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:
- What are teachers’ learning needs for teaching engineering?
- 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.
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 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.
Sykes and Wilson (2015), in their review of research on teaching, identify two domains of professional knowledge with a number of associated subdomains (table 5-1). Like Danielson, this framework is subject-matter agnostic.
The Interstate Teacher Assessment and Support Consortium (InTASC) core teaching standards and learning progressions offer yet another, similar conceptualization (box 5-2).
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
|Domain I: Instruction||Domain II: Professional Role Responsibilities|
Collaborating with other professionals
Working with families and communities
Fulfilling ethical responsibilities
|Domain I: Instruction||Domain II: Professional Role Responsibilities|
Meeting legal responsibilities
SOURCE: Sykes and Wilson (2015). © 2015 Educational Testing Service. Reprinted by permission of Educational Testing Service, the copyright owner. All other information in this publication is provided by National Academies Press and no endorsement of any kind by Educational Testing Service should be inferred.
work with students, parents, administrators, and colleagues in 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 for Teachers of 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.
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 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 4-3), 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” (Morrell et al. 2019, 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 Preparation and Professional Development for 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.
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 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 expo-
sure 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).
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 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 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 learn 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 explor-
ing 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 has 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).
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
|Core concept of engineering||Subconcepts|
|Statics||Resultants of force systems|
|Equivalent force systems|
|Equilibrium of rigid bodies|
|Dynamics||Kinematics (e.g., particles and rigid bodies)|
|Mass moments of inertia|
|Force acceleration (e.g., particles and rigid bodies)|
|Mechanics of materials||Stress types and transformations|
|Material characteristics, properties, and composition (e.g., heat treating)|
|Electrical power||Motors and generators|
|Transmission and distribution|
SOURCE: Huffman et al. (2018). Reprinted with permission.
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.)
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:
- Applies principles related to statics (e.g., moment, stress, strain) to analyze systems and solve problems.
- Applies principles of dynamics (e.g., force, acceleration, moment of inertia) to model and solve problems.
- Understands terminology (e.g., analog, digital) and concepts related to electric circuits (e.g., circuit analysis, digital logic circuits).
- Applies principles of fluid mechanics (e.g., Pascal’s law, Bernoulli’s law) to solve problems in fluid flow.
- Understands the applications of thermodynamics (e.g., heat transfer, energy conversions, efficiency) to engineering systems.
- Understands terminology and concepts related to control systems (e.g., input, output, feedback).
- Understands and applies the concepts of sketching and skills associated with computer-aided drafting and design.
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 at https://www.tx.nesinc.com/Content/Docs/274PrepManual.pdf.
|XI Engineering Method||Engineering Standard I The beginning engineering teacher possesses a working knowledge of engineering fundamentals.|
|Engineering Standard II The beginning engineering teacher understands the design process and integrates mathematics, science, technology, engineering, and other knowledge to design solutions to engineering problems.|
|Engineering Standard VI The beginning engineering teacher understands and applies knowledge of tools, equipment, technologies, and procedures used in the design and production of systems.|
|XII Engineering Profession||Engineering Standard III The beginning engineering teacher understands the legal and ethical requirements of the engineering profession.|
|Engineering Standard IV The beginning engineering teacher understands the concept of teaming and demonstrates knowledge of careers in engineering and technology and the role of professional and student engineering organizations in career development.|
|Engineering Standard V The beginning engineering teacher understands the societal contexts of engineering and technology.|
|Engineering Standard VII The beginning engineering teacher understands the importance of professional development and knows how students learn and develop engineering skills and concepts and uses this knowledge to plan and implement effective classroom instruction and laboratory experiences to meet curricular goals.|
|Engineering Standard VIII The beginning engineering teacher knows how to provide a safe and productive learning environment for implementing activities in engineering education.|
|Engineering Standard IX The beginning engineering teacher identifies, evaluates, and utilizes new and emerging technologies.|
SOURCE: Copyright © Texas Education Agency, 2018. The materials found on the agency’s website or paid for under a works for hire contract are copyrighted © and trademarked ™ as the property of the Texas Education Agency and may not be reproduced without the express written permission of the Texas Education Agency.
- Applies mathematical principles of pneumatic pressure and flow to model and solve problems.
- Applies mathematical principles of manufacturing processes in lathe operations and computer numerical control mill programming to model and solve problems.
- Applies mathematical principles of material engineering to model and solve problems.
- Applies mathematical principles for mechanical drives to model and solve problems.
- Applies mathematical principles of quality assurance (e.g., using precision measurement tools) to model and solve problems.
- 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
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
|Design strategies||Beginning vs. informed designers||Learning goals where students…||Teaching strategies where students…|
|Beginning designers…||Informed designers…|
|Understand the challenge||Pattern A. Problem solving vs. problem framing||Define criteria and constraints of challenge. Delay decisions until critical elements of challenge are grasped.||State criteria and constraints from design brief in their own words. Describe how preferred design solution should function and behave. Reframe understanding of problem based on investigating solutions.|
|Treat design task as a well-defined, straightforward problem that they prematurely attempt to solve.||Delay making design decisions in order to explore, comprehend, and frame the problem better.|
|Build knowledge||Pattern B. Skipping vs. doing research||Enhance background knowledge, and build understandings of users, mechanisms, and systems.||Do info searches and read case studies. Write product history report. Do studies and research on users. Reverse engineer existing products. Conduct product dissections.|
|Skip doing research and instead pose or build solutions immediately.||Do investigations and research to learn about the problem, how the system works, relevant cases, and prior solutions.|
|Design strategies||Beginning vs. informed designers||Learning goals where students…||Teaching strategies where students…|
|Beginning designers…||Informed designers…|
|Generate ideas||Pattern C. Idea scarcity vs. idea fluency||Generate range of design ideas to avoid fixation. Know guidelines and reasons for various divergent thinking approaches.||Do brainstorming and related techniques to achieve idea fluency. Relax real-world constraints or alter original task to see it in new ways. Do generative database searches.|
|Work with few or just one idea, which they can get fixated or stuck on, and may not want to change or discard.||Practice idea fluency in order to work with lots of ideas by doing divergent thinking, brainstorming, etc.|
|Represent ideas||Pattern D. Surface vs. deep drawing & modeling||Explore and investigate different design ideas via sketching, modeling solutions, and making simple prototypes.||“Mess about” with given models. Use words, gestures, artifacts to scaffold visualizing solutions. Do rapid prototyping using simple materials or various drawing tools. Conduct structured review of ideas.|
|Propose superficial ideas that do not support deep inquiry of a system, and that would not work if built.||Use multiple representations to explore and investigate design ideas and support deeper inquiry into how system works.|
|Design strategies||Beginning vs. informed designers||Learning goals where students…||Teaching strategies where students…|
|Beginning designers…||Informed designers…|
|Weigh options and make decisions||Pattern E. Ignore vs. balance benefits & trade-offs||Consider both the benefits and trade-offs of all ideas before making design decisions.||Give explanations for design choices. Describe and portray pros and cons for all design options under consideration. Articulate design values and advice like KISS (Keep It Super Simple) and human-centered design.|
|Make design decisions without weighing all options, or attend only to pros of favored ideas, and cons of lesser approaches.||Use words and graphics to display and weigh both benefits and trade-offs of all ideas before picking a design.|
|Conduct experiments||Pattern F. Confounded vs. valid tests & experiments||Run valid “fair test” experiments to learn how prototypes behave and to optimize their performance.||Create design advice for others and generalizations based on valid tests. Do investigate- and-redesign and product comparisons tasks. Do tests to optimize performance.|
|Do few or no tests on prototypes, or run confounded tests by changing multiple variables in a single experiment.||Conduct valid experiments to learn about materials, key design variables, and the system work.|
|Design strategies||Beginning vs. informed designers||Learning goals where students…||Teaching strategies where students…|
|Beginning designers…||Informed designers…|
|Troubleshoot||Pattern G. Unfocused vs. diagnostic troubleshooting||Diagnose and troubleshoot ideas or prototypes based on simulations or tests.||Follow troubleshooting steps: observe, name, explain, and remedy. Do troubleshooting stations/videos. Do modeling or cognitive training in troubleshooting.|
|Use an unfocused, nonanalytical way to view prototypes during testing and troubleshooting of ideas.||Focus attention on problematic areas and subsystems when troubleshooting devices and proposing ways to fix them.|
|Revise and iterate||Pattern H. Haphazard or linear vs. managed & iterative designing||Manage project resources and time well. Use iteration to improve ideas based on feedback. Employ design strategies repeatedly in any order as needed.||Use design storyboards to record progression of their work. Give instruction and scaffolding for project management & design steps. Encourage taking risks, learning while iterating, and reflecting on how the design problem is framed.|
|Design in haphazard ways where little learning gets done, or do design steps once in linear order.||Design in a managed way, where ideas are improved iteratively via feedback, and strategies are used multiple times as needed, in any order.|
|Design strategies||Beginning vs. informed designers||Learning goals where students…||Teaching strategies where students…|
|Beginning designers…||Informed designers…|
|Reflect on process||Pattern I. Tacit v design thinking||. reflective||Periodically reflect while designing and keep tabs on strategies used. Review to check how well solutions met goals.||Keep design diaries and portfolios. Compare/contrast design cases of approaches used by different groups. Do computer-supported structured reflections about design work.|
|Do tacit designing with little self-monitoring while working or reflecting on the process and product when done.||Practice reflective thinking by keeping tabs on design strategies and thinking while working and after finished.|
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.
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 Preparation and Professional Development for 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 (MDOE 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 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.
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.
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 Engineering Education Beliefs and Expectations Instrument 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 a city in the Midwestern United States (Nathan
et al. 2009). In answering the survey questions, study participants indicated that 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 it in judging the vignettes. Nathan and colleagues (2011) documented similar findings in research involving teachers participating in professional development associated with Project Lead The Way.
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).
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.
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 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 math-
ematics 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 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 run an 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 requires 60 credits of STEM courses, including a 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 prospective middle school teachers of mathematics and science. 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 Program,4 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, 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. 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.
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 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.
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 of effective PD; it
- is content focused,
- incorporates active learning,
- 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:
- meetings to troubleshoot and discuss classroom implementation of the program,
- the provision of summer workshops to begin the professional development learning process, and
- 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 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.
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 followup. 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
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.”
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 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
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.
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).
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).
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. 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), or (d) increased engineering pedagogical content knowledge (self-assessed; e.g., Head and Hynes 2011; Webb 2015).
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).
Perceptions of engineers and engineering work, whether accurate or inaccurate, can affect the likelihood that teachers will implement engineering activities in the classroom (Yaşar 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).
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).
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 noticed positive results increased their self-efficacy for teaching engineering even when the activities they implemented were simple (Rich et al. 2017).
neering 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 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. Another 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. 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. Third, 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 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 knowl-
edge. 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. Together the two sites provide hundreds of resources and are visited by thousands of teachers each month, although 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, a program infusing 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 the community of the students and often involve children and their parents as well as elders and other community members.
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 the preparation of K–12 teachers of engineering, while 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.
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