Evolving STEM & Embodied Learning
“Learning is considered to arise from the reciprocal interaction between external, embodied, activity and internal, cerebral, activity, the whole being embedded In the environment in which it occurs” (22).
Winn (2002) describes a theoretical framework for socially situated learning in artificial environments where the concepts of embodiment, embeddedness and adaptation are interdependent. Embodiment is the physical dimension of cognition where the brain and body work together to gain knowledge. Each person has ‘umwelt’ which is the difference in how we interpret ideas since there is no object ive reality. We also use our bodies to solve problems, so “cognition consists of the constant, reciprocal, interaction between the mind and the environment” (pg. 11). Embeddedness is the interdependence of cognition and the environment. Artificial environments, like the Puget Sound simulation, allow learners to solve problems through their interaction within the environment which involves active discovery, testing and application. The dynamic adaptation in their thinking as a result of involvement in such environments leads to changes in thinking through (1) realizing something cannot be accounted for or explained, (2) distinguishing this new phenomenon from what’s familiar, (3) determining how this new knowledge fits with what one already knows, and then (4) using the new information in a meaningful way.
Stevens (2011) in The Missing Bodies of Mathematical Thinking and Learning Have Been Found, provides synthesis and interpretation to a set of articles contained in that journal issue focused on the active mind involving the body (sensing, feeling and thinking. Although he concurs with Winn (2002) that the body definitely plays an important role in mathematical cognition, he provided much criticism of the current research in terms of being able to accurately assess what is actually happening in these complex environments.
Roschelle’s (2003) early paper on determining the learning potential of wireless mobile devices is somewhat dated in its focus on the use of palm pilots to allow for embodied learning. Although this concept of having students be physically embodied with a device and navigating the physical space of a classroom, a participatory simulation, they can navigate digital environments in somewhat the same manner. He also discussed classroom response systems, like the Smartboard Senteos, that are useful for uncovering student misconceptions and quickly displaying group data for analysis. Collaborative data collection and analysis allows for socially-situated learning as well. He outlines many practical problems and needs for these types of uses to occur.
In having students learn Math using independent learning materials (sometimes provincially developed eLearning environments), I plan to find object and tools that will help me to teach algebra, linear, exponential and quadratic functions, exponents, fractions, and possibly financial math (interest, annuities, RRSPs, loans, etc.). There are several targeted flash objects or simple applications available online that could be used with a TGEM cycle exploration instead of a list of questions. Since the number of students I have working on these courses at any given time, It is difficult to incorporate much social grouping, but I plan to have students work in pairs and small groups to discuss/compare their learning.
References:
Roschelle, J. (2003). Keynote paper: Unlocking the learning value of wireless mobile devices. Journal of Computer Assisted Learning, 19, 260-272.
Stevens, R. (2011). The Missing Bodies of Mathematical Thinking and Learning Have Been Found. Journal of the Learning Sciences, 21(2), 337-346.
Winn, W. (2002). Learning in Artificial Environments: Embodiment, Embeddedness and Dynamice Adaptation. Tech., Inst., Cognition and Learning, 1, 1-28.
Questions for Colleagues:
- How could adult learning in an alternative education setting be altered to include social, interactive learning, i.e. learning community?
- How are students with learning disabilities affected when operating within TELEs in terms of demonstrating their knowledge?
- How can classroom response systems (i.e. Senteos) be used for more completed data collection and display, i.e. beyond the multiple choice and true/false questions?