Learning and Embodied Cognition: A Review and Proposal

Abstract

The objective of this review is to investigate research in instructional methods and embodied cognition in order to suggest the idea that a professor’s movement provides information by increasing levels of exogenous embodiment. This review describes how teaching methods varying in human activity lead to different outcomes and how those outcomes may be linked to the presence of an active body providing instruction. The embodied cognition literature suggests the physical actions we perform and the actions being performed around us shape our mental experience. We argue that students mentally imitate the gestures of their professor, this activity contributes to the embodied experience one has in a classroom, and that this increased activity leads to increased recall. One possible reason for increased student learning in human-centered environments is the activation of mirror neurons. Implications for teaching topics in a psychology classroom are discussed.

Introduction

Student learning is the goal of every instructor, no matter his or her teaching methods. While learning is every educator’s goal, the instructional methods used in today’s classrooms vary between human-centered and technology-centered methods. There is evidence that both human-centered and technology-centered methods have benefits. However, student outcomes given these different instructional methods differ. Human-centered learning features benefits such as active engagement and increased quality of learning (Craig & Amernic, 2006). Research in human-centered methods attributes increased performance in traditional classrooms to active learning, better concentration, communicative gestures, and decreased cognitive load (Craig & Amernic, 2006).

Multimedia learning, or learning from digital words and pictures, combines visual and auditory information in order to reduce the cognitive load required to process each separately (Mayer, 2009). Multimedia learning’s cognitive theory suggests that certain principles are designed to support cognitive function and lead to meaningful learning. The signaling principle of multimedia learning, including pointing or highlighting, states that learning is better when audio or visual cues direct students’ attention toward the most germane information (Mayer & Fiorella, 2014). Multimedia classrooms have the benefit of being accessible, and disseminating information is easy (Kiser, 1999). Evidence for better outcomes in the technology-centered classroom includes many of the same features cited as benefits in human-centered environments. The emerging problem in this research is the absence of a comprehensive explanation for why students perform differently given different instructional methods.

A solution to this problem may lie in the theory of embodied cognition. Embodied cognition involves how the body and mind work in tandem to create the human experience. Embodied cognition literature suggests that the physical actions we perform, as well as the actions being performed around us, shape our mental experience (Barsalou, 1999; Lakoff & Johnson, 1999; Niedenthal, 2007). The notion that people around us alter our cognitions has been revealed in literature on mirror neurons, a group of motor neurons that are activated upon watching another person perform some behavior (Fu & Franz, 2014). Embodied cognition theory assumes that thoughts and actions are influenced by sensory experience. As such, the embodiment effects of a given teaching method affect learning (Barsalou, 2008; Wilson, 2003). The purpose of this review is to integrate the literature on instructional methods and the research on embodied cognition in order to argue for an understanding of an instructor’s movement as representational gesture. We argue that as instructor movement and use of representational gesture increases in a learning environment, embodiment increases, perhaps due to neural activity involved in imitation, and leads to improved student outcomes.

Instructional Methods

The first focus of this review is to provide information about the kinds of methods being used in education and discussing their efficacy. Chronbach and Snow (1977) suggest that the most promising approach to understanding learning is to hold the fundamental assumption that learning is influenced by instructional methods. Learners, when unable to generate examples of concepts for themselves, rely on adequate instructional methods to provide those examples (Dunlosky, Rawson, Marsh, Nathan, & Willingham, 2013). Competing theories in human-focused instruction and technology-focused instruction suggest that the method of presentation directly and substantially influences students’ accumulation and retention of knowledge. Therefore, the method of providing examples should be critically examined. While the format for providing course content has changed from technology-assisted to technology-driven (Bichsel, 2013; Staley & Trinkle, 2011), outcomes in these environments depend more on the methods used to teach concepts than on the environments themselves. For that reason, the methods used to provide instruction are the focus of the current review of teaching pedagogy.

Human-centered methods

Human-centered teaching methods traditionally involve a person providing content while physically present with students in the classroom. Material is written by hand on a board and verbally reinforced. Students are focused on the instructor, whether they are speaking, writing information on the board, or pacing the room gesturing. These traditional, human-centered methods are referred to as “chalk talks” because technology is not an integral part of the information dissemination (Pitt & Orlander, 2017). The concept of active learning is most often studied in these traditional environments and entails getting students involved in the lecture by completing activities or participating in discussion (Chi & Wylie, 2014; Prince, 2004). These actions are simpler in a context where people are assembled in a room and given a physical presence to model. The instructor has the ability to change class dynamics with the movements they make as part of an active learning environment.

One of the largest benefits of human presentation-focused learning is the connection between students and the source of instruction. Prior research on human presentation concerns the effects of orienting toward the instructor. Bligh (2000) showed that visual illustrations, unlike purely verbal lectures, have an arousing effect. This effect suggests that students need to experience some visual stimulation in order to actively learn. Similarly, humans also have a visual reflex to orient toward movement, so hand movements can draw a student’s attention toward the lecturer (Bligh, 2000). When students watch the instructor write words on the board or gesture to explain math concepts, they orient toward that movement and therefore focus attentional resources on the information presented.

There is tentative evidence for this effect of instructor gestures providing representative information, in which passive observers watching another person physically present diagrams had better memory than when the items were presented automatically on a screen (Fiorella & Mayer, 2016). Sullivan and Christman (2015) also found evidence for exogenous embodied effects with hand gestures, using purely verbal information. Those in the embodied condition, who watched the researcher write words on the board, performed significantly better on an implicit recall task and equally as well on an explicit memory task than both control conditions. Especially surprising is the fact that participants in the control condition had 10 seconds of study time, whereas those in the quasi-control and embodied conditions only had about three seconds of study time and still performed better than the control group. The effects of embodiment in the condition where the professor provides representational information through their gestures surpass the effects of extra study time in the control condition. These findings may reflect in part the fact that the gestures can help form more elaborative memories (Chao, Huang, Fang, & Chen, 2013), and add to the literature suggesting the educational limitations of PowerPoint-type presentation of lecture material.

Gesture in Human-Centered Teaching

A human-centered traditional learning environment has heavily focused on gestures and imitation. De Nooijer, Van Gog, Paas, and Zwann (2013) argue that gestures have communicative and cognitive functions. Therefore, observation of these gestures should lead to increased learning, specifically of the information being presented. Their research also finds support for the notion that imitation increases word learning (De Nooijer et al., 2013). Gesturing allows a learner’s representation of a problem to be grounded in perceptual and motor information, thus making information readily available when solving a problem (Goldin-Meadow & Alibali, 2013). When learning properties of centripetal force, students who learned in a “high-embodiment” situation where they swung an object overhead had better generative knowledge on a follow-up test one week after study than students in a “low-embodiment” situation where they merely clicked a mouse to spin the object (Johnson-Glenberg, Megowan-Romanowicz, Birchfield, & Savio-Ramos, 2016).

Students watching an instructor write are not experiencing the same embodied effects as students who are actively manipulating objects as a part of their learning. However, embodiment is not an all-or-nothing concept in education; there are degrees of embodiment in educational content (Johnson-Glenberg & Megowan-Romanowicz, 2017). If gestures represent non-verbal information, the experience of watching someone present information such as a lesson on schemas, with an organizational chart or “mind map,” may provide scaffolding information about how to produce examples in the future that the student would not get had they not viewed the instructor write on the board. If students experience better memory when they imitate their instructor, they may experience an enhanced imitation effect from viewing the movement of an instructor writing words on a board, even if they do not produce their own gestures (Cook, Tip, & Goldin-Meadow, 2012; Valenzeno et al., 2003).

Consider teaching a lesson about reinforcement to psychology students. Explaining how the beeping of the seatbelt stopping once they put it on provides them with the negative reinforcement needed to put their belt on may be explained verbally. It may also be explained by drawing a car, writing the word beep, writing ‘seatbelt on’, crossing out the word beep, and drawing a smiling person with a belt on. By writing this verbal and visual demonstration on the board, you cause students to involuntarily think about themselves performing that action. In this way, reading and watching someone gesture are also embodied activities, albeit at a low level (Johnson-Glenberg & Megowan-Romanowicz, 2017). According to the taxonomy for embodied learning, this low-level demonstration would be a second- or third-degree level of embodiment; the learner is seated, there is some amount of gestural relevancy, and the environment may or may not be immersive (Johnson-Glenberg, Birchfield, Tolentino, & Koziupa, 2014).

Lessons with gestures are shown to promote deeper reasoning, synthesis, and information retention than lessons that do not feature gestures (Goldin-Meadow & Alibali, 2013). For example, Ping and Goldin-Meadow (2008) gave children a lesson on liquid conservation, either with gestures or without gestures, referring to the height and width of the two glasses. Children who were instructed with gesture did better from pre- to post-test than those instructed without conservation-related gestures. This suggests that instructional gestures support learning by conveying ideas through physical representation even when students do not do any movement themselves (Novack & Goldin-Meadow, 2015). Brooks and Goldin-Meadow (2016) also suggest a “sleeper effect” associated with gestures on the learning system, such that those who see gestures are better able to solve equations when tested later, even if they did not show improvements immediately after being shown the movements. This suggests that gesturing may provide scaffolding for learning in the future (Brooks & Goldin-Meadow, 2016).

Technology-Centered Methods

Technology use in classroom settings has increased considerably in popularity and sophistication in the last 10 years (Bichsel, 2013; Staley & Trinkle, 2011). Ten years ago, classrooms were highly technological if there was a Smart Board or the classroom had one computer. In today’s classroom, Smart Boards are commonplace, texts are offered as eBooks, and testing is often computer-based (Svokos, 2015). Supporters of technology-mediated virtual learning environments believe they eliminate barriers to individualized education, provide flexibility, enhance the opportunity for feedback from instructors, and increase student retention over traditional classrooms (Kiser, 1999). Critically, we do not have data to show if the requirement of participation and the constant contact with technology improves student outcomes over a human-centered learning environment.

Using technology in the classroom has increased overall; however, there are differing levels of technology use depending on the type of learning environment. In a sample of psychology courses from just one university, there are courses with limited technology use in the form of PowerPoint, there are blended courses with online learning components, and there are courses offered completely through digital media online. Each environment, from massive online open courses (MOOCs) to PowerPoint driven courses, provides unique benefits but also unique drawbacks.

Active learning, while most often studied in physical classrooms, has also been studied in MOOC environments. Given that we do not have a wealth of information on which features of online courses best improve student learning, active learning research on the MOOC platform focuses on factors (such as videos, interactive activities, and course readings) that contribute to increased learning (Koedinger, Mclaughlin, Kim, Zhuxin, & Bier, 2015). In an introductory psychology course, Koedinger and colleagues (2015) found that interactive course activities had a larger impact on student outcomes than doing course readings or watching videos. According to the researchers, this effect is due to the active learning features of interactive activities that are not present in passive reading or watching. These data mimic the evidence we have for active learning in the physical classroom. However, this research does not mention how an instructor’s movement might influence the active learning environment, even in a MOOC.

Arguably the most widely used information dissemination tool in the world, PowerPoint is the most common way for professors to present information to students (Parks, 2013). In some cases this multimedia technology has replaced human instruction, as the professor is merely there to read information from PowerPoint slides. Research has shown that multimedia presentation format does not always lead to a widespread performance increase for students in courses using it (Levasseur & Sawyer, 2006); some studies even show that students’ performance decreased when the instructor switched to PowerPoint from more traditional methods (Amare, 2006; Bartlett, Cheng, & Strough, 2000; Szabo & Hastings, 2000). While the majority of students report enjoying PowerPoint, students who receive instruction through PowerPoint slides report an inability to focus and the tendency to be thinking about information other than the lecture content (Bunce et al., 2011). It is not the case that all courses using PowerPoint are detrimental to student outcomes, but there is evidence that when just PowerPoint presentations are used with no board work, compared to an integrated, human-centered approach, student learning suffers (Bunce, Flens, & Neiles, 2011).

Embodied Cognition

The second focus of this review is to describe the conditions under which embodied cognition influences the human experience, with a specific focus on the experience of a student in the classroom. Embodied cognition marks a shift away from traditional cognitive science, which views the mind as a computer. Standard cognitive scientists view cognitive processes as computational; symbolic inputs produce symbolically encoded outputs (Shapiro, 2011). In this traditional view, senses exist independent of perceptions and actions. In what is considered the primary text on embodied cognition, Varela, Thompson, and Rosch (1991) defined this new theory of cognition as “embodied action” (p. 172). Embodied, by their account, means that cognition depends on the sensorimotor capacities of the human body and these sensorimotor capacities are “embedded in a more encompassing biological, psychological, and cultural context” (p. 173). Therefore, sensory and motor processes are one, inseparable entity in cognition and they are organism dependent. An organism on all fours and an organism standing vertically experience differences in the information their sense organs provide merely because of location (Shapiro, 2011). This difference in perception limits each organism in the actions they would perform based on what sensory information is available to them at the time of action.

Pioneer of embodied cognition theory Esther Thelen also challenged the traditional view of cognitive science. Thelen, Schoner, Scheier, and Smith (2001) see embodied cognition as cognition

…that arises from bodily interactions with the world… cognition depends on the kinds of experiences that come from having a body with particular perceptual and motor capabilities that are inseparably linked and that together form the matrix within which reasoning, memory, emotion, language, and all other aspects of mental life are meshed. (p. 1)

According to Thelen et al. (2001), traditional cognitive science sees the mind as computational, and embodied cognition is concerned with how perceptual symbols represent the real world. As Clark (2008) suggests, embodied cognition intends to mark the shift from the body as housing for the brain to the body as the brain’s partner in cognition. The body determines what sensory information is necessary for a perceptual experience and structures that information. The brain and body work in tandem to produce cognition that would not result from one process alone (Shapiro, 2011).

The core of the current research is aimed at understanding embodiment and conditions in which it alters outcomes. By definition, “embodied cognition pertains to the consequences on thought and emotion of living with our particular human sensory and motor systems” (Davis & Markman, 2012, p. 685). Since humans think in the context of their relationship with the environment, the level of embodiment a student experiences in an academic setting should heavily influence learning. We argue that one can experience embodied effects by watching a presenter move their body through space and internally mimicking that movement mentally, even in cases where the presenter is not in the room with the student.

Embodied Cognition in Education

The purpose of this review is to discuss the research that pertains to embodiment in the classroom. As such, it is important to discuss how embodied cognition has been examined within the context of education. Much of the research in education neuroscience does not include the body in the investigation of connections between cognition and educational theory (Osgood-Campbell, 2015). Learning is sometimes seen solely as a mental activity instead of an activity that recruits the mind and body. One notable exception to this philosophy is the work and teachings of Maria Montessori. Montessori asserts that students must actively experience their environments in order to learn. Words are not enough to spark mental development, as students depend on movement to develop cognitively (Montessori, 1988).

In the growing research on embodied cognition and learning, researchers have found positive effects of movement on learning outcomes in math, science, and language. One such investigation by Alibali and Nathan (2012) found that mathematical concepts are embodied because of the gestures teachers and students use to explain these concepts. Glenberg (2011) developed a program called “Moved by Reading” in order to investigate this effect. Glenberg (2011) found that when students manipulated toys as they read, they remembered significantly more about the stories and their comprehension was better than students who merely read the text. Despite the traditional view of learning as strictly mental, evidence like this suggests that the sensorimotor system is integrated with learning at many levels.

Further evidence from research on physics education suggests that not only should instruction be more embodied, but the level of embodied sensitivity in assessment is also important in understanding learning outcomes. In an experiment designed to measure learning gains in an electric field lesson, Johnson-Glenberg and Megowan-Romanowicz (2017) found that college students learned more from the electric field lesson when embodied simulations were included. The researchers manipulated the level of embodiment by giving participants the opportunity to watch a video about the described concepts or interact with the concepts via Kinect sensors. When the low- and high-embodied groups were tested, the method used to test them (either a traditional keyboard-based test or a more embodied Wacom tablet measurement) yielded a significant difference in learning, with the more embodied measurement yielding better performance for the high-embodied groups (Johnson-Glenberg & Megowan-Romanowicz, 2017). Additionally, those in the embodied conditions rated the tasks performed as more engaging and worth the effort they put into learning the lesson. This may be an important consideration for instructors who are looking to keep their students engaged in course content. For example, in Statistics and Research Methods in Psychology, instructors should provide opportunities for students to interact with data via manipulatives or by investing in technologies that capture body movement, such as emerging virtual reality technologies, when covering descriptive statistics, instead of creating a PowerPoint with the math already done step by step.

Empirical research about embodied cognition and learning primarily focuses on how increasing student motor involvement in a lesson increases student outcomes. One example of this empirical research is a paper by Smith, King, and Hoyte (2014) where the researchers examined how forming angles with one’s arms impacted children’s understanding of different types of angles. The researchers hypothesized that acting out angle concepts would provide opportunities for students to connect mathematics concepts to physical movements (Smith et al., 2014). There was a significant increase in angle understanding and drawing post-test compared to pre-test, suggesting that students improved their understanding of angles by grounding their knowledge in their motor experience (Smith et al., 2014). Other mathematic concepts also show some connection to embodiment. A concrete link between numerosity and embodied cognition is the existence and persistence of finger counting. Counting on one’s fingers involves integrating math concepts and sensorimotor action and, while the practice begins as an aid to children, it persists into adulthood because of the sensorimotor associations created for numbers under 10 (Bahnmueller, Dresler, Ehlis, Cress, & Nuerk, 2014).

Purposely involving one’s body in learning with the intent to remember information demonstrates how embodiment can affect memory. Understanding that the mind and body together create one’s experiences, Scott, Harris, and Rothe (2001) randomly assigned students to reading only, writing, independent discussion, collaborative discussion, or improvisation conditions. Participants read a monologue for 5 minutes and were told to look for main character traits. Each group then did the task associated with their group, with the improvisation group performing reenactments. The group who performed improv was the only group who involved their bodies in the recall of ideas. Accordingly, the improv group showed significantly better gist and verbatim memory than all the other groups, who did not differ from each other (Scott et al., 2001). The researchers hypothesized that students who acted out the monologue would remember more information about the main character and plot, and their results support that hypothesis. These results are consistent with the self-performed task effect (Englekamp, Zimmer, Mohr, & Sellen, 1994). According to Englekamp and colleagues (1994), there is information encoded when performing a task that is not encoded in a verbal task. When testing the encoded information, those who have engaged in task performance have motor information available to them that enhances their recognition. In the psychology classroom, this could be implemented in a demonstration of change blindness where students act out a scene in which people or characteristics change and other students try to spot the changes. Students will remember more about the definition of change blindness and about how it directly affected them in the past. This relates to the theory of embodied cognition, which can be used to explain memory differences for those who purposely involve their bodies in learning.

Embodied Cognition in Psychology

Applied psychological research on motor fluency, language, and social interaction, among other topics, has incorporated embodied cognition theory. Research in motor fluency incorporates the reported findings in mirror neuron literature and explains familiarity through embodied cognition. Longcamp, Anton, Roth, and Velay (2003) found that the presentation of letters activates premotor areas in the brain that are involved in writing (Exner’s area), even though the individuals in their experiments were aware they would not be doing any writing. This activation of mirror neurons in the left premotor cortex may give students the feeling of familiarity with a word, and therefore help them remember it in a recognition task (Longcamp et al., 2003). Yang, Gallo, and Beilock (2009) suggested that familiar, or well-learned, action-perception associations have a substantial impact on cognitive processes such as memory. According to embodiment theory, encountering a stimulus causes the motor or sensory systems associated with the stimulus to be triggered automatically (Topolinski, 2012).

Sakreida et al.’s (2013) work on the topic of reading’s influence on the sensorimotor neural network yielded similar results. Participants were given graspable nouns (e.g., ball), non-graspable nouns (e.g., hope), motor verbs (e.g., kick), and non-motor verbs (e.g., marvel) and were instructed to press a button while in the fMRI if the sentence they read referred to an action performed by the foot or leg (e.g., to kick a ball) (Sakreida et al., 2013). Their results indicated that the sensorimotor neural network is active during simulation as well as when executing an action. Concrete multi-word phrases revealed activation in more sensorimotor neural regions, while abstract multi-word processing activates areas involved in linguistic activity (Sakreida et al., 2013). Evidence shows that language, even when unrelated to a specific action, can activate motor neural networks, as is the case with embodied cognition.

Embodied cognition is often studied within the context of social psychology because the nature of social beings is to relate to others by having some understanding of their thoughts and emotions through empathy (Chaminade & Cheng, 2009). During social interactions, humans can directly perceive others’ mental states through perception of their embodied intentionality (Gangopadhyay & Schilbach, 2012). Further, during interaction, the body presents information to the perceiver that conveys certain types of social interaction (Wiltshire et al., 2015). Social cognition contributes to this understanding by providing the means to identify basic cognitive mechanisms that serve to solve challenges of social interaction, which our bodies are equipped to efficiently detect (Kaschak, Maner, Miller, & Coyle, 2009). The understanding of the world that arises as a product of having a body and mind that work inseparably to create an experience allows one to conceptualize how another body and mind might react in a given situation.

Tversky and Hard (2009) were interested in how people’s perspective changed based on photographs they viewed either having a person performing an action or the photograph having no person or action. If there was no person in the scene, the accompanying sentence asked, “in relation to the bottle, where is the book?”, and if there was a person in the scene, the sentence asked, “in relation to the bottle, where is his book?” (Tversky & Hard, 2009). Which photograph the participants viewed affected the frequency with which they took the other person’s perspective. When the photograph included a person, participants were significantly more likely to take the other person’s perspective than if there was no person in the photograph. When the sentences referred to the person in the photograph taking action, the participants were significantly more likely to take the other person’s perspective than if the sentence mentioned the person but did not mention his actions (Tversky & Hard, 2009). The researchers concluded that social interactions depend on one’s response to the actions, verbal or physical, and the perspectives of others. Further, Tversky and Hard (2009) suggested that embodied cognition enables disembodied thought; people overcame their own embodied perspective in order to take the perspective of the person in the photograph.

Across the lifespan, conceptual representations are continuously composed of new perceptual and motor experiences, and the development of language from childhood into adulthood is influenced by a child’s experience in their environment (Borghi & Cimatti, 2010; Thelen, 2008; Wellsby & Pexman, 2014). Kontra, Goldin-Meadow, and Beilock (2012) proposed that embodied cognition may provide a deeper understanding of the mechanisms of early childhood development as being action driven. By examining sensorimotor information as vitally important in children’s linguistic and conceptual understanding, and determining if and when children shift away from a reliance on this sensorimotor knowledge as their cognitions become more abstract and complex, developmental research could help advance theories of embodied cognition generally for the future (Wellesby & Pexman, 2014).

Mirror System Hypothesis

The third purpose of this review is to suggest one possible reason for the favorable learning outcomes seen in embodied education as mirror neurons. Mirroring another’s behavior is at the core of what it means to be human. Although controversial, we believe that imitation, perhaps driven by mirror neuron activity, influences the embodied experience of humans. Originally identified in primates, the mirror neuron system (MNS) represents a neurophysiological circuit distributed across the premotor cortex that selectively activates when either conducting a specific action, or when observing another individual performing the same action (di Pellegrino, Fadiga, Fogassi, Gallese, & Rizzolatti, 1992). What distinguishes mirror neurons from other sensory or motor neurons is the fact that their activity depends on both action execution and action observation with some degree of specificity for the type of action (Kilner & Lemon, 2013).

Extending into human neuroscience, the Mirror System Hypothesis (MSH) developed because hominid evolution yielded a species whose brain combined imitation and action recognition in a way that allowed the species to approximate performance (Arbib, Gasser, & Barres, 2014). According to Arbib and colleagues (2014), once humans realized imitation was effective for social communication, they began mimicking the gesture, and eventually language, of others. According to the MSH, our goal in communication is to gain insight into the internal world of others. Therefore, language must be embodied in the sense that our understanding and use of words is acquired by awakening the feelings of our own experiences (Jeannerod, 2005). The mirror neuron network allows us to understand others by “internally replicating them” (Arbib et al., 2014, p. 62). This idea of internal replication speaks to the experience humans have as we integrate our bodily experience with our mental operations—often gaining additional information about ideas and materials through someone else.

The current review is concerned with human mirror systems research in action observation and action performance because of its relation to learning and embodied cognition through the broader concept of imitation. Effects of action observation have been seen in primates as well as humans, such that observing an action being performed recruits mental representations that are also involved in performing that action (Barchiesi & Cattaneo, 2015). The actions described in most mirror system research are simple and direct, unlike the movement that occurs in a classroom.

Imitable stimuli are encoded in terms of articulatory gestures, which depend on understanding the human body and how it moves (Wilson, 2001). This isomorphism allows for the observer to mentally process actions and facilitates the execution of motoric actions. The automaticity of imitation allows humans to engage in social learning, a process that is essential for developing language, for understanding the meaning of extra-linguistic information, and for developing a sense of one’s culture (Wilson, 2001). Imitation allows us to use the perspective of others as perspective for ourselves, no matter how simple the action.

The message we deliver to students often contains information that is not conveyed in our speech, but rather in our gestures (Church & Goldin-Meadow, 1986; Goldin-Meadow, 2003). Students are able to then use the information from our gestures to understand and use this information later, without awareness of the source of their knowledge (Goldin-Meadow & Sandhofer, 1999). Ping, Goldin-Meadow, and Beilock (2014) measured how listeners use information from gestures in their mental models of the speaker’s message. Participants heard a sentence that referred to hammering a nail into wood and either saw a congruent gesture (nailing something horizontally), or an incongruent gesture (nailing something vertically) (Ping et al., 2014; Zwaan, Stanfield, & Yaxley, 2002). The researchers found that when the gesture matched the pictures participants saw, participants were quick to respond to the picture from the sentence; information from the gesture was incorporated into the mental model participants had of the speaker’s message (Ping et al., 2014). The researchers suggest that the listener’s motor system is involved in recreating a mental simulation but do not offer a specific explanation for what the mechanism may be. Because the research on the neural underpinnings of premotor activity is limited in humans, behavioral data that suggests such activity does exist is crucial for the current argument and the field needs more of it.

Another piece of research on the motor system’s involvement in mental simulations has shown that face-to-face presentation of information seemingly activates the motor system less than over-the-shoulder perspectives (Jackson, Meltzoff, & Decety, 2006). In order to determine if the viewer’s perspective of a knot-tying demonstration would influence premotor activation and subsequent performance in a knot-tying exercise, Garland and Sanchez (2013) recruited undergraduates to study instructional media about knot-tying procedures. Participants were placed in either the over-the-shoulder (OTS) or the face-to-face (FTF) condition and were given pictures or an animation of knot-tying procedures. Participants were evaluated on the time they spent trying to recreate the knots, whether they finished in the 2 minute time limit, and how many steps of the knot-tying process they were able to recreate. Garland and Sanchez (2013) found that students in the animation condition performed better than students in the static image condition, but these effects were largest for students in the OTS condition. The researchers suggest that mirror neuron activity is higher in conditions involving a more “egocentric” view of the procedure required to perform an action; however, mirror neuron activity was not directly measured. The way information is presented may affect cognitive appraisals and subsequent performance, and as such, it is notable that watching a teacher write or draw on the board involves an over-the-shoulder, or egocentric, view from a student’s perspective (Garland & Sanchez, 2013). The instructor’s movement is representative of the movement a student will likely need to make in the future and students who view these gestures can envision themselves performing them later. This idea has implications for education and the methods by which we teach students.

Conclusions

The current review links the literature on instructional methods and embodied cognition in order to argue for a new conceptualization of instructor movement as teaching by providing representative gestures. We suggest that as embodiment increases in teaching and learning, information retention increases for students, potentially due to the imitation effects typical of the mirror system hypothesis. The gestures created by the professor represent bodily information that the student can later use to perform motor actions or use to enhance their overall recollection of materials. We argue that gaining information from an outside embodied source is a type of embodied experience, nestled within the current literature on embodied theory, and suggest a potential reason for this as premotor neuron activity that is seemingly taking place as a result of watching someone perform an action. While imitation is not always required in an embodied experience, in cases of learning from others’ movements, neural imitation effects may be important.

The significance of this research extends to all types of education. Understanding the impact instructor movement has on student learning is crucial to implementing changes in education and instruction. Students who are instructed using embodied methods benefit from the experience of watching an instructor navigate problems. Understanding mathematical functions is improved by linking them to natural continuity of motion (Nunez, Edwards, & Matos, 1999). The more we understand about natural body movement through space and how the movement influences our understanding of abstract concepts, the more we can do to improve instruction and learning in every classroom. Embodied cognition and learning research has focused on the active manipulation of objects to increase learning; however, the current research can expand that understanding to more passive forms of learning. This research can provide theoretical backing for implementing human methods in an age of digital content. Realistically, this research may also be able to provide information about how human methods and digital teaching methods can be merged, such as combining virtual reality and gesture or moveable digital content.

Implications

The concept of instructors providing exogenous information about embodiment through gestures has real implications for education, specifically for the teaching of psychology. Psychology does not lend itself easily to embodied explanations in the way that physics or mathematics do. The challenge for instructors is to bring up the level of embodiment of all information dissemination, and in psychology that information is usually verbal. We can teach a concept like the scientific method in research with representative gestures. Writing each step on the board in front of the students and connecting the steps using circular arrows may be subconsciously activating their motor neurons for writing the same cycle in a way that viewing a static diagram of the cycle on a PowerPoint cannot. The primary way humans learn is by seeing someone else do what we would like to accomplish. Physically showing students how to represent the scientific method in a cyclical pattern can only help them when they later imitate that pattern.

Representing information through movement is not typical in psychology courses, but with this information psychology instructors may feel more empowered to incorporate gesture and their own body movement in their lectures. Another realistic application of this idea is from a lecture on memory. The instructor can easily put up a PowerPoint with levels of processing. The PowerPoint may be engaging, but it is not the only way, or even the best way, to explain Craik and Lockhart’s (1972) work. The instructor could write structural processing, phonemic processing, and semantic processing with a flow chart indicating which levels are shallow, which levels are deep, and how short-term and long-term memory relates to the framework. Drawing these concepts in a diagram instead of showing the same diagram pre-drawn on a PowerPoint gives students additional information that they can call upon later when tested about the topic.

The primary focus of this review was how embodiment affects learning and memory. In further experiments, we would like to explore the influence of embodiment from an exogenous source and the corresponding representational gestures on performance measures other than memory, such as comprehension, speed, and affect. Future research in the area would further the understanding we have of how learning occurs and how the learning of psychology can be improved through movement. Additional experiments would help to develop this theory and inform our concept of how others’ actions influence our cognitions and behavior.