Embodied Learning

The following is a reflection for my ETEC 533, Technology in Science & Mathematics classrooms course in my Masters Program.

How could you use what is developed in these studies to design learning experiences for younger learners that incorporates perception/motion activity and digital technologies? What would younger children learn through this TELE (technology-enhanced learning experience)?

First, some rough definitions will be helpful for this discussion:

Embodiment: Representing an idea in a tangible form.

Embeddedness: The degree to which a student is engaged in an activity’s physical location/presence.

Dynamic Adaptation: The changes that occur to a student and the environment, simultaneously.

Below is an example lesson of using embodied learning, and artificial environment with the help of robotics, to better create an environment that fits within a child’s zone of proximal development.

Computational Thinking (CT), Embodiment, Programming, & How Robotics can improve Grade 1 students’ understanding of Angles

In order to better apply the concepts of embodiment, embeddedness, and dynamic adaptation, it makes sense to anchor our discussions and musings. As I am a technology teacher, programming is a large portion of my curriculum, but the concepts of computational thinking apply immensely towards mathematics as well. I’ll be discussing how grade 1’s understood angles (concepts not introduced until 3rd grade) through the use of dash and dot robots.

Lesson Overview

Previously, I had taped out “mazes” using coloured masking tape on the ground. Each maze length was in 10cm units, and turns were selected in 15 degree units. It is helpful to know that to the App for dash and dot allows them to move in 10cm increments, and turn in 15 degree increments. Mazes made various shapes such as squares, L’s, Z’s, etc, and students had to make the robot move from one end to the other. 

Analysis

As this was an artificial environment, or Umwelt, as Winn would claim, I was able to know what the robots were capable of creating, and thus, create an environment in which I could control a student’s experience within this environment. While not truly artificial like a VR experience or video game, the limitations of the robotics themselves allowed me to place constraints on students to experience simple maze such as an “I”, then incorporate turns like an “L” and then more advanced turns like a “Z”. Students advance through levels of mazes, and in each new maze they encounter a “break” in their current understanding of turns, and must draw a distinction from previous knowledge (such as a left turn 90 degrees and a right turn 270 degrees are the same, if a particular maze was limited to only turning 1 direction). The student can ground their distinction in other turning knowledge from previous mazes, and right away embody the knowledge with seeing the robots in action. This lesson allows for students to interact with geometry concepts within an artificial, restricted environment in an engaging way to better support their learning in scaffolded chunks.


REFERENCES

Alibali, M. W., & Nathan, M. J. (2012). Embodiment in mathematics teaching and learning: Evidence from learners' and teachers' gestures. Journal of the Learning Sciences, 21(2), 247-286. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/ 10.1080/10508406.2011.611446

Miller, C & Doering, A. (Eds). (2013). The new landscape of mobile learning: Redesigning education in an App-based world. Minnesota: Routledge.

Novack, M. A., Congdon, E. L., Hemani-Lopez, N., & Goldin-Meadow, S. (2014). From action to abstraction: Using the hands to learn math. Psychological Science, 25(4), 903-910. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984351/ (Links to an external site.)

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114. Full-text document retrieved on January 17, 2013, from: http://www.hitl.washington.edu/people/tfurness/courses/inde543/READINGS-03/WINN/winnpaper2.pdf