As described in Chapter 2, the changes that occur during middle and high school (learners experiencing rapid changes physically, socially, and cognitively) may directly or indirectly affect learners’ overall interest in school, and their specific interest in science investigation and engineering design. Middle and high school students are beginning to form their own identities—as individuals and potential scientists and/or engineers. Peers can exert influences on the choices that learners make about their engagement and participation in academics and other activities that potentially compete for their time and attention (Eccles and Barber, 1999). Moreover, learners from traditionally underrepresented populations are also constructing their ethnic and racial identities at this time (Rivas-Drake et al., 2014), which may be affected by whether they see scientist or engineer as a plausible identity for a member of their group. As such, learning, interest, and motivation to learn are essential when considering students’ involvement in science investigation and engineering design.
America’s Lab Report (National Research Council, 2006) focused on many aspects of laboratory experiences, but the research on learning was narrowly discussed. Over the past decade, substantial progress has been made examining aspects of learning, interest, and motivation that facilitate student engagement in investigation and design (Blumenfeld, Kempler, and Krajcik, 2006; Lazowski and Hulleman, 2016; Linnenbrink-Garcia and Patall, 2016; Nieswandt and Horowitz, 2015). In particular, the contexts in which learning takes place are important because they can engage learners in authentic tasks that are culturally relevant and meaningfully support the development of connected knowledge (or deep learning) so that learners
could then apply their knowledge to other situations (National Research Council, 2012). These contexts encourage learners to raise meaningful questions and facilitate their sustained learning on cognitively challenging tasks. When supports from a myriad of relevant contexts converge in the science classroom, science and engineering ideas emerge as needed to address challenges, design solutions, or make sense of phenomena.
Developing usable knowledge requires the learner to actively engage in making sense of human challenges and natural phenomena about which they develop and refine questions, make predictions, and explain phenomena using repeatable and reliable evidence (National Research Council, 2012). For the knowledge to become more connected, learners need to apply their knowledge to new phenomena and design solutions by building from prior knowledge and experiences that allow for opportunities that reflect on their learning (Novak and Gowin, 1984). By using multiple representations of information (e.g., gestures, diagrams, graphs, equations) within diverse and meaningful contexts, learners’ knowledge becomes more connected and more refined (Waldrip, Prain, and Carolan, 2010). Moreover, learning is enhanced within a collaborative and inclusive community in which discourses are used as tools to express knowledge and debate and come to resolution regarding ideas and the validity of evidence to support claims (Osborne, 2010).
This chapter begins with a discussion of the different theoretical perspectives about learning that have shaped science education. Several themes that are part of a rich learning context are then discussed. The chapter concludes with a discussion of the importance of interest and motivation for science investigation and engineering design.
The cognitive perspective of learning is the traditional view of learning. A cognitive perspective treats the individual learner as the primary unit of analysis, highlighting the processes and structures hypothesized to operate in an individual’s mind as he or she physically interacts with others, objects, and events or mentally imagines these interactions. The focus on the minds of individuals in the cognitive perspective is useful in understanding behavior and promoting change within an educational system that tracks performance achievements and gains of individual learners.
In contrast to the cognitive perspective, the sociocultural perspective of learning emphasizes context. Context is multifaceted and encompasses conditions directly and indirectly connected to the learner. At one extreme, it refers to the immediate settings in which learners are directly involved; the science classroom is an example of this facet of context. At the other extreme, context refers to conditions far removed from learners’ direct participation but that nonetheless impact them: Institutional arrangements
like state formulae for funding education and certification requirements for highly qualified science teachers exemplify this aspect of context. The general notion of context captures the relational nature of learning—the learner’s relationship with others; the material resources available and experiences to facilitate learning; the learner’s relation to the formal and informal protocols and procedures operative in the spaces in which learning occurs; and the learners’ relation to arrangements and decisions often far removed from the learner that produce policies that influence learning and other experiences (Cole, 1995). Although the initial learning context that supported early learning might fade, and as learning progresses other contexts become more prominent, they are all critical to the process of learning, interest, and motivation.
Sociocultural perspectives are useful in considering and addressing large-scale, persistent patterns in education (e.g., underrepresentation of females in computational fields)—particularly in educational systems historically and intentionally designed to differentiate access to education by group membership. A sociocultural account of learning emphasizes the following: (1) what is learned (e.g., practices, symbol systems) and what facilitates learning (e.g., tools) are culturally determined; (2) this determination is socially mediated by and situated within historical and contemporary sociopolitical conditions; and (3) the internal processes of individual learning are influenced by these cultural determinations and social mediations.
A more comprehensive perspective of learning integrates the cognitive perspective with the sociocultural perspective. This holistic perspective of learning emphasizes both what is internal and what is external to the learner (Cobb, 1994) and may prove useful in realizing the vision of science education proposed in A Framework for K–12 Science Education (hereafter referred to as the Framework; National Research Council, 2012). With educating all learners in science and engineering as its first goal, an integrative approach is necessary to fulfill the aims of three-dimensional learning (see Chapters 1 and 2 for an explanation of the three dimensions), with particular attention to making these practices equitable and inclusive. This approach allows for an understanding of the collective nature of some types of learning in the classroom. For example, the sense-making of groups as they work together on a phenomenon of design solution shapes the learning of the individuals working together.
Our view of learning for this report synthesizes the views of a number of significant reports on science education that each offered compilations of the current learning sciences research showing that learning occurs within and is inseparable from contexts. As can be seen in Box 3-1 and elaborated
on below, several common themes emerge from these reports. In addition, our view of learning in this report incorporates the importance of contexts reflected: Learning occurs within and is inseparable from contexts.
Learning Involves Making Cognitive Connections
In order to learn, it is necessary to form new connections among concepts and for knowledge to be useful in new contexts. Connections among concepts become formed and are enriched as learners interact with the world, respond to human needs, make decisions, and make sense of new experiences they encounter (Novak and Gowin, 1984). Some of the important types of connections learners make include connecting new concepts to prior knowledge and experiences, forming episodic connections to their lived experiences and the stories they hear, seeing analogies and contrasts between distinct concepts, and relating abstractions to concrete objects and experiences, either literally or metaphorically. As individuals use their knowledge, more connections are made among concepts.
Multiple and varied experiences enrich these connections (Chi, Feltovich, and Glaser, 1981; Ericsson et al., 2018; Goswami, 2012; National Academy of Engineering and National Research Council, 2014; National Research Council, 2000; Noble et al., 2012) such as through social and physical interactions with others and the world. These interactions provide rich, multisensory contexts that greatly aid memory and sense making. Social and physical interactions also help learners to develop metacognitive understanding of their own knowledge and ways of knowing, to reflect on what they do and do not understand, and to describe what they know through language (such as explanation and argumentation) and building and revising models (such as diagrams, systems of equations, physical prototypes, and computer programs). As a result, these interactions—making sense
of phenomena, gathering and analyzing data/information, constructing explanations and design solutions, and communicating reasoning to self and others—are all critical to learning. Science investigations can therefore enhance learning by providing physically and socially rich experiences that reveal and help form meaningful connections among concepts and offer ways to change existing concepts in the face of contradictions and reflections on learning.
When knowledge is organized with numerous meaningful connections, individuals can access that knowledge to solve problems, make decisions, and learn more. Elaborated webs of connected concepts are referred to as schemata. Schemata play roles in comprehension, remembering, and learning (Freebody and Anderson, 1983; Pritchard, 1990; Reynolds et al., 1982). Developing schemata is critical to learning because when an investigation activates that web of knowledge, the cognitive load1 is lower than if the activity is unrelated to previously acquired knowledge, allowing learners to learn more, learn faster, or figure out a new situation. Concepts that are not connected or connect in ways that do not allow access for problem solving and making sense of the world comprise inert knowledge, a knowledge that can be expressed but not utilized (Bransford et al., 1986; Gentner et al., 2009; Gick and Holyoak, 1980; Perkins, 1999; Renkl, Manid, and Gruber, 2010; Whitehead, 1929).
The evidence that meaningful learning has occurred is that individuals can use their knowledge in new situations, that is, transfer understanding of a concept to new experiences (National Research Council, 2000). In transferring understanding, connections between concepts become stronger and enriched. Transfer also relates to personal motivation when it supports learners in making connections from school learning to their values and lives outside of school (National Research Council, 2000). It is especially beneficial for learners and to societies in this scientifically and technologically advanced era when learning experiences facilitate the process of identity formation in which people come to think of themselves as engineering and science learners capable of doing investigation and design. The research is clear that usable knowledge—that is, learning that can be transferred to new situations—only occurs when individuals are actively making sense of the world (National Research Council, 2012).
Learning Is Developmental
Psychologists including Lev Vygotsky and Jean Piaget conceptualized learning in developmental terms with a primary emphasis on internal
mental structures (Piaget) and the interactions among internal processes and the social and physical world (Vygotsky).2 Vygotsky (reprinted in Cole et al. [eds.], 1978) defined the zone of proximal development as the difference between a child’s actual performance level from independent actions and the performance that is achieved when guided by a more capable other (e.g., a parent, teacher, or more experienced student). In an instructional setting, the zone of proximal development can be operationalized as scaffolding (Wood, Bruner, and Ross, 1976), where a more knowledgeable other provides social support within the child’s zone of proximal development to master a cultural skill, practices, or knowledge. These scaffolds then fade as the student demonstrates greater autonomy (Puntambekar and Hubscher, 2005).
Developing and revising models, as well as constructing evidence-based explanations for phenomena and evidence-based solutions to challenges, are complex cognitive processes that need to be scaffolded in classrooms and developed over time—they cannot be contained in isolated 50-minute class periods. Instructional resources can provide scaffolds by reducing complexity and providing hints (see Chapter 6), and teachers scaffold work synergistically with supports provided in materials to enhance the learning situation (McNeill et al., 2009; Tabak, 2004). Therefore, students benefit from coherent curricula that help them connect material across classes and grade levels and in which they can revisit concepts and ideas at multiple ages (see Chapters 5 and 6).
Learning Is Embodied and Involves Changing Actions and Perceptions
Actions are central to investigations. Experiencing phenomena and challenges and making sense of them through developing and revising models, arguing from evidence, planning and carrying out an investigation, or constructing an evidence-based explanation are critical to the aspect of doing science and engineering. Through actions, learners can improve their understanding of conceptual relations through such sensemaking mechanisms as spatial metaphor and causal inference. Different strategies (e.g., contextualizing, spacing through repeated exposure, and providing variability) to deliberate practice (Ericsson, 2008) have been linked to increasing the learner’s flexibility and retrieval of information.
2 Neo-Piagetians examined cognitive development from other theoretical perspectives, like social cognitive theory, and considered other complexities, such as interactions between the learner and contexts (e.g., others, tools) surrounding the learner. In similar fashion, neo-Vygotskian scholars have shown that children can operate beyond their autonomous levels of performance when they receive assistance.
An equally important consideration is the ways learners use their perceptions, so that they can begin to see (and hear, feel, and smell) the world differently. Engaging learning in various multimodal experiences—reading and writing text, experiencing phenomena, using simulations, interpreting graphs—is essential for meaningful learning. Investigations may enhance science learning because they engage learners’ embodied ways of knowing in service of perceptual, motoric, and procedural learning.
Learning Involves Social and Emotional Engagement in Communities
Learning is enhanced within a collaborative community in which language is used as a tool to express knowledge, argue explanations and solutions, and come to resolution regarding the validity of evidence to support or refute a proposed explanation (Osborne, 2010). Working with peers and knowledgeable others supports individuals’ learning new ideas and skills that they could not learn on their own. The back-and-forth of using ideas builds new connections and reinforces previously made connections.
When learners argue the validity of their evidence and share diverse perspectives on these ideas with others, their interactions help them to form new connections among ideas or enrich previous connections. Knowledge becomes shared within the community. As such, collaborations promote learners building shared understandings of scientific ideas and of the nature of the discipline (Krajcik and Shin, 2014). Teachers or more knowledgeable others need to support learners in collaborating, including listening to others’ ideas, being open to and respectful of others’ ideas, making use of others’ ideas, and pressing for more information.
Learning Is Influenced by Levels of Engagement
When students are cognitively engaged, they experience high levels of challenge, skill, and interest (Schneider et al., 2016) that will drive their learning (see the section “Interest and Motivation” below). Engagement relies upon learning principles, such as authentic situations, context, active engagement, choice, and collaboration to engage individuals and promote learning. Such environments engage learners in science investigations, collaborations, and artifact creation that represent their developing understanding. Not all environments promote cognitive engagement that sustain students in learning challenging ideas. More often than not, learning environments (i.e., traditional classrooms) do not push students to address
challenges that are important to them, make sense of phenomena that are situated in their lives, or allow them to make decisions about the direction of an investigation. Such environments do not inspire students to invest effort or to persevere in learning challenging ideas.
Learning Is Historical
Science education reforms often situate learning as a present-day, here- and-now neutral event that primarily involves the teacher or other knowledgeable other, the learner, and the materials and tools for science learning. A sociocultural view of learning with a focus on context acknowledges the historical, sociocultural nature of learning. For example, advanced education for many families with multigeneration college completers is a complex event that is expected and endorsed by the families. This event is also facilitated by conditions that persist across generations. Individual learners’ science learning can be a similar production.
On one hand, sociocultural perspectives can cast science learning as a local social practice. It is a contested space where the larger institutional issues (e.g., funding, teacher quality, historical inequities in access) and histories embodied in social practice (e.g., beliefs about who can and cannot do science) intersect (Holland and Lave, 2001; Penuel et al., 2016). On the other hand, sociocultural perspectives can situate science learning within a complex activity system (Cole, 1996a,b; Engeström, 2009). This system view allows a specific individual’s science learning at a particular moment in time to be examined in relation to the learner’s past experiences and future aspirations and the past and present experiences and future aspirations of the learner’s significant others. In addition, the complex activity system view allows for the consideration of science learning with respect to the learner’s membership in a socially defined group (e.g., gender, race, disability) as it pertains to the group’s historical and contemporary status in society generally and in the activity system in particular.
Learning as historical is illustrated in several ways in a case study about a young boy named Leonardi (see Box 3-2). For example, the case
highlights how the classification of Leonardi shaped the perceptions that teachers and school leaders had regarding his potential to engage with science learning. Learning as historical from the systems end of the sociocultural perspective continuum is implicit but nonetheless present in a myriad of ways: policy and resources around pull-out instruction, qualifications, and employment consistency of Leonardi’s past and present teachers who taught science, and the quality of the facilities and equipment to build and test the machine models are just a few.
Learning Occurs Within and Is Inseparable from Contexts
Learning, conceived as forming connections among concepts and changing perceptions and actions, is intricately linked to contexts. There are numerous examples of context as an intermediary of learning, but consistent illustrations appear in the Framework committee’s treatment of progression, the common element, distinctly sectioned throughout the report, to practices, crosscutting concepts, and core ideas, as excerpted here:
In the earliest grades, as students begin to look for and analyze patterns—whether in their observations of the world or in the relationships between different quantities in data (e.g., the sizes of plants over time)—they can also begin to consider what might be causing these patterns and relationships and design tests that gather more evidence to support or refute their ideas. By the upper elementary grades, students should have developed the habit of routinely asking about cause-and-effect relationships in the systems they are studying, particularly when something occurs that is, for them, unexpected. The questions “How did that happen?” or “Why did that happen?” should move toward “What mechanisms caused that to happen?” and “What conditions were critical for that to happen?” In middle and high school, argumentation starting from students’ own explanations of cause and effect can help them appreciate standard scientific theories that explain the causal mechanisms in the systems under study. Strategies for this type of instruction include asking students to argue from evidence when attributing an observed phenomenon to a specific cause. For example, students exploring why the population of a given species is shrinking will look for evidence in the ecosystem of factors that lead to food shortages, over-predation, or other factors in the habitat related to survival; they will provide an argument for how these and other observed changes affect the species of interest (National Research Council, 2012, pp. 88–89).
In addition to illustrating developmental influences, the above excerpt implicates contexts of learning in numerous ways that point out the synergy between sociocultural and cognitive perspectives on scientific reasoning.
The excerpt featured contexts as the setting (e.g., level of education, the stage for learning) in which student observations, questioning, and explanations occurred as they engage in investigation. Context is also implicit in the excerpt: fundamentals are not listed or clearly described but must be present for the described learning to occur. For example, contexts include the determination of the processes highlighted in the investigation and how these processes unfold; the materials needed to carry out the investigation (e.g., packaging and representation of phenomena for student examination); and more knowledgeable others to scaffold understandings (e.g., teachers employing instructional strategies). A change in any of the contexts—the settings, the tools used by learners, etc.—would alter the learning experience and the learning. The expansive nature of context (e.g., close proximity to and distant from the learner), the myriad manifestations of it (e.g., physical materials in classroom, policies that define what is valued, familiarity and value of the problem to the learner), and the integral function it plays in cognition and learning make context a critical tool in achieving inclusive excellence in science education and high-quality science learning for all learners.
As illustrated in the previous section, developing a deep and usable understanding of science as envisioned by the Framework involves forming new connections among concepts and application of that knowledge in new contexts. Learning is a lifelong process as people construct foundational knowledge through formal schooling and then expand knowledge throughout their lives as they mindfully engage in problem solving and making sense of the world. People are able and willing to engage with science from infancy through adulthood only if they are motivated to do so. The contexts of learning are important factors, and finding opportunities to cultivate motivation and interest in science investigation and engineering design is key.
Motivation can evolve and change over time and elements of the student’s learning environment can foster curiosity3 and interest that supports the motivation to learn (Hidi and Renninger, 2006). In general, motivation has been found to be a key mechanism for enhancing student learning outcomes in science (Lazowski and Hulleman, 2016). For example, the evidence for underrepresented learners suggests that issues related to interest
3 Curiosity is an additional construct often associated with motivational variables including interest. Like interest, curiosity can be thought of as a state induced by environmental factors, such as novelty and complexity, as well as a more stable trait (Silvia, 2012). However, curiosity is most often considered as an emotional factor (Renninger and Su, 2012), whereas most motivational variables consist of both emotional/affective and cognitive components.
and motivation may be the primary factor behind underrepresentation in certain STEM career tracks rather than ability (Wang, Eccles, and Kenny, 2013). However, the study of motivation in STEM learning is primarily supported by correlational or qualitative case studies (Lazowski and Hulleman, 2016) and as such, no direct mechanism has been specifically linked with motivated behavior and subsequent academic achievement (Linnenbrink-Garcia and Patall, 2016). To promote three-dimensional learning, creating meaningful environments that use various motivational constructs is essential.
Theories of Motivation
Due to the importance of interest and motivation for engagement in science investigation and engineering design and persistence in STEM more broadly, research has focused on student perceptions specific to science and engineering that can be barriers to motivation. In general, some learners have firm beliefs that they “just can’t do” science or engineering; perceive stereotypes that exclude groups from feeling they can participate; have little experience with science or engineering outside of academic context; and/or feel that learning in science or engineering has little inherent value to them (e.g., “When will I ever use this?”). These barriers can be overcome through interventions that target specific or multiple motivational constructs; however, they are not necessarily able to address systemic exclusion of individuals or groups from participation in science and engineering (see Chapter 2). There are several different contemporary theories of motivation: expectancy-value, attribution, social-cognitive, goal orientation, and self-determination (Cook and Artino, 2016; Schunk, Meece, and Pintrich, 2014).
Eccles and Wigfield developed the ideas behind the theory of expectancy-value (Wigfield and Eccles, 2000). For this theory, motivation is a function of the expectation of success and perceived value. There are two pieces behind expectancy-value. The first concerns the expectation of success, which is the degree to which individuals believe they will be successful if they try. The second concerns the perceived task value, which is the degree to which individuals perceive the task as having personal importance (Cook and Artino, 2016).
Attribution theory, described by Weiner in 1985, explains why individuals differentially respond to a given experience. These different responses are thought to arise from the ways in which the individual perceives the cause of the initial outcome. There are three dimensions that can describe the “cause”: (1) locus—whether it is internal or external to the learner, (2) stability—whether it is fixed or likely to change, and (3) controllability—whether it is within or outside of the individual’s control (Cook and Artino, 2016). For example, Ziegler and Heller (2000) trained teachers of an 8th-grade physics
class to give feedback on student work that emphasized that the students’ efforts were responsible for their success. After 1 year of the physics classroom intervention, learners in a treatment group demonstrated increases in their belief of an internal attribution of success (i.e., success is attributed to effort) and achievement test scores as compared to a control group. Similar outcomes were found for high-achieving high school girls (although importantly, not for boys, who already had significantly higher beliefs in internal attributions of success) in chemistry who received attribution training through informational videos (Ziegler and Stoeger, 2004).
Social-cognitive theory of motivation is one that is also considered to be a theory of learning. It focuses on the reciprocal interactions among personal, behavioral, and environmental factors with self-efficacy being the primary driver of the motivated action (Cook and Artino, 2016). Bandura (1994) described self-efficacy as one’s belief in one’s ability to succeed in specific situations or accomplish a task. Interventions that target increasing student self-efficacy have also demonstrated a positive effect on motivation and achievement in science and engineering (Bong, Lee, and Woo, 2015; Linninbrink-Garcia and Patall, 2016). Promoting learners experiencing achievement appears to be the most common approach to positively influencing self-efficacy. Although this method of intervention does seem promising, there appear to be very few intervention studies aimed specifically at increasing self-efficacy in middle and high school science or engineering.
The theory of goal orientation focuses on whether learners tend to engage in tasks for mastering content (mastery goal), for doing better than others (performance-approach goal), or for avoiding failure (performance-avoidance goal) (Cook and Artino, 2016). Mastery goals are associated with interest and deep learning, whereas performance-goals are associated with better grades (Cook and Artino, 2016). Research has consistently shown that learners who demonstrate a strong belief that success in science is a result of effort are more likely to feel confident about their ability to engage with science, to persevere when the going gets tough, to retain what they have learned for long periods, to have generally positive attitudes toward science (Blackwell, Trzesniewski, and Dweck, 2007; Elliot, McGregor, and Gable, 1999), and to continue engaging with science after school (Fortus and Vedder-Weiss, 2014).
Self-determination theory, developed by Deci and Ryan, explores intrinsic and extrinsic motivational factors (Deci, Koestner, and Ryan, 1999). Intrinsic motivation is when a learner performs a particular activity for personal rewards, whereas extrinsic motivation is when a learner performs an activity to earn a reward or avoid a punishment. The relationship between intrinsic and extrinsic motivation with respect to learning is described in the next section. A major approach to interventions aimed at improving intrinsic motivation is to attempt to increase a student’s sense of value or
connection to science and engineering. Improving student’s perceptions of what real science and engineering jobs are like has been linked with increases in the learner’s value for the content being learned. Role models for learners can help inspire them to engage and achieve in science and engineering disciplines, and see themselves in these roles (Stout et al., 2011). Through a direct value intervention, Harackiewicz and colleagues (2012) used brochure mailings and a website to support parents’ belief in the usefulness of taking high school science courses and to guide parents in talking to their children about the utility of math and science. Learners in this intervention demonstrated increased enrollment in high school science courses and increases in utility value of science courses if their mother’s perception of utility value also increased. A follow-up study found that these same learners had higher math and science ACT scores and greater pursuit of STEM careers (Rozek et al., 2017).
Overall, it is important to provide opportunities for learners to challenge their own perceptions about science learning, which could lead to increased interest and motivation to learn; however, it should be acknowledged that these efforts may not be sufficient to overcome systemic institutional barriers such as racial and gender biases or inadequately resourced and supported learning experiences.
Intrinsic and Extrinsic Factors Influencing Interest and Motivation
The quality of learning during science investigation and engineering design is dependent, in part, on the student’s interest and motivation to engage during the investigation (Blumenfeld, Kempler, and Krajcik, 2006). When learners are intrinsically motivated, they want to engage in an investigation because it is viewed as interesting and enjoyable. Learners are more intrinsically motivated when there is the perception of a high degree of autonomy rather than being externally controlled (Deci and Ryan, 2000). Moreover, as these learners willingly engage in investigation, they are more likely to perceive the challenges as within their abilities. On the other hand, external rewards may undermine the learner’s perceptions of autonomy and control, decreasing intrinsic motivation and interest (Deci and Ryan, 1985). However, teaching strategies that use rewards to stimulate interest in a topic may provide learners with the encouragement needed to develop feelings of autonomy, competence, and academic achievement (Vansteenkist et al., 2004).
In education, the use of extrinsic motivation is still under debate (Linnenbrink-Garcia and Patall, 2016). Extrinsic motivation was once thought to be detrimental to long-term student motivation and have lasting negative consequences for learning, because it was thought to undermine intrinsic motivation (e.g., Deci, Koestner, and Ryan, 1999). However,
research has suggested that extrinsic motivators such as rewards and grades may actually have important benefits to promote motivation, because they may be necessary to motivate learners who have less interest (Hidi and Harackiewicz, 2000). As such, intrinsic and extrinsic motivational factors can exist simultaneously, and their intersection can be beneficial for motivation and learning (Harackiewicz et al., 2002). For example, learners may attempt to pursue learning content material deeply to master course content and grow their knowledge of the subject (i.e., are intrinsically motivated) and simultaneously attempt to maximize their course grade (i.e., are extrinsically motivated) during learning in academic coursework.
Design Features to Promote Interest and Motivation through Science Investigation and Engineering Design
Classrooms can be structured to make particular goals more or less salient and can shift or reinforce learners’ interests (Maehr and Midgley, 1996). Research in interest development has proposed several methods of maintaining and increasing interest that can be used to promote quality and sustained engagement in science investigation and engineering design (Nieswandt and Horowitz, 2015). In particular, the design principles include (1) providing choice or autonomy in learning, (2) promoting personal relevance, (3) presenting appropriately challenging material, and (4) situating the investigations in socially and culturally appropriate contexts.
Providing Choice or Autonomy
The first design principle focuses on providing choice or autonomy. Research on interest development suggests that allowing learners some autonomy to choose the direction or content of their learning (Patall, Cooper, and Wynn, 2010), particularly in science and engineering (Nieswandt and Horowitz, 2015), and having options that relate to one’s interests (Azevedo, 2013; Walkington, 2013) can benefit interest development and learning. When learners are given the opportunity to make choices about their learning, they may gain a sense of competence, which may foster interest and motivation (Patall, Sylvester, and Han, 2014). However, too much choice, particularly with lack of knowledge about those choices, can have negative consequences that can lead to random choice or being overwhelmed (Katz and Assor, 2007). Overall, allowing learners to experience phenomena or challenges and then brainstorm related questions they can explore is an important aspect of providing choice. Teachers need to be mindful to structure the learning environments to scaffold the selection of choices and provide ones that connect to a variety of other possible student interests outside of the content being learned (see Chapter 5).
Promoting Personal Relevance
The second design principle involves tailoring science investigation and engineering design work to be relevant to the student and is important for engagement and learning (Järvelä and Renninger, 2014). One way that this can be accomplished is by situating the phenomena within the learner’s local context (see the place-based learning discussion below). Alternatively, as described above, the student could be offered some choice about the topic so that he or she may choose a topic of inherent interest. To help learners see or make personal connections during an investigation, teachers can ask learners to describe how the work they are doing in the science and/or engineering class is related to their lives. For example, Hulleman and Harackiewicz (2009) found that when learners self-describe the personal relevance of learning tasks, it can lead to improvements in interest and achievement as it allowed the learners to sense the value or make a connection between science and engineering and their own lives.
Funds of knowledge are broadly defined as the historically accumulated and culturally developed bodies of knowledge and skills essential for household or individual well-being (Gonzales, Moll, and Amanti, 2005). The concept of funds of knowledge emerged out of the qualitative work of teacher-researcher collaborations with families of students living on the United States-Mexico border; they are the valuable understandings, skills, and tools that students maintain as a part of their identity (Moll et al., 1992). Incorporating learners’ funds of knowledge can increase their understanding of science and engineering concepts and increase their motivation. For example, Kellogg and colleagues (2016) examined the role of participatory bioexploration assays for American Indian and Alaska Native learners using medicinal plant knowledge as an entry point to support student engagement. Through the use of observational monitoring,4 the study found that the integration of learners’ cultural knowledge increased engagement during classroom discussions as well as during investigation and design activities.
Project-based learning (Krajcik and Shin, 2014), with its focus on engaging learners in finding solutions to questions anchored in phenomena that they find meaningful and opportunities to ask and explore questions, also provides this relevance. For example, Hoffman and Hausler (1998) found that situating a physics-related problem—the working of a pump—into a
4 The STROBE method was used to measure in-class student engagement. That is, visible behaviors, such as looking at the instructor, writing, reading classroom content, or performing experiments were quantified and measured. The percentage of time that students exhibited disengaged (actively off task–talking or passively off task–sleeping) and engaged (listening/watching/speaking, writing or reading, and hands-on activity) behaviors was calculated across the activity period (Kellogg et al., 2016).
real-world context—the type of pump used in heart surgery—resulted in significantly more interest for high school girls. Place-based learning (Sobel, 2005), often used in environmental education, offers another approach to increase personal relevance as the focus is on challenges and phenomena that exist in the local community. Learners are more likely to make personal connections and see science and engineering as more relevant to their lives by working on challenges with which they can directly identify. For learners from communities traditionally underrepresented in the sciences and engineering (low-income learners from urban and rural contexts, girls, and certain racial and ethnic groups), place-based education has the added potential to help learners see the relevance of science and engineering concepts in their daily lives and communities (Clark, Fuesting, and Diekman, 2016; Endreny, 2010).
Presenting Appropriately Challenging Material
The third set of design principles is based on creating lessons and tasks that are appropriately challenging for learners. Optimal difficulty and complexity of a task can lead to long-term individual interest development (Nieswandt and Horowitz, 2015). There is variability in the success of learners in challenging situations with some learners thriving (Renninger and Su, 2012) and others lacking perseverance (Sansone, Thoman, and Fraughton, 2015). For learners faced with an environment that is more challenging than they are comfortable with, it may be beneficial to provide some scaffolding to the investigation. Teachers can help the learner by highlighting the potential personal relevance to the learner, include more incremental steps to help the learner feel more comfortable and interested in the investigation, and provide feedback that conveys appreciation for the difficulty of the problem for the learner. These ideas are further expanded in Chapters 4, 5, and 6.
Socially and Culturally Situated Learning
The last design principle concerns socially and culturally situated learning. There has been an increase in the use of situated and sociocultural approaches with the intent to foster interest and motivation (Azevedo, 2013). To positively influence motivation, STEM lessons must be sensitive to the cultural and personal backgrounds of learners and leverage the power of social engagement to enhance interest development. Curriculum designed in this way can facilitate retention and reactivation of the learned content and develop interest (Häussler and Hoffman, 2002; see also Chapter 6).
Another method of utilizing socially or culturally situated learning is to design lessons to deliberately emphasize social and cultural connectedness.
Social connections support interest and learning in content by providing a shared experience and excitement for the work, access to information, and ideas about how and what to pursue next (Bergin, 2016). As noted in the discussion on the importance of context in learning earlier in this chapter, cultural connectedness enhances what is familiar to the learner. Cultural connectedness also affirms aspects of learners’ identities by conveying the value of their backgrounds and experiences, as demonstrated in Dee and Prenner’s (2017) research on cultural relevance by way of high school ethnic studies curriculum.
These social and cultural connections aid in internalizing values for the content (Deci and Ryan, 1991) through finding shared purpose, focus, and values (Rogoff, 1998). Promoting social and cultural connectedness can be achieved by creating investigations that make explicit connections between school-based learning and the real worlds that the learners live in (Pressick-Kilbourn, 2015), and intentionally pointing out the importance of these connections. It is important that the attempt to make these connections is culturally appropriate, authentic, and related to the real lives of the learners.
Students from Underrepresented Populations
Within the broad field of science education, as articulated in Chapter 2, a growing body of work draws attention to issues of equity. Chapter 2 highlights that there have been a number of systemic institutional barriers that have limited the opportunities that members of traditionally underrepresented groups have in science. The limit in opportunities may influence whether or not the learner might have eventually developed an interest in science and engineering topics. Girls, learners from backgrounds traditionally underrepresented in the sciences and engineering, English learners, and learners with physical and cognitive disabilities could benefit from instructional practices that encourage their participation in investigation and design that, in turn, have the potential to spark and strengthen their interests in pursuing science-related and/or engineering education at various levels. Many of the strategies just described have been successfully implemented to improve interest, motivation, and learning for students from these underrepresented groups (Alexakos, Jones, and Rodriguez, 2011; Calabrese Barton and Tan, 2018).
Learners’ identities in science and engineering are shaped by their opportunities to engage meaningfully in science and engineering knowledge and practice, to be able to use that knowledge in combination with other forms of salient knowledge to take action on issues they care about, and to be recognized for their efforts by their teachers and other learners.
However, when any of these three components of identity work5 are disrupted or limited, learners’ identity work suffers (Calabrese Barton et al., 2013). For example, in a study that examined girls from grades 6–8, it was found that those learners who lost interest in STEM had limited opportunities to exercise agency in science or to be recognized for their efforts to do so (Tan et al., 2013).
Longitudinal and multisited ethnographic studies and design-based research document how youth from underrepresented backgrounds participate in and develop science identities over time (grades 6–9) and place (home, afterschool, school; Jiang et al., 2018; Tan et al., 2013). Having opportunities to create identities as “community science experts” (people who have deep knowledge of community and STEM and can merge them toward solving science-related problems) is one form of identity work that has been shown to support youth from historically underrepresented backgrounds in increasing their STEM knowledge and practice and in increasing their agency in STEM (Birmingham and Calabrese Barton, 2014; Calabrese Barton and Tan, 2010). That is, students walk away thinking “I can solve this problem collaboratively right here in my community, right now using what I know.” Work by Calabrese Barton and Tan (Calabrese Barton and Tan, 2018) also shows that when youth are supported in taking up STEM practices in ways that reflect deep and critical knowledge of the needs communities face, they persist in STEM learning toward more robust STEM/engineering designs.
An additional factor to be addressed for those groups traditionally underrepresented in science and engineering are persistent gendered and racial stereotypes in these fields (Buck et al., 2008; Museus et al., 2011). One method of attacking the common stereotypical image of white males in science and engineering fields is to provide role models. Researchers have found that rather than simply matching student demographics, presenting science and engineering as disciplines made of a multitude of real and diverse people is effective in developing interest and motivation in these fields (Cheryan et al., 2011). In a study of role models for girls, Buck et al. (2008) reported that learners want both male and female role models from a variety of racial backgrounds with whom they can make personal and real connections, rather than one who is “perfect.” Betz and Sekaquaptewa (2012) found that presenting overtly feminine STEM role models had a negative effect on promoting interest in science and math for girls with lower interest. Moore (2006) also pointed out that there is an important part for
5Calabrese Barton and colleagues (2013) define identity work as “the actions that individuals take and the relationships they form (and the resources they leverage to do so) at any given moment and as constrained by the historically, culturally, and socially legitimized norms, rules, and expectations that operate within the spaces in which such work takes place” (p. 38).
family role models to play in developing interest in STEM areas as they can play a critical role in the career decision process (e.g., the role model can articulate the struggles, provide assistance, and support during learning). By providing role models, students’ eyes are open to the possibility that they can become involved in science and engineering themselves. This can aid learners in seeing congruence between their content-based identity as a doer of science and engineering, and other identities such as gender and race.
However, larger societal and institutional issues related to inequities and biases (such as those discussed in Chapter 2) play a key role in underrepresented student motivation that create external barriers for these learners, and these external barriers must be addressed. (For a comprehensive review of this issue, see DeCuir-Gunby and Schutz, 2016.) For underrepresented students, persistence in science and engineering learning requires “substantial financial resources, as well as ongoing social and educational support, to make the transition from interest in engineering to a college major and a career in an engineering field” (Bystydzienski, Eisenhart, and Bruning, 2015, p. 94). In relation to in-the-moment classroom learning, adding social supports may be one area classroom educators can focus on to remove external barriers to success for underrepresented students. Teachers, as well as parents and peers, can resist setting lowered expectations and offer encouragement to engage in science and engineering learning as social supports for underrepresented students (Yu, Corkin, and Martin, 2016). Classroom environments must also actively pursue positive inter-group relations, where all individuals are given equal status, support from authority, and a voice in creating common goals (Kumar, Karabenick, and Warnke, 2017).
The Framework and the resulting Next Generation Science Standards and state standards provide a rigorous set of standards and expectations for all learners in grades K–12. Learners are expected to use their knowledge to solve problems and make sense of phenomena by using disciplinary core ideas, crosscutting concepts, and science and engineering practices. The science education community can use what is known about student learning and motivation to inform efforts, while also conducting further research to expand understanding of learning and motivation.
Learning and motivation work together to promote usable knowledge in learners. There is a wealth of theoretical models describing how to develop and maintain interest and motivation in science and engineering and how this increased motivation is linked to increased learning and achievement. It is known how to characterize the goals of learners and aspects of the learning environment that can be harnessed to promote the formation
of usable knowledge. While empirical classroom-based research is lacking that compares motivational interventions to control conditions that could be used to change STEM education, there is some evidence to suggest that interventions designed to address intrinsic motivation in science and engineering are effective (Deci, Koestner, and Ryan, 1999).
Several design guidelines from interest development research can be integrated into science and engineering learning environments to effectively increase learning during investigation and design activities. These guidelines include (1) providing choice or autonomy in learning, (2) promoting personal relevance, (3) presenting appropriately challenging material, and (4) situating the investigations in socially and culturally appropriate contexts. They can be a useful starting point for researchers to evaluate the effectiveness of specific instructional innovations, but also speak to teachers and designers about how to design effective learning environments. Motivation-based interventions offer a path to improve the representation of women, people of color, and other underrepresented groups in science and engineering. Additional information could be gained from longitudinal studies and theoretical frameworks sensitive to examining factors—ones internal to individuals as highlighted by a cognitive perspective on learning and ones external to individuals centralized in a sociocultural view of learning—that influence participation and persistence of underrepresented groups in science and engineering in three-dimensional context.
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