Making sense of movement in embodied design for mathematics learning

Abstract

Embodiment perspectives from the cognitive sciences offer a rethinking of the role of sensorimotor activity in human learning, knowing, and reasoning. Educational researchers have been evaluating whether and how these perspectives might inform the theory and practice of STEM instruction. Some of these researchers have created technological systems, where students solve sensorimotor interaction problems as cognitive entry into curricular content. However, the field has yet to agree on a conceptually coherent and empirically validated design framework, inspired by embodiment perspectives, for developing these instructional resources. A stumbling block toward such consensus, we propose, is an implicit disagreement among educational researchers on the relation between physical movement and conceptual learning. This hypothesized disagreement could explain the contrasting choices we witness among current designs for learning with respect to instructional methodology for cultivating new physical actions – whereas some researchers use an approach of direct instruction, such as explicit teaching of gestures, others use an indirect approach, where students must discover effective movements to solve a task. Prior to comparing these approaches, it may help first to clarify key constructs. In this theoretical essay we draw on embodiment and systems literature as well as findings from our design research so as to offer the following taxonomy that may facilitate discourse about movement in STEM learning: (1) distal movement is the technologically extended effect of physical movement on the environment; (2) proximal movement is the physical movements themselves; and (3) sensorimotor schemes are the routinized patterns of cognitive activity that become enacted through proximal movement by orienting on so-called attentional anchors. Attentional anchors are goal-oriented phenomenological objects or enactive perceptions (“sensori-”) that organize proximal movement to effect distal movement (“-motor”). All three facets of movement must be considered in analyzing embodied learning processes. We demonstrate that indirect movement instruction enables students to develop new sensorimotor schemes including attentional anchors as idiosyncratic solutions to physical interaction problems. These schemes are, by necessity, grounded in students’ own agentive relation to the world while also grounding target content such as mathematical notions.

Embodied Learning Environments for Graphing Motion: a Systematic Literature Review

“…Considering bodily experiences as fundamental for learning has a rather long history in the educational and developmental sciences, and has recently received an increased interest through the embodied cognition paradigm (e.g., Abrahamson and Bakker 2016;Radford et al 2005;Wilson 2002). Piaget (1964) described how during the first sensorimotor developmental stage a child acquires "the practical knowledge which constitutes the substructure of later representational knowledge" (p. 177).…”

Touchscreen Tablets: Coordinating Action and Perception for Mathematical Cognition

“…However, these theories have by and large focused on learning-with- paper rather than learning-with- technology (Papert, 2004). This theory-to-practice gap is particularly acute in the case of touchscreen tablets: Whereas tablets offer a breakthrough in human-computer interaction by way of enabling direct multi-touch manipulation of virtual objects, educational research is still scarce on how performing motor actions can contribute to the development of conceptual knowledge (Glenberg, 2006; Marshall et al, 2013; Abrahamson and Bakker, 2016). Even when researchers do engage students in multimodal interaction, where action and perception are elicited as cognitive entry into target concepts, these actions and perceptions are rarely studied via multimodal learning analytics (Worsley and Blikstein, 2014).…”

Classifying Learner Behavior from High Frequency Touchscreen Data Using Recurrent Neural Networks

“…Students devise a broad variety of sensorimotor schemes for enacting a target movement [2,7,8,12]. Knowing what schemes students are employing is critical for supporting their learning, and yet determining these schemes has been a challenging engineering task.…”

“…Understanding proportionality involves appreciating multiplicative relations between extensive quantities; a change in one quantity is always accompanied by a change in the other, and these changes are related by a constant multiplier [14,26]. Our MITp approach to support students in developing multiplicative understanding of proportions draws on embodiment theory, which views the mind as extending dynamically through the body into the natural-cultural ecology [2]. Thus human reasoning emerges, and is expressed through situated sensorimotor interactions [1].…”