The primary motivation for inviting authors to participate in writing this book was the need to include at least one representative of each of the four STEM domains, i.e., science, engineering, technology, and mathematics, in conjuction with each one of the three educational themes comprising the title of the book: cognition, metacognition, and culture. These two dimensions—the domain with its four values and the theme with its three values—gave rise to a matrix with 12 cells, each of which is a chapter in its own right. We ended up with 15 chapters: an introduction and a discussion, two chapters on technology and culture, and two chapters on engineering culture. Chapter 5 concerns both cognition and metacognition in cyberlearning. Table 15.1 presents the chapters according to their domains and the theme dimensions.

Table 15.1 Book chapters according to domain and theme
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The cross product of the four STEM domains and the three themes—cognition, metacognition, and culture—has provided a rich, encompassing framework for this edited book’s authors to express the extensive research and different views on STEM education from a variety of vantage points. The views expressed in the book chapters are indeed quite diverse. Thus, one might claim that the book is not focused enough. Yet, we maintain that the different contexts of the chapters and multiple foci of studies highlight the differences in the various domains of study covered in the book, notably, differences between science education and engineering education. These differences stem from the diversity of cultures, including norms, values, and worldviews, as well as the different approaches to STEM education, which influence how cognition and metacognition are viewed.

For example, what teachers need to know in order to teach science to children (Chap. 2 in this book) is very different from what teachers need to know for teaching engineering design to children (Chap. 8 in this book). Both require complex cognitive and metacognitive processes, but despite having the end goal of educating children, they employ very different ways of thinking and reflecting on the educational practices. These differences are the result of the cultural contexts from which science education and engineering education derive their goals and the differences in the knowledge and skills required to teach science on one hand and engineering design on the other hand.

Teaching engineering design to undergraduate students (Chap. 10 in this book) is another cognitively complex process, which is influenced by the culture of engineering as practiced by professionals. It requires university instructors to have a set of knowledge that is different than the set that classroom teachers teaching engineering design need to have, reflecting the different goals of educating professional engineers rather than school children.

It is also evident that what constitutes literacy as a cognitive and metacognitive activity varies as a function of domains and the cultures that are characteristic of those domains. For example, there are major differences between mathematical literacy, discussed in Chap. 12, and science literacy, which Chap. 4 elaborates on. Thus, very different stances on literacy surface, with Mevarech and Fan (2018, in this book) on one side, while Sjöström and Eilks (2018, in this book), are on the other side. The former authors argue that mathematical literacy is the comprehension and use of mathematics as measured by the PISA assessment, while the latter claim that literacy in science consists of global citizenry.

Culture, as explored by our authors, depends upon grain size. Some authors have chosen to look at country-level influences, while others have looked at specific social influences, domain-specific cultures, and even the cultures associated with levels of schooling. Culture, especially at the national level, influences also the ways European and North American scholars address cognition, metacognition, and culture. However, what all of the authors addressing culture have in common is that culture influences what we think is important to know and be able to do. Culture also influences decisions about pedagogy. In particular, culture can both impede and support the adoption of technologies that have the potential to advance both learning and metacognition, as discussed in Chaps. 6, 7, and 8.

Across the book chapters, the discussion on metacognition has focused on the essence of metacognition and on how it can support teaching and learning. Metacognition in science, engineering, and mathematics education is the focus of Chaps. 3, 9, and 13, respectively. While authors agree on a core set of metacognitive strategies, primarily planning and monitoring, the metacognition they examine is different depending upon who performs the monitoring and the reflecting processes. The authors differentiate, for example, between teachers’ pedagogical metacognition and students’ metacognitive strategies while solving problem. Authors also grapple with the difficulty of fostering and supporting metacognition and determining whether, and to what extent, metacognition is taking place. Determining if metacognition is actually happening is often inferential, as it is measured indirectly by observations such as how well students solve problems. Wengrowicz, Dori, and Dori (Chap. 9 in this book) tackle the task of assessing metacognition by adding a layer of meta-assessment in the realm of pedagogy, making assessment a student-centered activity and meta-assessment as a complementary activity of the course staff, who assesses the individual students’ quality of assessing peers’ team projects.

Given the diversity of views about cognition, metacognition, and culture, this book presents the breadth of perspectives and the richness of research into these STEM domains and themes with their variety of approaches and definitions.

The word clouds in Figs. 15.1 and 15.2 are a graphic, fun way to determine where our authors focused their attention and to demonstrate the diversity of perspectives on cognition, metacognition, and culture under the umbrella of STEM domains.

Fig. 15.1
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Word cloud of the 50 most frequent words in the book

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Fig. 15.2
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Word cloud of the 100 most frequent words in the book

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15.1 Major Book Concepts and Keywords

Figures 15.1 and 15.2 are word clouds of the approximately 117,000 words in the book,Footnote 1 created by software developed by Jason Davis.Footnote 2 These figures represent the 50 and 100 most frequent words in the book, respectively. Figure 15.1 highlights where the authors were focusing their attention by their frequency as indicated by the size of the word. Words that appear with high frequency include students, science, knowledge, engineering, learning, teachers, education, teaching, technology, design, problem, metacognition, metacognitive, mathematics, scientific, research, model, mathematical, solving, understanding, thinking, modeling, problems, cognition, practice, course, skills, research, culture, teacher, assessment, practices, process, instruction, literacy, cognitive, social, processes, information, tools, classroom, and school.

Doubling the number of words in Fig. 15.2 from 50 to 100 allowed some new relevant words to show up. These were STEM, development, studies, inquiry, content, tasks, society, activities, strategies, environment, Bildung, study, approach, and individual.

This collection of words provides a faithful mental image of the major topics dealt within this book. Interestingly, while “students” is the most frequent word, the singular “student” is over four times smaller. Similarly, “teachers,” one of the most frequent words, is twice as frequent as “teacher.” This might be an indication that the authors’ reviews, studies, and discussions in the book tend to generalize for students and teachers as groups of stakeholders, rather than focusing on the individual student and teacher. The words STEM and culture are not as frequent as one might expect from a book on these subjects, but science, engineering, and education do appear amongst the most frequent words followed by technology and mathematics. Indeed, there is tension in the literature between unifying and separating the teaching of all or some of the STEM domains. However, this may be an artifact, because we called for papers that addressed science, technology, engineering, and mathematics as separate domains.

If we combine “metacognition” with “metacognitive,” we get a word count that is about as frequent as science or knowledge, and if we combine “science” with “scientific,” this becomes at least as big as most frequent word, “students.”

While the word cloud examines frequency of single words, many of the keywords that the chapter authors defined are phrases that comprise two or more words. By switching from words that authors actually used to keywords they defined in their respective chapters, we emphasize how cognition, metacognition, and culture relate to the various STEM domains (see Table 15.2).

Table 15.2 Keywords by STEM domain, theme, and chapter
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A more parsimonious way of looking at key words and phrases is to say that our authors are interested in students’ learning and acquiring knowledge and skills in various contexts with support from teachers and technology.

In what follows, we integrate the keywords in Table 15.2 to elicit main ideas and insights by STEM domains and themes. We walk through the major ideas, as indicated by the keywords, using the underlying logic of tracing the path from knowledge to practices, such as nature of science, higher-order thinking, and scientific literacy. We then discuss major constructs of metacognition and the relation of both cognition and metacognition to culture.

15.1.1 Cognition

We start with the first theme, cognition. In this book, authors refer to cognition of students and of teachers as a process of knowing, understanding, and thinking.

They frame knowledge acquisition as the process of building background knowledge and developing competencies for solving increasingly complex problems. Well-defined problems help scaffold knowledge acquisition in classroom contexts, often with focus on acquisition of theoretical scientific concepts. Knowledge application, as viewed by our authors, may include the process of knowledge transfer as students engage in complex design projects or mathematics situations. It requires determining and applying relevant knowledge from the students’ prior knowledge, assuming that these students retain that knowledge from prior studies.

Knowledge production results from the ongoing iteration between knowledge acquisition and application, inducing deeper understanding of the problem context and consequently better design with a variety of features (Chap. 8 in this book).

Teacher cognition is a knowledge base for teaching, which includes formal propositional knowledge, practical knowledge, and beliefs, as discussed in Chap. 2. Cognition is thus an active learner-centered process. It is not supported by traditional educational practices such as lecture- or textbook-based instruction, challenging notions of efficiency and most forms of standardized paper-and-pencil assessments.

Scientific practices, also referred to as inquiry teaching, are consistent with recent education reforms in the United States. They align with how scientists carry out scientific investigations and inquiry. Scientific practices include multiple aspects of scientific work that are important for children to engage in and learn as students in the classrooms. They include human aspects of science, such as the recognition that science is empirically based, creative, and tentative (Chap. 2 in this book).

Scientific inquiry is a term encompassing the various ways in which scientists study the natural world. It involves a process of investigation, framed by asking testable questions and collecting and interpreting data to develop explanations about the natural world (Chap. 2 in this book).

Authentic practices, discussed in Chap. 5, encompass the instruments, strategies, and heuristics of a professional, including how to communicate in a range of technical forms to a variety of audiences, how to work with others in teams, and how to mentor and apprentice others who are less experienced. Engaging in what scientists do as authentic, scientific practice and inquiry have wide-ranging implications for curriculum development, teacher preparation, and assessment. Changes in curriculum development, teacher preparation, and assessment are currently underway, but they will not succeed unless there is a change in what policy makers and the public think of as teaching and learning. Beyond educating students, STEM educators will have to engage in educating the public through persuasive communication. This persuasion includes hard data that engaging in authentic scientific practices and inquiry results in positive academic outcomes for all children, as measured by a variety of assessment tools.

At the core of mathematics literacy are complex, unfamiliar, and nonroutine (CUN) tasks (Chap. 12 in this book). Funds of knowledge, defined in Chap. 14, are bodies of knowledge and skills that are essential for household or individual functioning and well-being and which have culturally developed and historically accumulated. This view of mathematics, advocated by mathematics educators, runs counter to the views of mathematicians who refer to mathematics as a logical closed system, worthy of study in and of itself, with no need to reference or map to the real world. These differences have contributed to the debate over whether STEM fields can be integrated or should remain distinct. In the United States, attempts to integrate mathematics with other areas of science, technology, and engineering in the K-12 curriculum have been met with resistance. The recently developed US Common Core Standards for mathematics present mathematics in a third way, addressing mathematics as both content and mathematics practices. This third way of viewing mathematics is also debated by ‘pure’ mathematicians.

Global citizenship education is, according to UNESCO, education that aims to empower learners to play active roles in facing and resolving global challenges and to facilitate learners’ transition to being proactive contributors to a more peaceful, tolerant, inclusive, and secure world. Closely related to global citizenship education is education for sustainability: education, public awareness, and training that are presumed to be keys for achieving sustainability. In Agenda 21, the UN suggested that there is a need for education for sustainable development and provided a corresponding definition. In recent years, the idea of education for sustainable development is under constant debate, and similar terms like education for sustainability or sustainability education are used interchangeably. A critical view on these two concepts is presented in Chap. 4.

In the past, notions related to global citizenship and sustainability have been part of STEM standards and documents, but despite their presence, classroom instruction has focused heavily on core content. The Next Generation Science Standards, developed by the National Academies in the United States, addresses skills needed for global citizenship and places greater emphasis on sustainability than previous standards. However, it remains to be seen whether these standards will be implemented rather than ignored, as similar standards were in the past. Much depends upon whether assessments contain a substantial number of items that look into student understanding in these areas. Whether these standards are addressed in classrooms will also depend upon the political climate and views about the purpose of education in countries around the world. Those who deny climate change and view globalization negatively could exert influence to prevent global citizenship and sustainability from being addressed in the curriculum and classroom.

Underlying a host of cultural perspectives is the nature of science (NoS, see Chap. 2 in this book)—the idea that things in the universe exist and events in it occur in consistent patterns that are comprehensible by systematic gathering of information through various forms of direct and indirect observations and testing this information by methods including, but not limited to, experimentation. The principal product of science is knowledge in the form of naturalistic concepts and the laws and theories related to those concepts. Building on the notion of scientific inquiry, Chap. 2 elaborates on the related inquiry-oriented pedagogy—a teaching method that fosters students’ deep understanding of NoS by engaging students in the practices of science, including posing questions, developing evidence-based explanations, building and using models, analyzing data, creating and defending arguments, using critical thinking, and communicating conclusions.

An almost synonymous term, very often used to refer to these skills collectively, is higher-order thinking, which indicates the kinds of students’ cognitive activities that are beyond the lower level kinds of thinking, such as recall of memorized bits of information and following a well-defined algorithmic procedure to solve a quantitative problem by plugging numbers in formulae. Higher-order thinking, in contrast, means applying, analyzing, evaluating, transferring, and creating. Examples of higher-order thinking in science include constructing arguments, asking research questions, making comparisons, considering and evaluating controversial issues, establishing causal relationships similar to how scientists think, and incorporating moral issues into scientific debates (Chap. 2 in this book).

A major concept in science education is scientific literacy. In 2015, the Organisation for Economic Co-operation and Development (OECD) Programme for International Student Assessment (PISA) defined scientific literacy as “the ability to engage with science-related issues, and with the ideas of science, as a reflective citizen” (PISA 2015, p. 7). There are different visions of what scientific literacy should encompass. These range from learning science for further training, via knowledge and understanding, to making the natural world and technological ramifications of science meaningful and accessible to the learner, toward critical visions of science learning for societal participation and action (Chap. 4 in this book). The latter vision emphasizes transformative learning and critical global citizenship. Indeed, transformative learning is a process in which the individual transforms and extends prior knowledge, beliefs, and attitudes. Transformative learning also includes active participation in critical discourse, in which the individual is exposed to the experiences and views of others in order to extend her own views on the world and society. Mathematics literacy, discussed in Chap. 12, which is essential for modern citizens, refers to the application of mathematical knowledge and skills in various situations. It includes reasoning mathematically and using mathematical concepts, procedures, facts, and tools to describe, explain, and predict phenomena.

Understanding the nature of science, fostering the practices of science, scientific and mathematical literacy, and higher-order thinking are more important than ever. In the new digital age, where anyone can post statements online, tweet, or blog, and the existence of facts is being debated, students need the skills and knowledge to navigate through this world. The ability to distinguish between a claim and evidence, to evaluate the evidence to support a claim, and to relate a claim to a larger conceptual framework is strongly related to global citizenship and sustainability. So too is mathematical literacy, where arguments are based on numbers and numbers are used to make predictions resulting from mathematical models.

The authors of Chap. 8 argue that engineering design cognition is a reciprocal interplay between knowledge acquisition and knowledge application that the designer engages in throughout the problem-solving process. While teaching practices often emphasize acquisition more than application or vice versa, the problems engineers tackle are often novel, typically due to their context, such as location or primary users. The authors present diverse definitions of design or design inquiry to emphasize the multifaceted views of design similar to the argument about the nature of science. Design or design inquiry has (a) multiple solutions, among which the designer selects the best one viable for the given context; (b) a set of strategies used by designers, which starts with building deep understanding of the problem and its context; and (c) a cognitive activity that involves reasoning (Chap. 8 in this book).

Behind the greater emphasis on engineering, design, design cognition, and design inquiry is the recognition that many of the problems the world faces today are engineering problems with engineering solutions. Exposing students to engineering before university serves to increase the number of students who will go on to study engineering. Exploring design cognition and design inquiry is a response to stakeholders and employers who are calling for better prepared engineers and serves to improve university instruction in engineering programs.

Innovation, defined as the generation, utilization, and circulation of new knowledge, is widely acknowledged among policy makers in Europe as being critical for countries to stay competitive in the twenty-first century, and this is true for all nations (Chap. 11 in this book).

15.1.2 Metacognition

As should be expected from this book’s title, a major theme of almost all the chapters in this book concerns cognition- and metacognition-related issues.

Metacognition, first defined by Flavell (1979) as higher-level cognition or cognition about cognition, or thinking about thinking, encompasses a set of skills that enable learners to understand and monitor their cognitive processes. Discussed in Chap. 9, metacognition is concerned with knowledge of cognition—what students know about their knowledge and regulation of cognition and what students can do with this knowledge to better control their learning.

Metacognition-based pedagogical intervention is pedagogical intervention that aims at enhancing specific scientific and metacognitive skills. Such interventions are often accompanied by assessing their effect on the students (Chap. 3 in this book). It also refers to teaching learners how to learn and solve problems by guiding them to activate and implement metacognitive processes, such as planning, monitoring, control, debugging errors, and reflecting. As argued in Chap. 13, pedagogical metacognition is metacognition that relates to understanding and knowing how, when, and why to implement or integrate metacognition in teaching and learning. Meta-cognitively oriented teachers are aware of their students’ learning processes and apply instructional methods that help students to be also aware of their learning.

Metacognitive self-regulation, discussed in Chap. 13, is an important aspect of the self-regulation cycle that relates to regulation of cognition and involves five kinds of strategies: planning, information management, monitoring, debugging, and evaluation.

Knowledge of cognition refers to what individuals know about their own cognition or about cognition in general, as discussed in Chap. 3. It includes at least three different metacognitive types of awareness: declarative knowledge (“about”), procedural knowledge (“how to”), and conditional knowledge (“why” and “when”). Knowledge of cognition is relatively stable but is age dependent. While it can be imperfect, one can often state it explicitly.

Regulation of cognition refers to regulatory skills and involves several metacognitive strategies, such as planning, evaluating, and monitoring. Some researchers refer to regulation of cognition as information management, or “debugging,” which sometimes replaces the “planning” element. Regulation of cognition is relatively unstable and age independent, and several studies suggest that it can be learned (Chap. 3 in this book).

Metacognitive science learning is a learning process that employs one or more metacognitive skills in some science education domains and settings, as discussed in Chap. 3. More specifically, metacognitive self-directed questioning, suggested by the authors of Chap. 12, calls for using four kinds of metacognitive questions for inducing comprehension, connection, strategies, and reflection.

The metacognitive teaching method IMPROVE is an acronym of all the teaching steps: introducing the new materials to the whole class by modeling the metacognitive questioning, metacognitive questioning in small groups, practicing by using the metacognitive questioning, reviewing by using the metacognitive questioning, obtaining mastery on lower and higher cognitive processes, verification, and enrichment and remediation (Chap. 12 in this book).

Assessment, in the context of this book, is the process of collecting and processing data or evidence about the impact of education. Assessment of students’ learning outcomes specializes into two major types, formative and summative, as elaborated in Chap. 9. In this book, assessment is a major focus in the metacognition theme but less so in the cognition theme. Researchers who study students’ cognitive learning outcomes use a variety of assessment tools. Based on Chaps. 3 and 9, assessing metacognitive skills is important, but researchers are still struggling to measure these skills.

Metacognition assessment tools are quantitative and qualitative tools for assessing students’ metacognition. Examples, presented in Chap. 3, include Physics Metacognition Inventory and Self-Efficacy Metacognition Learning Inventory—Science. The need to develop new approaches for engineering education has been a trigger for the development of meta-assessment, or assessment of assessment, as a technique for systematic evaluation of the assessment process itself, defined and discussed in Chap. 9. Student-oriented meta-assessment relates to assessment of how students assess their peers’ outcomes. This peer assessment, namely, an arrangement in which individuals consider the amount, level, value, worth, quality, or success of the products or outcomes of learning of peers of similar status, is discussed in Chap. 9.

Research and development in the area of metacognition are driven by the recognition that learning is a process that teachers and technology can support, but it ultimately takes place within an individual by that individual. Moving learning from rote fact recall to deep processing is complex, and the various chapters addressing metacognition are attempts to determine how best to foster metacognition. Metacognition does not occur automatically; teachers must teach students the concept and language of metacognition explicitly and embed metacognitive activities in the content they teach. Metacognition is not altogether generic, and each of the book chapters that addresses metacognition makes this clear. Thus, although metacognition is thinking about one’s own thinking, and aspects of one’s thinking such as monitoring can be identified, it is thinking about one’s own thinking in specific contexts.

15.1.3 Culture

The third theme, along with cognition and metacognition, is culture, defined in Chap. 6 as sociohistorical knowledge and practices embedded within communal, linguistic, economic, and technological contexts. Culture relates to values, and the concept culture and values reflects the context of the users, their associated beliefs about progress, and the patterns of organization. Interactions with culture and values impact technologies’ realizations and diversity. Understandings of culture and values thus emerge from concurrent understandings of technology and ways people practice it, as argued in Chap. 7.

A key concept of the central and northern European culture of education is Bildung, a cornerstone of Chap. 4, which traces back to Wilhelm von Humboldt’s works in the late eighteenth century. Bildung, according to von Humboldt, is a process of forming the personality toward individuality. The contemporary interpretation of Bildung, which started to develop in the 1950s, focuses on allowing the individual to develop capabilities and attitudes for self-determination, participation in, and solidarity with society. Bildung is one of the cultural perspectives of a particular group of individuals in a particular time that aim at understanding the complex sociocultural context. Other key cultural perspectives are language, knowledge, worldviews, beliefs, morals, customs, habits, and activities. Chapter 4 elaborates on how applying cultural perspectives to science education helps direct our attention to interactions and diversity across different cultures, curriculum models, disciplines, and students’ academic classes or ages.

In order to facilitate connecting what learners learn to the worlds in which they live, pedagogy in STEM in general, and in mathematics in particular, has to be culturally relevant. Culturally relevant pedagogy, discussed in Chap. 14, is an approach to developing curricula and classroom practices that enable students to resist assimilation into the cultural norms of the majority and to use classroom learning to take action in their communities. Culturally relevant pedagogy supports students as they experience academic success, develop and maintain cultural competence, and develop a critical consciousness, through which they challenge the status quo of the current social order. Culturally relevant pedagogy can be instrumental in mathematical modeling—a process by which a real-world situation is analyzed, described, or understood using mathematics. The process, described in Chap. 14, is typically iterative. It involves stating assumptions, translating a description of the situation into mathematical equations, drawing conclusions from the mathematical solution, and revising the choices made along the way.

Culture is an aspect of cognition, metacognition, curriculum development, and standards that is often neglected. Addressing culture in instruction raises the question of whose culture: national culture or that of minority groups or all? Culture in instruction also runs the risk of trivializing or stereotyping some cultures and criticism of cultural appropriation. However, examining the role of culture in STEM has enriched our understanding of why some students disengage from the curriculum, why some students feel that they do not belong in a STEM career, and why some engineering projects have not been successful.

Technology is defined in Chap. 6 in the educational context as networked information and computing devices, methods, and technologies, such as iPads, Web 2.0 tools and resources, digital video recording and editing, scientific models and simulations, and digital scientific measurement via probeware.

Chapter 7 introduces the term culture of technology—the web of human interactions and activities that are mediated through the use, status, supply, and organization of technology, along with the human skills and knowledge associated with it. Culture of technology is deeply wrapped into lifestyles, expectations, values, and beliefs. For precollege science classrooms, it is affected by the context of use, science classroom users, and expectations of science teaching and learning. This is especially true for digital natives, discussed in Chap. 6, who are the generation of children, typically born after 1980, and who have grown up with considerable exposure to personal computers, video games, and the Internet. An example of the effect of a specific culture is the Anglo-American tradition. This engineering education tradition, discussed in Chap. 11, began in Anglo-American countries during the first Industrial Revolution (1760–1840s) and was characterized by high levels of self-government, where engineers were mainly entrepreneurs or freelance professionals who had learned advanced science and mathematics on the job. A parallel example is the Continental European tradition, which started in continental highly bureaucratic European countries, such as France, where engineers were mainly public servants who had learned advanced science and mathematics in school.

Analogous in some sense to the nature of science, the nature of technology (NoT, see Chap. 7 in this book) serves as an explanatory basis for how technologies evolve and interact with individuals, society, culture, institutions, and the economy. The NoT interrogates the artifact—the technology, its interactions with humans, and the role that culture and context play in these interactions. NoT engages the full system, product, or service life cycle, from conception, design, and development to enactment, usage, and discard. The NoT framework addresses five core dimensions that help to explain realizations of technology in precollege science classrooms. These dimensions address the role of culture and values, notions of technological progression, technology as part of systems, technology diffusion, technology as a fix, and technological expertise. The work of philosophers of technology, specified and discussed in Chap. 7, is a prime source of information needed for understandings of NoT.

One recent pedagogical approach enabled by technology is the flipped classroom. This approach uses online Web-based video resources to explain and explicate content that is traditionally provided through lecture, freeing up class time for more interactive learning activities, as elaborated on in Chap. 6. The flipped classroom is an example of an innovative teaching and learning approach that is being increasingly studied through an iterative process. This process includes creating classroom activities and using technology to drive inquiry and socially interactive learning activities and is applicable to teaching and learning of all STEM domains. More specifically, a Web-based environment, discussed in Chap. 13, is a learning and teaching environment that provides possibilities for learning and teaching in synchronous, asynchronous, autonomous, and collaborative modes by giving access to open-ended activities that move beyond theoretical declarative knowledge into complex learning and teaching, supporting cognitive and metacognitive processes. Such technologies free the time of both students and teachers for reflection—a systematic and socially situated practice of observation, evaluation, and modification of one’s knowledge and social activity (Chap. 13 in this book). Web-based environments also facilitate cyberlearning through the use of networked learning technologies, discussed in Chap. 5, which have the potential to expand and transform learning opportunities, interests, and outcomes for all learners.

Philosophers of technology explain that technology is best understood in light of cultural structures and expectations, jointly termed scaffolding. As explained in Chap. 5, similar to how construction scaffolds support construction workers and extend their reach, instructional scaffolds support learners and allow them to perform tasks that they would not be able to do without this support. Examples include sentence starter prompts, explicitly defined roles and responsibilities, and partially completed examples. Addressing technology in a book about STEM is difficult. Technology changes so rapidly that research quickly becomes outdated. Technology also has the problem of overpromising. In the past, the technologies of television and language labs were touted as the tools that were going to transform education. Yet, the impact of these technologies was minimal. A variety of interesting current technology-driven experiments, such as cyberlearning in general and the flipped classroom in particular, have great potential while facing some serious challenges. Teachers need better training in the pedagogies of technology. Students, especially in lower socioeconomic classes, need easier access to the Internet, and schools need improved infrastructure to support these rapidly changing technologies. Educators should learn a lesson from the work in adaptive technologies for individuals with disabilities. In that work, one of the foci is on whether the individual can use an adaptive technology in school and not whether the adaptive technology helps the individual learn. Students and teachers can use many forms of technology, and our emphasis should be on whether those technologies support learning and under what circumstances.

Engineering education, another issue addressed in this book, is defined in Chap. 10 as the actions taken to educate and train novices to become practicing engineers. Engineering education includes the structure, curricula, and pedagogical approaches used to prepare students for careers as valued members of the engineering workforce.

Engineering culture is defined in Chap. 10 as a set of behaviors or beliefs that characterize the field of engineering. It encompasses the norms established by an engineering group, primarily industry, which are continually passed from one member to another. More specifically, engineering education culture is the set of behaviors, norms, and beliefs that characterize the field of engineering education. The authors argued that different educational units or environments, such as an engineering college, school, department, or program, may have a different engineering education culture and therefore typically exhibit diverse and different everyday actions when applying engineering education. In particular, this can apply to the process of enculturation as an engineer—understanding and adopting the traits of a professional engineer for becoming part of the engineering discipline. As explained in Chap. 10, as part of this process, individuals discover their identity as engineers within the greater field of engineering.

Many new approaches in engineering education include a component of project-based learning (PBL). This teaching and learning method, discussed in Chap. 9, focuses on developing a project in order to engage students in sustained, cooperative investigation, combining academic knowledge with real-world applications. Applying PBL in appropriate socioeconomic contexts, students learn to manage increasingly complex systems of scientific knowledge while gaining practical skills and contextual awareness in an organic, integrated fashion. PBL is confusingly also an abbreviation of problem-based learning (this abbreviation is more commonly used in Europe), and as argued in Chap. 11, a critical component of this kind of PBL is the scaffolding of a network of problems with increasing complexity, spanning from reproductive learning in the form of routine to complex problem-solving in contexts. It also involves the complexity of real-life settings, which promotes creative learning. Indeed, collaborative problem-solving, discussed in Chap. 5, is a core STEM practice and a critical and necessary twenty-first-century skill, as it relates to individuals working together to set shared goals, negotiate, and ultimately solve problems, particularly those with potentially multiple solutions and solution paths.

As mentioned earlier, engineering educators are concerned about preparing engineers for the world of work. In response to criticism about the lack of diversity in the engineering workforce and the call for better-prepared engineers, engineering educators have taken a hard look at the culture of engineering and changes it should undergo. Being practical minded, engineering educators have borrowed heavily from psychology, education, and the learning sciences to improve the preparation of engineers. Chapters 9, 10, and 11 reflect the concerns about diversifying the engineering workforce and preparing a more skilled engineering workforce. Many innovations in engineering education have been introduced in response to the 2007 book Rising Above the Gathering Storm: Energizing and Employing American for a Brighter Future (National Academies of Engineering and Institute of Medicine, 2007).Footnote 3

The concern for educating a better-prepared engineer through better instruction is not just a US phenomenon. Aalborg University in Denmark has long been a leader in project-based engineering education, and engineering programs around the world have adopted many of these approaches to instruction.

15.2 Summary and Future Research

Reviewing research in all four STEM domains and referring to the three book themes enable us to draw generalizations and go beyond the state of the art of cognition, metacognition, and culture in STEM education.

  • Cognition and metacognition play essential roles in enhancing STEM literacy and students’ learning in all four STEM domains and at various age levels.

  • Several authors have shown that metacognition can be enhanced in typical classrooms and under regular school conditions.

  • Many of the current effective innovative teaching methods include one or more metacognitive components. Examples of these methods include problem- and project-based learning (PBL), inquiry-oriented pedagogy, IMPROVE, engineering design inquiry, flipped classroom, Web-based environment, cyberlearning, and collaborative problem-solving.

  • Assessment tools that are based on metacognitive inventory have been proven to be effective for both formative and summative evaluation in small and large courses.

  • Beside cognition and metacognition, culture provides another important perspective on STEM learning. For example, in many Western countries, girls tend to avoid majoring in STEM domains, but this is not the case in Eastern countries. Furthermore, while in some countries, such as Singapore, metacognitive skills are part of the mandatory mathematics curriculum; in other countries the teacher can decide whether she or he would like to include these higher-order thinking skills in STEM instruction.

  • Educational systems are as good as the teachers within them. The role of the teachers becomes even more crucial in STEM education. Examples of teachers’ professional development to improve pre- and in-service pedagogical content knowledge are training for inquiry-oriented pedagogy, reflecting on the teachers’ own videos, and practicing mathematical modeling.

The authors of these book chapters have suggested various ways in which their research can be extended and refined. Before closing the book, in which work on three themes that are often studied separately is presented in an integrated way, we take this opportunity to stimulate the readers to investigate new research directions. We summarize the authors’ suggestions and ours by chapters.

In Chap. 2, “Teacher Cognition of Engaging Children in Scientific Practices”, Crawford and Capps (2018, in this book) focus on teachers’ subject matter knowledge, pedagogical knowledge, pedagogical content knowledge of scientific practices, and the nature of science. They document the various types of knowledge of teachers prior to and following a professional development course that the authors conducted. Based on their study, it would be interesting to relate the qualitative findings concerning two teachers to the entire group of 30 teachers who participated in the professional development program overall. Two interesting questions in this context are: How did the group 30 teachers reflect on the model presented in this chapter? Can we identify initial categories of teachers’ professional growth based on the model the authors suggested?

Chapter 3, “Students’ Metacognition and Metacognitive Strategies in Science Education” by Avargil, Lavi, and Dori (2018, in this book), is a review that focused on students with respect to four study types: (1) theoretical papers, (2) papers focusing on assessment tools for metacognition, (3) metacognitive learning processes, and (4) metacognition-based pedagogical intervention. They found very little on the first two study types, so it would be important to deepen the theoretical research and develop more tools for assessing metacognition. While the focus of the review was students, the authors found out that the literature on teachers and metacognition is also scarce, so investigating metacognition from teachers’ viewpoint is also in order, as is the case with younger students.

The three different visions of scientific literacy presented in Chap. 4, “Reconsidering Different Visions of Scientific Literacy and Science Education based on the Concept of Bildung” by Sjöström and Eilks (2018, in this book), are based on the concept of Bildung in the context of science education. Vision III, the most complex one, aims to foster a change in society, which would make it more sustainable. However, one could argue that implementing this complex approach in science education would require more resources, including money, time, and expertise, than doing so for either Vision I or II. Future work could use the theoretical basis of the complex vision presented in this chapter as a basis for designing curricula and action research to benefit the learner, science education, and the society.

In Chap. 5, “Designing for Collaborative Problem Solving in STEM Cyberlearning,” Crippen and Antonenko (2018, in this book) provide a detailed description of their self-developed design framework for cyberlearning via collaborative solving of authentic problems. This framework contributes to STEM education research by providing an opportunity for studies into collaborative STEM problem-solving in online environments. The framework contributes also to STEM education in general by leveraging collaborative problem-solving to enhance meaningful learning. Future studies into the implementation of this framework in other STEM subjects would provide researchers with an account of how collaborative problem-solving enhances learning in the different STEM subjects. Such studies would also provide instructors with knowledge on how to best implement this framework in their classrooms. The authors discuss planning, monitoring, and reflection as components of metacognition relating to regulation of cognition within their framework. Future studies can help integrate into the framework also declarative, procedural, and condition components of knowledge of cognition.

Chapter 6, “Technology, Culture, and Young Science Teachers – A Promise Unfulfilled and Proposals for Change” by Yerrick, Radosta, and Greene (2018, in this book), is somewhat surprising in revealing that the preservice teachers studied were not quite the digital natives portrayed in the literature. While the preservice teachers did engage with technology for personal use, teaching with technology was “sparse.” Moreover, the preservice teachers did not describe themselves as being creative in the use of technology in their teaching. The authors point out that not all technologies are equal and that some are more useful in supporting preservice teachers learning than others. The authors provide a cultural explanation for the low level of engagement in the example of an inquiry activity. However, one wonders if the preservice teachers’ limited use of technology to teach inquiry has more to do with their misperceptions of what inquiry is than their proficiency in using technology for teaching and learning. Alternatively, the technology tasks that the students explored may not have been sufficiently engaging, resulting in their limited enthusiasm and effort and a disinclination to use technology in their own teaching. Furthermore, as the preservice teachers experienced, trouble with the technology can be disastrous in the science classroom in terms of management and completion of lessons. Yet, the preservice teachers considered the reflection videos important to improving their teaching. It is worth investigating whether the positive results are due to reflection, the type of technology used, or some combination thereof.

In Chap. 7, “Technology, Culture, and Values: Implications for Enactment of Technological Tools in Precollege Science Classrooms,” Waight and Abd-El-Khalick (2018, in this book) provide a framework for integrating technology into the science classroom that takes into consideration the nature of technology and its place in culture and society. This framework enables instructors to better integrate technology into teaching and learning based on their specific teaching environment. It also helps researchers to conduct intervention studies concerning the use of technology in science education in various contexts. Future studies should strengthen the theoretical basis of the authors’ framework by integrating insights from Vigotsky’s seminal work on the place of technology in education and test the effectiveness of this framework in sciences other than biology and in other STEM subjects.

In Chap. 8, “Engineering Cognition: a Process of Knowledge Acquisition and Application,” Purzer, Moore, and Dringenberg (2018, in this book) conceive engineering design cognition as a combination of knowledge acquisition, which is a goal of project-based learning, and knowledge application, which is a goal of problem-based learning, as key factors in knowledge production. Engineering design cognition can therefore serve as a potential framework for combining these two active learning approaches into a coherent and effective engineering design instruction approach. Intervention research with a combined project- and problem-based learning curriculum within the engineering design cognition framework could potentially provide fruitful learning and research outcomes.

Chapter 9, “Metacognition and Meta-assessment in Engineering Education” by Wengrowicz, Dori, and Dori (2018, in this book), combines theory and practice. It describes the assessment model, the course, rubric, and projects. The course and the pedagogy clearly require a great deal of upfront work on the part of instructors. The data that shows the effectiveness of the peer meta-assessment may convince others to try this approach. Students’ excerpts indicate that they were asking metacognitive questions, showing that they were able to evaluate clarity and understandability, completeness, correctness, and documentation of their peers’ projects. The Appendix in Chap. 9 shows that while the students in the large class found the task demanding, students in the small class noted that it had helped them learn the conceptual modeling languages. Given the characteristics of the students in the two courses and the difficulty of the task as expressed by students in the large class, the question that arises is whether this model of instruction is generalizable to students attending less selective institutions, especially those with larger classes. Future research on the effectiveness of the approach should compare and contrast the impact of the approach in a variety of instructional and cultural settings.

In Chap. 10, “The Impact of Culture on Engineering and Engineering Education,” Carberry and Baker (2018, in this book) discuss the relationships between engineering, engineering education, and culture. They show how cultural perception of engineering and the resulting engineering education and engineering culture impact men and women’s approach to and place in engineering. The authors provide educators, educational policy makers, and public communicators of engineering and engineering education with a basis for making engineering education more culturally accessible to women. The findings of the authors’ survey could also be used in the development of tools for assessing students’ attitudes toward engineering and engineering education. Future work suggested by the authors could focus on developing concise definitions of engineer, engineering, and engineering education, while empirical studies could explore students’ reasons and arguments for choosing a career in engineering from a gender perspective. Findings from these studies would help inform both educational and public communication efforts.

In Chap. 11, “Engineering Education in Higher Education in Europe,” Corlu, Svidt, Gnaur, Lavi, Borat, and Çorlu (2018, in this book) provide insight into how engineering education systems have developed across Europe. They link this development to the innovation score of the European Commission (EC) by comparing engineering education systems in three European countries. The chapter includes a detailed description of the systems in Denmark and Turkey and comparing them to the UK’s engineering education system. Future studies could provide a more detailed characterization of engineering education systems and of innovation that go beyond the EC’s definition. Additional comparisons of different European and other countries’ engineering education systems can further elucidate the relations between these systems and innovation.

In Chap. 12, “Cognition, Metacognition, and Mathematics Literacy,” Mevarech and Fan (2018, in this book) describe a pedagogical method for mathematics problem solving and its positive impact on students’ mathematical literacy. This method is based on problem solving processes embedded within metacognitive scaffolding through question posing. The authors’ method is implemented by the classroom teacher following an evaluation for its effectiveness. This method can be adopted by and adapted to other STEM subjects. The authors encourage teachers to place problem solving at the center of their students’ mathematics learning process. This pedagogical method could be adapted to various collaborative authentic problem solving processes, thereby contributing not just to promoting students’ mathematical literacy, but also to boosting their ability to solve authentic mathematics problems, both individually and collaboratively.

The cognition/metacognition and teaching instruction model in Chap. 13, “Promoting Mathematics Teachers’ Pedagogical Metacognition – a Theoretical-practical Model and Case Study” by Kohen and Kramarski (2018, in this book), advocate moving the preparation of mathematics teachers from simply providing them with a series of instructional strategies to challenging the teachers to engage in student-centered teaching. This approach encourages knowledge construction through metacognition and self-regulation. As the authors point out, this is a sorely needed change in the approach to mathematics teacher preparation, since metacognition develops slowly and is quite poor among both students and teachers. Mathematics education lacks a vocabulary to communicate teachers’ classroom activities, which this model provides. The case study of two female teachers has benefits and limitations as a test of the model. Further research is needed for the generalizability of the instructional model to the preparation of elementary teachers who have limited mathematics backgrounds, to teacher preparation programs outside Israel, and to minority students preparing to be mathematic teachers. Furthermore, the preservice teachers taught their peers. Testing the model in a variety of contexts with a broader range of students and in real classrooms will provide mathematics educators with the knowledge they need to improve the preparation of future mathematics teachers.

In Chap. 14, “Mathematical Modeling and Culturally Relevant Pedagogy” by Anhalt, Staats, Cortez, and Civil (2018), the authors state that two pedagogical approaches rely on students’ knowledge of everyday situations: mathematical modeling and culturally relevant pedagogy. Yet, the question of how to combine these two approaches in the mathematics classroom has remained open. The chapter intends to remedy this situation by reviewing the relevant literature in two disparate disciplines and providing an in-depth exploration of a concrete example of how modeling and culturally relevant pedagogy can be combined. The rationale for combining the two approaches is that it will improve students’ performance and be more motivating and relevant to them. The authors base this claim on the positive student outcomes found in the research literature. The authors provide a brief description of the impact of including a module of mathematical modeling and culturally relevant pedagogy in a mathematics pedagogy class. Given the short duration of the module, it is understandable that the impact was modest. However, the trial of the module did identify the difficulties preservice teachers, and most likely also in-service teachers, will encounter while trying to combine modeling with students’ funds of knowledge. Another difficulty the preservice teachers encountered was the development of a critical consciousness through which they would challenge the status quo of the current social order. Future research should look into whether the combination of mathematical modeling and culturally relevant pedagogy is more effective than traditional mathematical pedagogies.

For STEM teachers to be able to perform these different roles, they must possess advanced cognitive and metacognitive skills, as well as cultural awareness. This will enable them to better monitor and improve students’ learning and teach the students in ways that suit their cultural backgrounds. Effective monitoring of students necessitates assessment, making teacher assessment literacy another important competency for teachers to possess (Avargil et al. 2012; Dori and Avargil 2015; Xu and Brown 2016).

Anyone interested in implementing teaching focused on cognition, metacognition, and culture on a wide scale can draw encouragement from empirical demonstrations of improvements in cognition and metacognition. Examples include those described in Chaps. 2 and 3 for science students and teachers, respectively, in Chap. 9 for engineering students, and in Chaps. 12 and 13 for mathematics students and teachers, respectively. The impact of culture-aware teaching on learning outcomes, including cognitive and metacognitive skills, discussed in Chaps. 4, 7, 10, and 14, is therefore a fruitful direction for future research in STEM education.We conclude by noting that this book concerns three major topics of STEM education research—cognition, metacognition, and culture. The findings and conclusions presented throughout this book provide three overarching suggestions for STEM teachers: (1) nurturing cognitive skills in students to help them attain STEM knowledge in various domains, (2) developing students’ metacognitive awareness to help them set learning goals and plan for achieving those goals, and (3) teaching students in culturally appropriate ways while helping them acquire cultural knowledge and values.