Monthly Archives: July 2017

Embodied and Informal Learning

It’s Safe to Come Back Now.

Essentially, early applications of AI to model the brain and human learning failed because it viewed cognition as internal and sequestered from the environment.  Constructivism and Situated Learning theories filled the gap, exploring best practices from a broader learning environment perspective.  Their success as theories seem to permeate the MET program.  After significant developments in neuroscience, it’s safe to come back to cognitive learning theories!

Can the Brain Operate in the Absence of an Environment?

Embodied cognition  seems to come down to this question.  In the old system of AI, although not necessary, once “loaded with programs” the brain could operate independently of its environment, a computer floating through space just doing its own thing.  The key change was to overthrow the “isolated brain” model and replace it with a complex, adaptive cognition system that is floating in an environmental soup.  In this model the “computer” cannot operate without a context.  Moreover, the embedded connection between the corporeal organs of the cognitive system (eyes, ears, etc) and the environment form a unique “umwelt”.  In other literature, I’ve heard this called a “lifeworld”.  A paper by Jones (2013) notes that students are naturally motivated to learn and develop successful adaptations to their environment when involved in informal learning activities, like Geocaching.  I believe motivation and the concept of umwelt are very strongly connected.  That is, it is easier to be motivated to learn things when you perceive them clearly and see subtleties in the same way that “beer tasters…[have]… heightened perceptual discrimination” (Winn, 2003, p. 13).    In his 2010 article, Nunez argues that the time is right to develop and use a more rigorous scientific approach to this theory of learning.

Learning as Adaptation.

This section of the Winn paper produces a teaching “road map” of sorts for providing the desired environmental pressures to idealize learning.  If bio-chemistry and genetic history provide a basis for our cognition, then environment provides the pressure to adapt or “learn” in stages:

  1. Notice something is wrong with concept.  (Declare a break)
  2. Disambiguate the effect.  (Draw a distinction)
  3. Embed the “new rule” to the existing conceptual network.  (Ground the distinction)
  4. Give the idea a trial run to test its usefulness.  (Embodying the distinction)

This seems a lot like Scaffolded Knowledge Integration with an additional “usefulness testing” stage.  These readings have made me more aware of the situated learning in my own practce as it relates to the senses.  I can see that the design and building of physical artifacts in PBL is of crucial importance!

Questions for Colleagues

  1. There is a mention of “Genetic predisposition to change” (Winn, 2002, p. 19).  Does this suggest that some students are genetically better at learning?
  2. Further in the paper, Winn states “The rules or procedures, that specify how the student interacts with the environment in the first place also change through adaptation, based on their success at producing fruitful behaviour.”  (Winn, 2002, p. 20).  Is this the same as saying that winning begets winning?  Is learning exponential or self-rewarding?
  3. Finally, in reference to Jones’ (2013) study of informal learning structures, how do we leverage the intrinsic motivational features of informal learning and make it count for our more formal processes?  Can understanding student “umwelt” and making their learning visible help us chose more motivating projects and approaches to teaching?


Jones, A., Scanlon, E., & Clough, G. (2013). Mobile learning: Two case studies of supporting inquiry learning in informal and semiformal settings. Computers & Education 61, 21-32.

Linn, M., Clark, D., & Slotta, J. (2003). Wise design for knowledge integration. Science Education, 87(4), 517-538.

Núñez, R. (2012). On the science of embodied cognition in the 2010s: Research questions, appropriate reductionism, and testable explanations. Journal of the Learning Sciences, 21(2), 324-336.

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.


Socrative is an interactive questioning app.  While it is to specific to Math and Science I have used it often in both subject areas.  The program offers the opportunity for students to work in groups and enter their response to a question that you push out to the linked devices.  All answers show up on the display and then in their groups they vote on which answer they think is the best.  It allows for lots of discussion and interaction between peers and even if they are unsuccessful in finding the correct answer they get to see all of the answers and then decide why one is better.  Great at getting kids talking and talking about their learning and explaining why.

Authentic & Embodied Learning

Wow, were there ever a lot of interesting readings this week! I decided to kill two birds with one stone and choose readings that could inform the TELE that I will be undertaking for my final project. The aim is to use this TELE for my Grade 1 students in September and the readings this week helped me step closer to my goal. For that reason, I chose to read the Winn (2003), Aleahmad & Slotta (2002), & Huang, Lin & Cheng (2010) articles.

The Winn (2003) article focused on the connections between learning, the activities chosen and cognition. Examining the interactions between the learning that occurs and its relativity to the learning environment, via one’s external body is what Winn (2003) refers to as embodiment. Mathematics is a topic that benefits from embodied learning. One way that I have used embodied learning in my classroom is when doing a math unit on measurement and weight. I have filled little-big bags of sand and the children will pass them around. Based on what they feel, they will order them in what they believe to be lightest to heaviest. We then check our answers by utilizing a scale to see if we are correct or not. I have also brought students outside to explore our local community and compare different rocks, tree branches, etc. and categorize them as heavier/lighter. I find that when my students are able to leave the traditional classroom setting and explore their physical environments, the learning is deeper. As Winn (2002) states, “Embeddedness therefore depends on the nature of the interaction of the students with the Umwelt [environment] and how well the Umwelt reflects properties of the environment” (p. 13).

The Aleahmad & Slotta (2002) article examined handheld technology, such as phones, iPads, tablets, etc. and web-based science activities (WISE). Combining the two, the authors argue, makes for a “unique educational opportunity” (p. 2). As I mentioned earlier, I am teaching a Grade 1 class in September and have been trying to find educational technologies that would be age-appropriate for my students. When looking through the WISE archives, I noticed that despite the fact that there is a K-3 category, there are no WISE activities for this age group of students. The Aleahmad & Slotta (2002) article made me think about the use of Virtual Realty and Augmented Reality programs and their usefulness in the classroom. While I have not implemented either into my classroom, the idea leaves me with some questions.

Questions to Consider:

  1. Should WISE activities only being designed and utilized for Grades 3 and up or is it possible to create a WISE that would benefit younger students?
  2. What are some VR/AR that are suited to younger students? Are these two technologies still too young in their development to be used in classrooms?
  3. If students are learning in artificial environments, does authentic learning occur? Do all learning environments have to produce authentic learning?


Aleahmad, T. & Slotta, J. (2002). Integrating handheld Technology and web-based science activities: New educational opportunities. Paper presented at ED-MEDIA 2002 World Conference on Educational Multimedia, Hypermedia & Telecommunications. Proceedings (14th, Denver, Colorado, June 24-29, 2002); see IR 021 687.

Huang, Y. M., Lin, Y. T., & Cheng, S. C. (2010). Effectiveness of a mobile plant learning system in a science curriculum in Taiwanese elementary education. Computers & Education, 54(1), 47-58.

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.

Math and the embodied learning classroom

Winn (2003) believes that the role the environment plays in learning has been greatly underplayed in research.  As we moved to acknowledging that constructivism was a more student active way to support learning Winn builds upon that interaction between environment and learning and states that we must “in turn, […] consider […] how our physical bodies serve to externalize the activities of our physical brains in order to connect cognitive activity to the environment.” (Winn, 2003) He continues with this thought process to argue and to support his theory that a more integrated approach “framework that integrates three concepts, embodiment, embeddedness and adaptation.” (Winn, 2003)

Article two found that targeted formative qualitative feedback improves student performance on tasks.  Roschelle, Rafanan, Bhanot, Estrella, Penuel, Nussbaum, & Claro (2010) used a cooperative learning environment as it mimics similar traits to peer tutoring and encourages two positive learning situations: positive interdependence and individual accountability.  Using a program called TechPALS that encourages three students to work together to solve part of a problem in math using a portable tech device, instant feedback in relayed to the group about the problem as a whole and then the students continue to solve.  Throughout the process feedback is provided real time to the teacher.  Overall they saw “small group practice of tasks that link conceptual understanding and mathematical procedures as a genre of activity that can be further supported using technology.” (Roschelle et. al, 2010)

The third paper I read looked at use of gestures in math classroom and its influence on understanding.  Novack, Congdon, Hamani-Lopez, & Goldin-Meadow (2014) conducted a study to see if students could generalize the knowledge beyond the problem that was taught.  Novack et. al (2014) found the “first evidence that gesture not only supports learning a task at hand, but more importantly, leads to generalization beyond the task.”

I chose to look at the study of mathematics for this week as it was mentioned that so much of our work has been around science and TELE’s and I wanted to explore TELE’s in a math environment.  Students often struggle conceptually with Math, long division for example.  It’s hard to replicate with hands on learning due to size of numbers but I wonder if a more embodied learning approach would result in greater understanding by students.  I am sure there is, I just need to find it, but a TELE that would allow students to interact with large numbers and divide into groupings to see how long division works if they would then be able to bring that knowledge to the algorithm?

I end up with these questions:

  • We know feedback is important, what other TELE’s can be used to support more instant feedback to students in an elementary math classroom?
  • What bridges need to be developed or examined, for example the Math gestures study, to support students moving from concrete hands on to algorithms and showing their work?
  • What supports do teacher need to be able to teach Math in an embodied learning style?


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.

Roschelle, J., Rafanan, K., Bhanot, R., Estrella, G., Penuel, B., Nussbaum, M., & Claro, S. (2010). Scaffolding group explanation and feedback with handheld technology: impact on students’ mathematics learning. Educational Technology Research and Development, 58(4), 399-419.

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation.  Technology, Instruction, Cognition and Learning, 1(1), 87-114.

Virtual worlds


This weeks readings regarding embodiment and VR/AR made me think about two separate platforms that I am starting to use in my classroom.  As Winn states“Artificial environments can use computer technology to create metaphorical representations in order to bring students concepts and principles that normally lie outside the reach of direct experience.”(Winn, 2003). Cospaces is a VR creation program that allows for the effortless creation of virtual spaces to interact with using cheap VR devices such as Google cardboard.  As the article discusses we learn more when immersed in environments “Bodily activity is often essential to understanding what us going on in an artificial environment.  The ability to move about makes it easier to remember three dimensional spacial layouts.”(Winn, 2003). I only had the final term to have my students start to develop spaces within this platform but what I did notice was the speed at which they picked up not only the construction of the virtual environment but the ease with which they started to code object interaction within the virtual space.  I have used Scratch for 3 years now to teach coding and CoSpaces uses the same Blockly script writing to code your characters or environment to interact with the user.  While Scratch is 2D the 3D plan seemed to increase intrinsic motivation, boost problem solving ability and heighten creative construction in a way that far surpassed Scratch. While there is of course the benefits of multimodal forms of learning I also believe that “memory retrieval and learning is aided when information is associated with physical locations.” (Bujak, Radu, Catrambone, MacIntyre, Zheng, & Golubski 2013).  Drop students into a lush tropical jungle in CoSpaces or Minecraft and get them to learn about perimeter and area will yield a much more memorable result than teaching it in a classroom.


The second platform that I have been experimenting with at home is Leap Motion

Now while most schools cannot afford a Vive or Occulus Rift this really is the next level for physical interaction with virtual objects.  “AR technology can aid the creation of embodied metaphors, by combining physical and virtual manipulatives into experiences where students use physical objects augmented with virtual information.(Bujak, Radu, Catrambone, MacIntyre, Zheng, & Golubski 2013).

The software/hardware combination is very powerful and while the price point is far too high I believe that soon we will start to see these kinds of infrared tracking devices hooked in to VR platforms used more in education.

As well as with CoSpaces I can attest to the fact “a significant difference in the behavior and engagement of students during the AR implementation as compared to their normal classroom behavior” (Dunleavy, Dede, & Mitchell, 2009).  Previously disengaged students suddenly don’t want to leave Math class because they are enjoying their time immersed in the experience.  We are just at the cusp of this new tech completely changing the way we teach and I am excited about the ways that VR/AR will transform learning.


Two questions:


How do we couple VR with content as building games is very time consuming?

What skills do we lose when implementing these new technologies?


Bujak, K. R., Radu, I., Catrambone, R., MacIntyre, B., Zheng, R., & Golubski, G. (2013). A psychological perspective on augmented reality in the mathematics classroom. Computers & Education, 68, 536-544.


Dunleavy, M., Dede, C., & Mitchell, R. (2009). Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. Journal of Science Education and Technology, 18(1), 7-22.


Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.

Embodied Learning with Osmo

Embodied learning involves the whole body when learning and constructing knowledge. Embodiment means that states of the body, such as arm movements, arise during social interaction and play central roles in social information processing (Barsalou, 2003). Numerous studies have shown that body movements and embodied learning can have substantive positive effects on children’s cognition, learning, and academic achievement (Chandler & Tricot, 2015). Anderson (2003) explains that Embodied Cognition is learning that results from interactions with our environment. In primary grades, students count with their fingers, use number blocks, and manipulativew, to develop basic number sense.

As I was reading the articles, I continued to connect this to STEM activities in the classroom. In a lot of STEM challenges, students are building, tinkering, and making, using their hands. We often interact with nature for science, whether it be nature walks, documenting ideas in our science journals or on the iPad, or doing experiments. From my experience, I have found that students retain more information and can share evidence of their learning when it is connected to a hands-on, interactive project or lesson.

I also connected these articles to Osmo game sets for the iPads. I recently adopted this in my classroom for math rotations. I think that incorporating Osmo into a math program is an example of a learning activity that incorporates motion activity and digital technologies. Osmo is a gaming accessory for the iPad. It includes a base, reflective mirror, and tangible pieces. It creates a hands-on learning experience paired with technology. The learner interacts with the pieces and the iPad, an example of motion activity and embodied learning. Osmo is intended for children aged 6-12. Students love using it because of its game-based learning style. “Researchers agree that the use of manipulatives in mathematics increases mathematics achievement and plays a large part in student learning, understanding, and conceptualization of simple to complex concepts” (Boggan, Harper, & Whitmire, 2010).

Questions I am left with…

Is embodied learning as effective for students who can’t control their body?

How can we provide more embodiment during math instruction, not just in activities?


Barsalou, L. W. (2003). The psychology of learning and motivation: Psychology of learning and motivation volume 43 social embodiment.43C, 43. doi:10.1016/S0079-7421(03)01011-9

Boggan, M., Harper, S., & Whitmire, A. (2010). Using manipulatives to teach elementary Mathematics. Journal of Instructional Pedagogies. Retrieved from

Chandler, P., Paul Chandler, & André Tricot. (09/01/2015). Educational psychology review: Mind your body: The essential role of body movements in children’s learning Springer. doi:10.1007/s10648-015-9333-3


Cognition in Physical Activity

Cognition is embodied in physical activity interacting within contextual situations, constructing knowledge instead of traditional encoding, remembering and recalling. Learning incorporates cerebral with bodily, negotiating meaning through social activity externalizing thinking as behavior. Reciprocal interaction between mind and environment offers differing perspectives, for example interpreting 3D space using bodies as data points. Our brains map objects to representations, where mental reasoning depends on factors like economic status, ethnicity, family support, teacher quality and school preparation (Winn, 2003). Biological adaptation transforms pictures into associative networks dynamically interacting sensory inputs. Bodily engagement like thought-gesture coproduction grounds perception and action with physical environment (Núñez, 2012), where experience develops structure towards higher level conceptual systems. Reality environment can differ from known umwelt (Winn, 2003) based on individual background, where multiple ways of knowing removes fixed objective standards to assess knowledge. Thinking is embodied and situated, testing hypotheses and explanations, where science uses methodical experimentation collecting empirical data to avoid reductionism. Science operationalizes cognitive mechanisms, using speech, gesture, eye and thought synchronization to make introspections of observations.

Technology reduces physical limits enabling metaphorical representations out of reach from direct experience, instrumenting tools to observe phenomena and make inferences. Explanations are limited by natural environment viewing from particular time space scales. Metaphors however risk misinterpretation or incomplete understanding, for example distorting time whose simplification results in misconception (Winn, 2003). Complete attention to immersion may produce flow as total engagement and enjoyment losing track of time, while reduced presence caused by distraction or discomfort impedes learning. Aleahmad and Slotta (2002) used handheld technologies with browser-based learning environments to scaffold data collection and reflection activities. WISE Inquiry maps coordinated activities, embedding pop-up notes or hints. Convenient portable data creation makes content dynamic with syncing, where beaming checklists have ‘cool’ factor maximizing take-home learning through social networks. Learners select criteria for wider audiences, evaluating sources when synthesizing observations.

During teacher education, a particular lesson involved volunteers lining up holding papers containing numbers and a decimal point. As students reorganized themselves along the line, they embodied significant figures in Chemistry. However the extent of learning content between observers and participants may vary, having difficulty translating activity back into traditional media. Educators persuade students to challenge uncertainty with difficulty embedded in constructive activity towards intuitive explanations. Optimal challenge elicits curiosity to adapt embodied interactions to affect deeply-rooted belief and genetic predisposition to change. Instruction proves effective only when employed at appropriate levels of granularity. Embeddedness employs interdependence between cognition and environment, dynamically interacting to regularly process learning.

  • How do we coordinate movement towards cognition for learning content? What is the bodily basis of conception, image schemas and conceptual mappings (Núñez, 2012)?
  • What affordances and limitations does each representation mode provide? What specific advantages for example does real-world data have over dynamic content?


Aleahmad, T. & Slotta, J. (2002). Integrating handheld Technology and web-based science activities: New educational opportunities. Paper presented at ED-MEDIA 2002 World Conference on Educational Multimedia, Hypermedia & Telecommunications. Proceedings (14th, Denver, Colorado, June 24-29, 2002); see IR 021 687.

Núñez, R. (2012). On the science of embodied cognition in the 2010s: Research questions, appropriate reductionism, and testable explanations. Journal of the Learning Sciences, 21(2), 324-336.

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.

Comparison & Synthesis

Sorry about the lateness, I’m out of town and have very spotty connections. But, here is my overall take of the TELEs.

Anchored Instruction and Jasper


LfU and MyWorld

T-GEM and Chemland

Learning Approach

Use meaningful approach towards learning by helping students make meaningful connections to difficult concepts.

Scaffold students through difficult concepts, with the help of media.


Inquiry based learning on web.

Builds knowledge through student- centred lessons.

Interactive learning


Learning for use, putting purpose for the learning by identifying the use of the content.

To motivate learning by identifying the use of the content in real world situations


TPCK lessons that Generate, Engage, Motivate

Lesson taught with the aid of simulators to digitally enhance learning.


Interactive Learning


From the different TELEs, we looked at, there were a few things that seems to have made up the basic recipe for successful TELEs. This list includes educators’ need to focus on creating lessons that are student-centered, have the option to be self-paced and allows for active learning through interactive interactions with the content through a technological component. Another key component noticed in the different frameworks, was also the critical thinking component in the approaches. The frameworks recognize the importance of students being intrinsically motivated through their own curiosity and skills, which fuels the learning process for each student.  

Technologies can help educators guide students in the right direction while not having to physically cater each lesson for each student. That said, I believe that technology can only enhance a lesson so much, but can not completely replace the teacher’s existence, and technologies will only enhance a lesson if it’s chosen correctly.


Partners In Research (PIR Canada)

Partners in Research (PIR Canada) is website

that has a number of free online programs for elementary to high school students. One program is called VROC (or virtual researcher on call that connects specialists in the field with students) and the other is PIR Live Events (webinars). I have done several PIR Live events and been a part of webinars with inventors in the UK. Webinars cover a variety of STEM topics – from makerspace to cancer research. Students can pose questions and “chat” to the guests in real time. It was a great opportunity for students!

They also have their own YouTube channel and PIR TV to get students interested and enthusiastic about STEM.

Mobile Devices and Embodied Learning

Winn’s (2003) concept of “Umwelt” was interesting and it had me thinking about how we all “see” the world very differently. As students embody experiences, they make meaning through their interactions. Winn states that “..the uniqueness and variability of Umwelt are not the result of limited sensory capacity, which we saw above is a physiological constraint. Rather, they arise from differences in each individual’s experience of the environment” (p. 12). Stemming from this I consider about our students with learning challenges who have always interacted with their environment in different ways than neuro-typical students and how embodied learning provides opportunities for more inclusive education in all subject areas.

Novak’s article (2014) was thought provoking. Grade three students were instructed in one of 3 types of problem solving strategies:

  1. physical action
  2. a concrete gesture miming that action
  3. an abstract gesture

All three types of strategies aided students in solving problems they were trained to solve, but the abstract gesturing was successful in applying this knowledge to general conditions. This gesturing led to deeper and more flexible learning. I found these results very surprising as an educator who was always told to incorporate the use of concrete manipulatives in math class. I have, however, used gesturing in science class teaching concepts such as the kinetic molecular theory and the movement of molecules and a applied the performing arts through a student-created play based on the digestive system. I am left wondering how we take this knowledge and apply gesturing into the teaching of mathematics? When I use Sphero with students, I have students use their bodies and arms to construct angles so that they understand the directions Sphero will roll on their commands, but I think using gesturing for more complicated tasks would be a challenge. Based on the works of Novack et all (2014) gestures were shown to foster generalization of math concepts – this was done without technology. How much of a role does technology or should technology play in Embodied Learning?

Finally, the article by Baya’a and Dahler (2009) I was not surprised in students’ positive perceptions of using mobile devices for learning mathematics and their role in embodied learning. The researchers found students enjoyed the novelty of using mobile devices especially within a mathematics class and that “mobile devices extend the learning environment in which the students work, and integrate it in real life situations where learning can occur in authentic contexts” (p. 6-7). Mobile devices offer the opportunity for learners to physically interact with the world outside of traditional classrooms. Coming back to students with learning (or physical) disabilities mobile technologies afford opportunities for students to interact with their environment in a ways that may not always be possible through traditional routes. In this study middle school students were using mobile technology in an outdoor education setting, using their own devices. How could we replicate the same positive educational experiences for our students using the hardware in our schools? How do we manage these tools within a school environment? Do we start with the technology and build the experience or the other way around? I was trying to reflect on how I have used mobile technology along the lines of this theory. What experiences do we as educators (and consumers of technology) have using mobile devices from an embodied learning perspective?



Bayaa, N. & Daher, W. (2009). Learning Mathematics in an Authentic Mobile Environment: The Perception of Students. International Journal of Interactive Mobile Technologies, 3, 6-14

Novack, M.A., Congdon, E.L., Hermani-Lopez, N., & Goldin-Meadows, S. (2014). From action to abstraction: Using the hands to learn math. Psychological Science, 25 (4), 903-910.

Winn, W. (2003). Learning in artificial environments: Embodiment, embeddedness, and dynamic adaptation. Technology, Instruction, Cognition and Learning, 1(1), 87-114.