Excerpt: The evidence I have reviewed – showing the distributed, visual, and physical nature of mathematical understanding – seems particularly significant when considering that mathematics, for most students, is taught as a series of numbers and abstract concepts. It is probably not surprising that so many students feel that mathematics is inaccessible and uninteresting when they are plunged into a world of abstraction and numbers. Most curriculum standards and published textbooks do not invite visual thinking. Many textbooks provide pictures, but they do not invite students to think visually or to draw their own representations of ideas. When textbook and classroom approaches do encourage visual work, it is usually encouraged as a prelude to the development of abstract ideas rather than a tool for seeing and extending mathematical ideas and strengthening important brain networks.

Excerpt: In summary, the human MNS is thought to help process other people’s actions and intentions, support motor and social imitation, and may contribute to our felt experience of the emotions of others through embodied simulation. This chapter reviewed how MNS regions, along with other neural networks, may contribute to better sensorimotor and socioemotional learning processes. It also supports classroom use of imitation learning, an emphasis on embodied learning strategies, and attention to social and emotional learning.

Excerpt: Sensorimotor experiences shape the structure of conceptual knowledge. Because experience plays such a vital role in developing concept representations, understanding how individual differences in sensorimotor experience contribute to differences in the structure of conceptual knowledge is critical. Autism spectrum disorder is associated with significant differences in sensorimotor experience during development, and in this chapter we have described recent research showing that those differences manifest in differences in how conceptual knowledge is organized. We have also speculated on some approaches to embodied learning that emerge from these recent findings, though a better understanding of the nature of conceptual knowledge differences along the autism spectrum (including how conceptual knowledge is organized) will be critical to tailoring educational interventions for individuals on the autism spectrum. Embodied learning may not be immediately intuitive to individuals on the autism spectrum, but combined with explicit connections to social cues and enriched physical education, children on the autism spectrum may benefit from embodied approaches to learning.

Excerpt: Inthis chapter, we review research on how perceptual and interactive features of manipulatives afford actions and on how those actions connect to target concepts. We acknowledge there are many other factors that may influence the effectiveness of manipulatives, including features of the instruction (e.g., Carbonneau & Marley 2015), children’s prior experience with the manipulatives (e.g., Mayer, 2003), and the ways in which the manipulatives are introduced (Donovan & Alibali, 2021). In this chapter, we focus on characteristics of the manipulatives themselves, specifically the perceptual and interactive features of manipulatives and the affordances, or possibilities for action, they offer. We argue that considering manipulatives in terms of affordances can provide new insights into the varying effectiveness of manipulatives in different contexts. We close by discussing implications for the design of lessons that use manipulatives for math instruction. For the purpose of this chapter, the term “manipulatives” refers to physical objects that can be touched and moved with the hands during problem solving and learning. Some example manipulatives include blocks, chips, Dienes blocks, Geotiles, balance scales, paper clips, popsicle sticks, and beanbags. A growing body of work focuses on computer-based, virtual manipulatives (Moyer-Packenham & Westenskow, 2013; Stull et al., 2013; Suh & Moyer, 2007), which hold promise because technology offers unique affordances for action. However, in this chapter, we focus on manipulatives as objects that can be physically manipulated with the hands. Manipulatives vary along many dimensions, and some of these variations have implications for how learners perceive and interact with the manipulatives. In the following sections, we consider the perceptual and interactive features of manipulatives in turn.

There is growing consensus in science, technology, engineering, and mathematics (STEM) education that the body plays an indispensable role in teaching and learning these disciplines (e.g., Lindgren & Johnson-Glenberg, 2013; Nemirovsky et al., 2014; for a review, see Skulmowski & Rey, 2018). In response, over the last ten years there has been an influx of educational technologies that capitalize on novel human-computer interfaces to deliberately incorporate learners’ bodies into the exploration of STEM phenomena. As these embodied learning technologies enter schools and museums, we still know surprisingly little about how educators can support embodied STEM learning with these designs. Synthesized from our previous studies, we introduce strategies for supporting STEM learning by being responsive to and productively engaging learners’ embodied ideas as they use embodied learning technologies. These strategies include (1) attending to learners’ embodied action and perception, (2) encouraging the multimodal expression of learners’ embodied ideas, (3) repeating and reformulating learners’ multimodally expressed embodied ideas, and (4) co-constructing multimodally expressed embodied ideas with learners. We explore these embodied responsive teaching strategies (Flood et al., 2020) in the context of two embodied learning technologies for mathematics – the Mathematics Imagery Trainer for Proportion and the Mathematics Imagery Trainer for Parabolas – and demonstrate how they give rise to students’ mathematical discoveries.

Excerpt: In this chapter we have reviewed the evidence that individual categories of emotions (that are the basis for perceiving and experiencing discrete emotions) are learned when sensorimotor and bodily affective changes are learned within a situational context and become “linked together” by the application of emotion words. Improving a person’s emotional vocabulary (to increase emotional granularity) is linked to improved emotion perception of others, and improved emotion regulation and increased mental health and well-being in the self. Finally, mindfulness improves these outcomes, most likely by increasing the ability to attend to and describe embodied affective changes (thereby increasing emotional granularity). In fact, burgeoning research suggests that improving emotional granularity might help protect individuals from a wide array of mental health disorders, especially adolescents who are disproportionately affected by certain disorders (e.g., depression, anxiety, eating disorders). Moreover, adolescence is a time when individuals experience rapid growth in the prefrontal cortex and increases in the connections between it and the temporal lobe, which support language acquisition and cognitive representations. Therefore, adolescence might be the perfect time to improve emotional vocabulary to facilitate granularity and ultimately enrich the conceptual structure of emotion categories. Classrooms and school settings should capitalize on teaching emotion vocabulary and mindfulness to individuals to not only improve emotional interactions and regulation but also to improve attention, focus, and cognitive awareness, which all facilitate academic performance.

An essential component of literacy – in both the native language and additional languages – is vocabulary. For example, multiple studies have focused on the influence of vocabulary knowledge on reading outcomes in English and in a variety of other languages (e.g., Lesaux et al., 2007; Snow et al., 1998). In addition, there is a literature on the role of rich vocabulary knowledge and its relation to comprehension (e.g., Proctor et al., 2012). Other studies have focused on the role parents and the social environment have on language development (e.g., Huttenlocher et al., 2010; Hoff, 2006). But how is that vocabulary learned in a formal setting such as a classroom or even in the home? The answer from standard accounts of cognition is usually a variant of repetition of the vocabulary list: read the word, read its definition; read the word, read its definition; read… Can we do better by approaching vocabulary acquisition from the perspective of embodied cognition? We begin this chapter with a brief overview of an embodied theory of language comprehension (for a fuller account, see Kaschak & McGraw, chapter 6 in this volume, or Glenberg & Gallese, 2012). Based on this theory, we offer a few suggestions for how a classroom teacher can enhance vocabulary learning. Finally, the bulk of the chapter comprises a review of several research projects implementing some of these suggestions.

E-approaches to cognition, which have been developed over recent decades, challenge the mainstream representational-cum- computational approach, offering us an alternative understanding of cognition. Yet fundamental differences in philosophical outlook divide the more conservative and radical branches of the E-family. This chapter introduces the core assumptions of E-approaches to cognition and details in which ways E-theorists divide into more conversative and more radical camps. Bracketing questions about how to decide between these options and other challenges to E-approaches, this chapter instead focuses on articulating possible practical outcomes for educators should they come to accept either of these E-approaches to cognition. Taking an imaginative leap, this chapter asks the following question: Assuming one has adopted either a more conservative or more radical E-framework, how would that choice matter to one’s thinking about educational research and practice?

Excerpt: Action has long been known to play a strong role in perceptual development. A large number of studies have shown the importance of action, and specifically self-generated action, in visual perceptual development and many different domains of cognitive development (e.g., Bertenthal & Campos, 1987; Bushnell & Boudreau, 1993; Gibson, 1969; Needham et al., 2002). In childhood, we learn to associate self-generated actions with percepts to construct representations of objects. Active interaction with the world facilitates learning about three-dimensional objects (Deloache, 1989; James & Swain, 2011; Piaget, 1953), depth perception (Richards & Rader, 1981; Wexler & van Boxtel, 2005), various types of spatial processing (Christou & Bülthoff, 1999; Held & Hein, 1963; Wohlschläger & Wohlschläger, 1998), eye-hand coordination (Needham et al., 2002), and mathematical concepts (Alibali & Nathan, 2012; Marquardt Donovan & Alibali, chapter 10 in this volume). Visual perception also uses information gained through action – locomotion, handling objects, head movements. Thus, we perceive in order to act, and we act in order to perceive (Gibson, 1979). All these coupled experiences of perception and action sculpt connections among sensorimotor brain systems that support typical cognitive development. For this knowledge to be useful for educators, we must address how active interaction with the environment has specific effects on learning in a school setting. Of the many educational competencies that are positively affected by self-generated action, one that is often not considered is learning to read. In what follows, I will review the importance of letter recognition for learning to read, how learning letters is affected by self-generated action – specifically handwriting – and review how brain imaging can help us understand why handwriting is important for letter learning. For educators, this chapter is intended to provide information regarding how we can improve letter knowledge (and subsequent literacy) through self-generated action, and importantly why handwriting has these positive effects on letter learning.

Excerpt: New and affordable VR systems allow educational designers to include more gesture and body movements into lessons for the classroom. The lack of clear pedagogy in design, including taxonomies for measuring the amount of embodiment for VR educational applications, are considered problems for the field. Therefore, as educational technology rapidly evolves, our design principles and quality rubrics need to keep pace. The QUIVRR rubric was created to help fill these teacher choice and VR designer guideline voids. This chapter presented the two important affordances for VR and a new, applied rubric called QUIVRR, which has been made available to all stakeholders.