement in focal tasks. They also emphasize the importance of focusing on specific content and instructional practices that have been demonstrated to be effective. And they acknowledge that teachers learn new content and practices in the contexts of their schools and districts, and what they learn needs to resonate and be aligned with policies and practices in their contexts. Many elements identified in the consensus models align with research findings on adult learning (NASEM 2018; NRC 2000). Several studies in science education offer empirical evidence, using large-scale quasi- experimental research designs, that professional development designed with these principles can improve teacher learning and practice as well as student learning (e.g., Heller et al. 2012; Roth et al. 2011; Taylor et al. 2017; Yoon et al. 2007). This is a relatively small dataset, however, and much of the research informing ideas about quality professional development consists of correlational and small-scale case studies, which often rely heavily on teacher self-report. It is helpful to understand teacher development as not only an individual issue but also a collective one, relying on mechanisms such as teacher professional learning communities and school-wide supports (NASEM 2015). In fact, research on school improvement suggests that teacher quality is dependent on the school communities that teachers work in, principal leadership, and other factors. This argues for professional learning experiences that include programs outside as well as during the school day and programs that aim to build the capacity of teams of teachers (e.g., Donna 2012; Henderson et al. 2010) or even an entire school’s faculty (e.g., Barger et al. 2007), rather than only individual teachers. Engineering-Related Professional Development Most research on professional learning opportunities for K–12 teachers of engineering focuses on PD experiences. This makes sense, since, as noted, the bulk of those who teach engineering to 120

PREPUBLICATION COPY, UNCORRECTED PROOFS K–12 students have not participated in formal teacher preparation programs but have learned about engineering through various PD experiences. To understand the nature of these experiences and their impact on K–12 educators, the committee conducted a thorough literature review, which yielded 155 relevant articles, 28 from peer-reviewed engineering education journals or book chapters and 127 published in conference proceedings. Below we summarize the findings.6 Many of the papers reported on program assessments or evaluations, and it is informative to consider both program characteristics and the different research methods and metrics used to study impact. This kind of analysis can help uncover potentially useful findings as well as reveal gaps and challenges in the research. Program Characteristics There was considerable diversity, across a number of dimensions, in the programs described in the literature. For example, educators’ learning experiences varied in length and intensity from a few hours or a single day to a week or more. Some PD workshops were repeated at regular intervals for several months or years, while others were a single experience with little follow-up. Some universities have incorporated engineering education graduate certificates in their curricula to provide professional development to current teachers in addition to teacher preparation (e.g., Besser and Monson 2014; Neebel 2015). The teachers who attended these programs tended to be engineering, mathematics, science, or technology teachers, although some programs also recruited school counselors (e.g., Gehrig et al. 2009; Grauer et al. 2013; Inman et al. 2003; Ohland et al. 1996; Rathod and Gipson 1999) or English and social studies teachers (e.g., High et al. 2009; Hunter et al. 2006). The programs were geographically dispersed across the United States and served small and large groups of educators. The smallest included fewer than five participants, the largest more than 2,000. All grade bands were represented, with some programs serving educators from all grades, just elementary and middle school, or just middle and high school educators. Several programs focused exclusively on elementary, middle, or high school educators. Although fewer than half of the papers included information about the programs’ funding, federal agencies such as NASA (Alemdar and Docal 2011; Alemdar and Rosen 2011; Baguio et al. 2014) and NSF funded many of them.7 Specific NSF programs supporting K–12 engineering professional development included the Graduate Teaching Fellows in K–12 Education (GK–12), which provided fellowships to allow STEM graduate and undergraduate students to visit K–12 schools8 (Al Salami et al. 2017; Caicedo et al. 2006); the Math and Science Partnership (MSP) Program, which provided funds for research and development of programs to improve 6 Two literature searches were conducted: (1) in February 2016 of the databases ERIC (Ovid), IEEE, ProQuest Research Library, Scopus, and Web of Science; and (2) in August 2017 of the American Society for Engineering Education’s conference paper database. Both searched as far back as 1998 and used terms such as “engineering education,” “engineering in early education,” “engineering teachers,” “K-12 teachers,” and “professional development.” 7 A small number of these programs were funded by companies (e.g., Henderson et al. 2010; Rockland et al. 2013) or state agencies (e.g., Grauer et al. 2013; Pelletier et al. 2006; Schreiner and Burns 2001). 8 Although the program is no longer active, a description from an earlier solicitation is available at https://www.nsf.gov/pubs/2003/nsf03532/nsf03532.htm. 121

PREPUBLICATION COPY, UNCORRECTED PROOFS achievement of all students9 (e.g., Burghardt and Llewellyn 2006; Burrows and Borowczak 2017; Krause et al. 2008); and the Research Experiences for Teachers (RET) in Engineering and Computer Science,10 which provides funding to university research labs to host K–12 teachers for a 4-to-6-week summer experience on campus (e.g., Autenrieth et al. 2014; Laffey et al. 2013; Nichol et al. 2017; Yelamarthi et al. 2017). The RET program specifically encourages projects that include teachers from high-need schools and individuals from populations underrepresented in STEM and promotes the inclusion of both K–12 teachers and university students (graduate and undergraduate) in these research experiences. For example, one program developed teams consisting of a tenured engineering or computer science professor, a middle or high school STEM teacher, a STEM faculty member at a community college, an undergraduate STEM- focused teacher candidate, and two undergraduate engineering students. Each team spent six weeks conducting research, participating in professional learning activities, and developing an engineering lesson plan to submit to the TeachEngineering website.11 Participating team members indicated more teaching engineering self-efficacy as well as better knowledge of engineering careers after their RET experience (Lavelle et al. 2019). Evaluations of NSF-funded programs show some promising results. For example, high school teachers who attended a one-week professional learning experience and then interacted with GK–12 graduate teaching fellows in science and engineering showed improved attitudes toward interdisciplinary teaching and teaching satisfaction, although middle school teachers in the same program did not show the same improvements (Al Salami et al. 2017). Another GK–12 program paired graduate engineering students with current teachers for a school year and also invited other teachers for a short summer institute taught by the fellows. A follow-up survey indicated that teachers increased their knowledge of engineering content and had greater understanding of what engineers do; many also reported incorporating engineering in their classrooms (Caicedo et al. 2006). One MSP program encouraged professional learning communities for STEM teachers in schools following a summer experience in which they team- taught an interdisciplinary unit and learned about assessing both student knowledge and application of that knowledge (Burghardt and Llewellyn 2006). Another MSP program found that participating teachers improved their attitudes toward interdisciplinary teaching and began to develop labs to demonstrate principles (Krause et al. 2008). RET program evaluations have also shown (often using locally developed measures) that participants increased their confidence and self-efficacy to teach engineering (Ghalia and Huq 2014; Nichol et al. 2017; Ragusa et al. 2014; Trenor et al. 2006), developed greater understanding of engineering (Autenrieth et al. 2014; Barrett and Usselman 2006; Conrad et al. 2007; Georgieva et al. 2013; Kapila 2010), and implemented engineering activities in their classrooms (Barrett and Usselman 2006; Kukreti et al. 2006; Laffey et al. 2013; Trenor et al. 2006). Although the RET program encourages the inclusion of teachers from high-need schools and individuals from populations underrepresented in STEM, most of the published evaluations do not specify that information about the participating teachers. When such information is reported, teachers are in schools with a high proportion of low-income students (e.g., Autenrieth et al. 2014; Nichol et al. 2017) or in urban settings (e.g., Kapila 2010; Ragusa et al. 2014). 9 MSP is described at an archived solicitation (https://www.nsf.gov/pubs/2003/nsf03605/nsf03605.htm). A new version of the program includes STEM and computing (https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505006). 10 https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505170 11 https://www.teachengineering.org/ 122

PREPUBLICATION COPY, UNCORRECTED PROOFS Research Methods and Metrics Evaluations of these programs took many forms. Although some were conducted by an external evaluator, in many cases it was either unclear who evaluated the program or clear that the director or other program staff performed the evaluation. Most assessments collected descriptive- level data [although some used existing validated scales, such as the Systematic Characterization of Inquiry Instruction in Early LearNing Classroom Environments (SCIIENCE; Molitor et al. 2014) or the Teaching Engineering Self-Efficacy Scale (TESS; Yoon et al. 2014)]; collected both pre- and postdata (e.g., Schnittka et al. 2014); or triangulated information from several sources (e.g., Wang et al. 2011a). Almost half of the evaluations used a mixed-methods design, collecting both qualitative and quantitative data, although most of the data were qualitative. A small number of evaluations compared outcomes between those attending the professional learning experience and a similar group of educators who did not attend (e.g., Rich et al. 2017). Qualitative data collected included observations of classroom teaching behavior (e.g., using the Reformed Teaching Observation Protocol; Singer et al. 2016), written reflections, open- ended survey responses, interviews, analysis of performance on specific tasks, and examination of artifacts such as lesson plans (e.g., Guzey et al. 2014; Wang et al. 2011a), syllabi, or presentations. Quantitative data included validated scales, concept inventories, and surveys. Qualitative measures are more common among these projects perhaps because engineering education is relatively new and there are fewer standardized measures, with respect to both surveys and observations of instruction available. This makes it more difficult for programs to document change with commonly used, validated measures of teacher attitude, knowledge, or practice. Program evaluations measured many different variables, including educators’ attitudes, behaviors, and knowledge of engineering or of the program they participated in, or student outcomes (e.g., Ragusa 2011). Most metrics relied on participants’ self-report (e.g., Henderson et al. 2010), although some evaluations used more objective measures (e.g., concept inventories, classroom observation protocols). Student learning gains were measured with standardized or other content tests (e.g., Macalalag et al. 2010), including for science literacy (Ragusa 2011). Other student outcomes, such as engagement or higher-order skills (e.g., collaboration, communication), relied mostly on reports from the teachers or observations from the providers of the professional learning experience (e.g., Hunter et al. 2010). A few evaluations noted cultural shifts within schools, such as teachers being more open to new ideas and a significantly increased level of collaboration (e.g., Nadelson and Callahan 2014). Some articles described the formation and sustainability of professional learning communities following the initial experience (e.g., Guzey et al. 2014; Hardré et al. 2013); others described observed or self-reported changes in teaching practices to use more student-centered pedagogies and engineering activities (e.g., Guzey et al. 2014; Kukreti et al. 2015). Several of the evaluations claimed that teachers had (a) improved understanding of engineering, based on either self-report (e.g., LeMire 2015) or a concept inventory test (e.g., Henderson et al. 2010), (b) improved understanding of the engineering research process and how engineering design connects to math and science (e.g., Nadelson et al. 2012), (c) increased engineering skills (e.g., Martin et al. 2015), and (d) increased engineering pedagogical content knowledge (self-assessed; e.g., Head and Hynes 2011; Webb 2015). 123

PREPUBLICATION COPY, UNCORRECTED PROOFS Although a few examined outcomes for students (e.g., Hunter et al. 2010; Macalalag et al. 2010; Ragusa 2011) or schools, the most commonly measured outcomes for participating educators related to increasing their own engineering literacy with the expectation that teachers could then develop it in their students. However, some programs aimed to promote literacy about engineering careers (Brophy and Mann 2008; Gehrig et al. 2009; Grauer et al. 2013) or encourage STEM integration (e.g., Al Salami et al. 2017; Wang et al. 2011a) and college and career readiness (e.g., Bowen 2016; Crawford et al. 2012; Nadelson et al. 2014; Steimle et al. 2016). Self-Efficacy and the Growth of Educator Expertise Because attitudes, beliefs, and self-efficacy affect teaching behavior (Shulman 1986), and because aspects of self-efficacy are discipline-specific (Yoon et al. 2014), many engineering professional learning programs explicitly assess changes in those areas. Teachers’ relative lack of knowledge and understanding of engineering (e.g., Cunningham et al. 2006), especially compared to math or science, can lead to negative attitudes toward engineering as well as a lack of confidence in, or even fear of, teaching engineering (Culver 2012; Lachapelle and Cunningham 2014). This fear can be overcome, however (box 5-7). BOX 5-7 Overcoming Teachers’ Fear of Engineering After I led one of my first professional development sessions for elementary educators, a 3rd-grade teacher approached me to confess that she had almost skipped the workshop. She had not been able to sleep the previous night as she was trying to envision how she could possibly teach engineering to her students. “If science is scary, engineering is terrifying,” she said. She had no idea what engineering might look like with young children and she had no background in the discipline itself. This was not the first time someone had shared these fears; I witnessed this initial trepidation often. However, the teacher did assert that she was glad she came to the workshop, despite her anxiety: “Now that I understand what engineering looks like for children, I see how it can work in my classroom and how engineering will benefit my students. I can do this. They can do this!” One barrier that many teachers face to including engineering in their classrooms is their fear of teaching a new subject. Many teachers have never taken a course in engineering and because the K–12 classes they attended did not include engineering ideas or activities they have no models to reference. Understandably, the idea of introducing this unfamiliar discipline to a classroom full of students can be fear-provoking and intimidating, especially for a discipline like engineering which evokes stereotypical perceptions of super-rigorous, highly quantitative study. How can such fear be overcome? Introducing educators to engineering activities can help them to visualize what age-appropriate engineering looks like. Engineering with six-year-olds is not the same as engineering with college students—appropriate activities consider central tenets of engineering but modify these to take into account the physical, cognitive, social, emotional, and language capabilities of students. High- quality professional development sessions and K–12 engineering curricula can demonstrate how engineering ideas might be translated for students of various ages. Participating in engineering activities as their students will provides a safe space for teachers to build their own knowledge of engineering. De-briefing the activities through the lens of the student learner and then through the 124

PREPUBLICATION COPY, UNCORRECTED PROOFS lens of a teacher helps educators to think about various facets and learning objectives of the engineering lessons and to develop comfort with the hands-on activities and facilitation strategies. Teachers tell me that access to, or interaction with, other colleagues can help mitigate fears related to engineering. Hearing about engineering experiences, challenges, pathways, and suggestions from more experienced peers can be comforting, motivating, and inspirational. Time to connect with supportive colleagues to plan or debrief engineering lessons is helpful. The opportunity to think through potential stumbling points they might encounter related to engineering and to brainstorm implementation strategies help teachers feel more prepared. Access to other teachers’ expertise does not have to occur face-to-face or even in real time: classroom videos that capture the engineering lessons being enacted with teachers in real classrooms provide opportunities to see and study how others professionals shape their lessons, guide their students, and prompt teams or individuals to work through challenging situations. Teachers appreciate models of pedagogical strategies that work with students. Testimonials about their experiences with engineering from educators who work with similar populations of students can also bolster beginning teachers’ courage to try this new discipline with their pupils. Finally, teachers tell me that their students’ responses to engineering activities propel them to work through the initial rough spots to hone their engineering instruction. They find that students are often more engaged in engineering activities than other school activities. Students, oftentimes those who have not been motivated by other school activities, are highly engaged by engineering challenges and demonstrate creativity and leadership. Engineering challenges can inspire underperforming or hard-to-reach students. This sort of student reaction, along with their excited pleas, “Can we do engineering today?” convinces hesitant teachers that their initial forays into engineering are reaching their pupils and encourages them to grow their knowledge of engineering and their repertoire of pedagogical strategies. SOURCE: This vignette was written by Christine Cunningham, Pennsylvania State University, founder of the Engineering is Elementary curriculum. Elements of the vignette were taken from Engineering in Elementary STEM Classrooms (Cunningham 2018). Printed with permission. Perceptions of engineers and engineering work, whether accurate or inaccurate, can affect the likelihood that teachers will implement engineering activities in the classroom (Yasar et al. 2006). Teachers and future teachers may also lack confidence in both their STEM content knowledge and their ability to teach engineering (Culver 2012). The self-efficacy of many science teachers to teach about engineering is quite low (box 5-8). BOX 5-8 Science Teachers Self-Efficacy to Teach Engineering In a national survey, Banilower and colleagues (2018) asked middle and high school science teachers how prepared they felt to teach three concepts in engineering: defining engineering problems, developing possible solutions, and optimizing a design solution. Fewer than 15 percent of teachers at either level felt very well prepared, while more than a quarter said they were not adequately prepared. In general, middle school teachers felt more prepared than high school teachers. Although Banilower and colleagues (2018) did not ask elementary teachers to indicate how prepared they felt to teach specific engineering concepts, when asked how prepared they felt to teach engineering, over half (51 percent) said they were not adequately prepared and only 3 percent said they felt “very well prepared.” Another 33 percent felt somewhat prepared and 14 percent felt fairly well prepared. 125

PREPUBLICATION COPY, UNCORRECTED PROOFS Most results reported by PD programs described improvements in attitudes, positive changes in behavior, and/or increases in knowledge. For example, many programs found more positive attitudes and beliefs about engineering, including the importance of connecting it to topics in science and math classes (e.g., Al Salami et al. 2017). Others noted that teachers had increased confidence (e.g., Curtis et al. 2016; Henderson et al. 2010; Sargianis et al. 2012) and decreased anxiety about teaching engineering in their classrooms. Teaching self-efficacy, assessed through self-report but also with validated scales (e.g., box 5-9), also improved following some programs (e.g., Head and Hynes 2011; Wang et al. 2011b; Webb 2015). BOX 5-9 Measuring Self-Efficacy Although not widely cited in the literature, two scales for measuring teaching engineering self- efficacy (TESS; Yoon et al. 2014) and engineering design self-efficacy (Carberry et al. 2010) have been designed. The TESS consists of 23 total questions in four subscales that measure self-efficacy for engineering pedagogical content knowledge, outcome expectancy, engagement, and disciplinary (i.e., managing student behavior). Yoon and colleagues (2014) examined the content and face validity of the TESS using structural equation modeling and item analyses. The engineering design scale consists of 36 questions that ascertain motivation and anxiety about performing engineering design activities as well as self-efficacy and outcome expectations individuals have about engineering design. Carberry and colleagues (2010) gathered evidence to show content, criterion, and construct validity of the instrument. Elementary teachers who participated in a year-long program that included 45 minutes of professional learning each week on computing and engineering in K–12 education increased their self-efficacy to teach these subjects compared to teachers from a similar school who did not participate, although both groups of teachers had similar self-efficacy for teaching math and science. Because one source of self-efficacy is a mastery experience (e.g., Bandura 1997), the teachers who implemented an engineering activity in their classroom and notice positive results increased their self-efficacy for teaching engineering even when the activities they implemented were simple (Rich et al. 2017). Lee and Strobel (2014), using a Concern-Based Adoption Model (Anderson 1997), examined teachers’ anxieties about and use of K–12 engineering before and after attending a PD program and found that they evolved during the program. Before the program, teachers were primarily focused on learning about engineering education, its demands on their teaching and time, the logistics of implementing engineering, and student outcomes. After participation, many of those worries had lessened, but teachers still had questions about impacts on students and wondered how to work with others in their school to implement engineering and how to determine its benefits for the school, teachers, and students. That is, as teachers acquired more information, their concerns changed from a personal focus (e.g., learning about engineering and what they need to teach it) to a focus on others (e.g., impact on student outcomes and how teachers could work together to best teach engineering), suggesting a need for continuing support as teachers implement engineering (Lee and Strobel 2014). Teacher leaders in K–12 engineering may be an important source of support for less-experienced educators (e.g., NASEM 2017, pp. 12–14). A small body of research has documented the challenges associated with preparing teachers to teach engineering. Using data collected from interviews and survey responses from 73 126

PREPUBLICATION COPY, UNCORRECTED PROOFS elementary teachers who participated in a week-long engineering PD experience, Sun and Strobel (2013) developed a model of adoption of engineering education that is directly related to how practical and sustainable teachers think the engineering instructional goals and materials will be. The researchers also note that as teachers’ confidence in and comfort with teaching engineering increase, the likelihood that they will implement engineering in their classroom also increases. A third factor influencing adoption is whether teachers believe that students benefit from learning engineering and if so how. Teachers who think of simple and limited benefits like knowing terms or having fun are less likely to teach engineering than those who appreciate that students will develop problem-solving and critical-thinking skills in addition to becoming familiar with engineering as a field of study or a career. Finally, the approach to incorporating engineering in the classroom affects implementation; teachers who view an engineering activity or lesson as isolated from their other teaching are less likely to adopt than those who purposefully connect engineering to other topics they teach. Similarly, three factors are related to the development of expertise in elementary engineering education. Teachers with a low level of expertise tended to present engineering lessons or concepts exactly as they learned them in their PD experiences without relating them to the context of their own classroom or their students’ lives. On the other hand, with greater expertise, teachers adapt lessons and activities to real-world contexts that students understand and relate to. Second, as teachers acquired engineering PCK, they increased their expertise, began to overcome problems such as student frustration with the engineering design process or group work, and eventually created lessons that provide active learning experiences for the students. Finally, teachers began to connect engineering to their teaching in other disciplines as their expertise grew (Sun and Strobel 2013). Diefes-Dux (2014) proposes a four-stage model for the implementation of elementary engineering education, beginning with PD experiences that help educators overcome unfamiliarity with and fear of engineering. However, even with increased comfort with and excitement about engineering, the first year of implementing engineering activities in the classroom often runs into barriers such as time constraints for preparing and incorporating lessons in the classroom, lack of awareness of and support for engineering education from colleagues and administrators, and beliefs about student learning. Thus, initial implementation of engineering activities is disconnected from the rest of the curriculum and does not connect students to broader knowledge of engineering. After that first-year experience, teachers may seek more PD opportunities in order to better connect engineering to other subjects and learn more about engineers and engineering. Finally, if they have support from the education system, including peers and administrators, teachers’ second-year engineering implementation better integrates with other subjects and promotes student learning. (Chapter 6 considers more fully the importance of systems of support for teacher professional learning.) Potentially Effective Practices Several professional learning experiences described in the literature include some features described earlier (Darling-Hammond et al. 2017; NASEM 2015) that are associated with high- quality professional development and so may deserve to be considered as potentially effective practices for building educator capacity in K–12 engineering education. Curriculum design-based professional development can provide educators with both engineering content knowledge and an active learning experience. One program using this 127

PREPUBLICATION COPY, UNCORRECTED PROOFS approach brought together teachers for six months to create and get feedback on student activities, lesson plans, and assessments. Participating teachers believed that the program increased their engineering knowledge (measured retrospectively), improved their self-efficacy for engineering curriculum design (measured three times with a scale), and produced curricula that addressed standards and integrated knowledge from engineering and other disciplines (Berry 2017; Berry and DeRosa 2015). An NSF-funded program at the University of Cincinnati provided professional development of sustained duration to middle and high school teachers so they could teach engineering to their students, with the goal of both improving student performance in science and mathematics and increasing student awareness of STEM majors. Teachers spent seven weeks during two consecutive summers learning foundational engineering and design principles, as well as applications of engineering to math and science topics. Some of the professional learning courses were taught by university engineering faculty, others by high school teachers experienced in K– 12 engineering education. Program evaluations showed that while all courses improved the teachers’ self-report of knowledge and skills related to engineering, high school teachers with more experience in and knowledge of how the K–12 educational system works were viewed as more effective instructors (Rutz et al. 2015). Professional development that brings together teachers from mathematics, science, and technology to form learning communities can support efforts to teach engineering in an integrated fashion. Donna (2012) documents a program in which interdisciplinary teams complete an engineering design activity intended to promote both content and pedagogical knowledge. Team members discuss how the activity connects engineering to concepts in mathematics, science, or technology, and they consider how it could be used as a pedagogical tool with students in other STEM classes. Many engineering PD experiences are of relatively short duration, so an online community of practice can support teachers as they implement what they learned. Although teachers cite lack of time as a barrier to participating in such a community, access to teaching and learning resources (Forbes et al. 2017) and the ability to hold discussions and receive feedback from peers help them as they begin to teach engineering (Liu et al. 2012). At least two engineering-focused online communities provide resources and other supports for K–12 educators: the LinkEngineering Educator Exchange (linkengineering.org), a project of the National Academy of Engineering, and TeachEngineering (teachengineering.org), overseen by a coalition of postsecondary institutions. Although together the two sites provide hundreds of resources and are visited by thousands of teachers each month, neither has been empirically evaluated for its effect on teachers’ knowledge of and confidence to teach engineering. Encouraging Culturally Responsive Teaching As noted earlier in the chapter (box 5-4), culturally responsive teaching is important for all educators and especially for those engaged in introducing students to engineering. The committee could find only one example from the literature addressing this important challenge. The program infused technology and engineering concepts in science and mathematics professional development for teachers working in American Indian schools in Utah. A key component was the creation of advisory groups of Native community members to help develop and provide culturally relevant professional learning experiences for the teachers (Becker et al. 2009). Teachers were exposed to the idea that traditional educational experiences are based in 128

PREPUBLICATION COPY, UNCORRECTED PROOFS the community of the students and often involve children and their parents as well as elders and other community members. CONCLUSION The committee found no definitive, empirically tested answer to the question of what engineering knowledge and practices K–12 teachers of engineering need. Sources we examined, such as the standards by Farmer and colleagues (2014), suggest that researchers and practitioners have made initial progress delineating important but general areas for the preparation of these educators. Far less progress has been made investigating how the knowledge base differs for teachers of different grades, how knowledge builds on itself over time (progression), what specific preparation in science and mathematics teachers of engineering should have (and how this preparation might vary according to grade and primary subject taught), how this preparation might differ from that needed by technology teachers, or how to test the preliminary conceptions of teacher knowledge empirically. It is notable that the bulk of research reviewed by the committee related to both the preparation of K–12 teachers of engineering and PD for these educators is focused at the elementary level. This may in part reflect the fact that, unlike most secondary educators, elementary teachers are responsible for teaching multiple subjects, often including science. Thus in some ways elementary classrooms may be better suited to the introduction and study of more integrative approaches to teaching. Research on teaching in general and on teaching in specific subjects, such as science, strongly suggests that pedagogical content knowledge is important to teacher effectiveness, and there is every reason to believe the same is true for teachers of engineering. However, there is scant information in the literature about the potential landscape of engineering teachers’ PCK. What few clues have been unearthed, related to engineering design, for example, do not appear to have been tested empirically to determine their validity. Knowledge of and skill in teaching diverse students through the use of more inclusive pedagogies seem to be essential elements of the professional knowledge base for teachers of engineering, whether the goal is general engineering literacy or more advanced understanding and skill in the domain. The committee also found no empirically tested answer to the question of what learning opportunities K–12 teachers of engineering will need. Research on quality teacher preparation, induction, and professional development in other subject areas suggests that these learning experiences improve teachers’ subject matter knowledge and PCK and correlate with student performance; it is reasonable to assume that engineering learning experiences would lead to similar improvements. The committee’s review of the literature describing engineering-specific teacher learning experiences uncovered some evidence that such professional learning can lead to improvements in teachers’ self-efficacy to teach engineering, attitudes toward engineering, and knowledge of the engineering design process and concepts. However, there is little research connecting those learning experiences to classroom teaching behavior or student outcomes. The growing number of programs of teacher preparation and PD experiences for K–12 teachers of engineering suggests that there are many opportunities for important research to be conceptualized and conducted. REFERENCES 129

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Engineering education is emerging as an important component of US K-12 education. Across the country, students in classrooms and after- and out-of-school programs are participating in hands-on, problem-focused learning activities using the engineering design process. These experiences can be engaging; support learning in other areas, such as science and mathematics; and provide a window into the important role of engineering in society. As the landscape of K-12 engineering education continues to grow and evolve, educators, administrators, and policy makers should consider the capacity of the US education system to meet current and anticipated needs for K-12 teachers of engineering.

Building Capacity for Teaching Engineering in K-12 Education reviews existing curricula and programs as well as related research to understand current and anticipated future needs for engineering-literate K-12 educators in the United States and determine how these needs might be addressed. Key topics in this report include the preparation of K-12 engineering educators, professional pathways for K-12 engineering educators, and the role of higher education in preparing engineering educators. This report proposes steps that stakeholders - including professional development providers, postsecondary preservice education programs, postsecondary engineering and engineering technology programs, formal and informal educator credentialing organizations, and the education and learning sciences research communities - might take to increase the number, skill level, and confidence of K-12 teachers of engineering in the United States.

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