This week, I had the opportunity to investigate Winn (2003), Aleahmad and Slotta, J. (2002), and Núñez (2012).
Winn (2003) provides a robust reimagining of the constructivist framework in light of developments in neuroscience. Winn (2003) situates embodied learning as an outgrowth of both constructivist and information processing theories. Winn (2003) rejects the constructivist perspective that a learner’s constructions are to unique to be adequately measured. He asserts that, instead, an educational designer can make use of artificial environments add predictability to the constructions students might make. With regards to information processing, Winn (2003) views the previous views as inadequate due to an exaggerated focus on symbol manipulation and insufficient exploration of their meaning. Winn expresses theory central tenants to the theory: That cognition is linked to our physical being (embodiment), that we are coupled to our environment (embeddedness), and that we influence, and are influenced by our environment (adaptation).
Nunez (2012) examines the state of embodied cognition as a theory. Nunez identifies that embodied cognition is capable of providing rich descriptions of phenomena but that many other theories have stalled at this point. To be considered scientific, embodied cognition must begin to generate testable theories. If it is unable to provide these, embodied cognition may not have a sufficient claim be being considered scientific.
Aleahmad and Slotta (2002) looked at the use of handheld devices for data collection when combine with the wise environment. They found promising results from two trials and were able to implement both survey style and measurement style data types.
Aleahmad and Slotta (2002) seem to have happened upon a possible solution to issues faced in Winn (2003). Winn asserts that engagement with artificial environments is key to realizing their benefits. What the tablet devices may allow is a sort of bridge between the artificial and real environments. When students leave the classroom, they must uncouple from an artificial environment. The tablet might serve as a kind of tether. The presence of the device, and the fact that data collect with it will return to the artificial environment, serves to continually remind students of the presence of the artificial environment waiting for them back in the classroom. Despite not being present, the artificial environment still acts upon the cognition of the student and influences how they behave in the real environment. These actions, in turn, will alter the artificial environment through the input of new data. In essence, while Winn (2003) was looking for a solution to students becoming distracted from the desired artificial environment, Aleahmad and Slotta (2002) are using a tablet to, in a way, distract students from the real environment and back to the artificial one.
In my own practice, I have had some great success using WISE to investigate the cause of the seasons. Instead of data gathering with mobile devices though, I used simulations with my students. The process clearly reflected Winn’s (2003) view that both the student and the artificial environment mutually influence each other. The students began with data to collect. As they manipulated the simulations, they began to develop questions. This led to different tests of the environment yielded further result and more questions. I also found that the use of simulations seems to reduce cognitive load. Students were able to reason more accurately when observing a model/simulation instead of having to use their working memory to represent and manipulate representations of the earth and sun.
Going forward, I would certainly plan to use more simulations to help students discover phenomena, scaffolded by leading questions or key data that needs to be gathered. Timely provision of dissenting information and observations, a key tool I began using in the above WISE unit, will be carried forward into other STEM subjects to help facilitate inquiry learning.
In terms of some questions about embodied learning, I wonder, to what extent could practicing externalized cognition can impact student learning in STEM disciplines? By prescribing certain styles or approaches to of note taking, equation solving, unit analysis, etc., in the external environment, might we be able to shape a student’s conceptions more accurately?
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. Available at: https://eric.ed.gov/?q=Integrating+handheld+Technology+and+web-based+science+activities%3a+New+educational+opportunities&id=ED476962
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. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/10.1080/10508406.2011.614325
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 March, 2017, from: http://www.hitl.washington.edu/people/tfurness/courses/inde543/READINGS-03/WINN/winnpaper2.pdf
Hi Daniel, I’m not entirely sure if I understand your question. Are you asking if we teach explicit methodologies when it comes to note taking, math processes, and such, will it positively impact our students’ conceptions? If that is what you are asking, then I would say, it depends. I think that there are times in which allowing students to think freely and creatively, posing problems and crafting solutions on their own, is appropriate. Yet, other times, following a more prescriptive process is going to lead to being able to reach farther in the academic math and science. Grade 10 math students sometimes don’t like it when I tell them what the minimum steps are to show, thinking that final answers alone are sufficient. But to craft complex mathematically based solutions, require students to defend their rational in a logical manner, similar to a lawyer who is making their case in court. We are not spat out of the womb knowing how to do this, nor will it be acceptable to provide our rational in a language that does not follow proper convention— proper notation is vital. When I was entering high school as a Grade 8 student, my mum enrolled me in a note taking and study skills course at UVIC. I was the youngest person there, surrounded by university students. To this day, I organize my notes in the same format that my instructor taught me! Getting me off on such a great foot was really great for my skills and confidence. It is much harder to get our students to reverse a “bad habit” or misconception that to simply start them off in the right direction from the get go.
…If this wasn’t what your intent was with the question, apologies!
Cheers, Dana 🙂
My question is more aimed at the reciprocal nature of student/environment and environment/student influences. Some cognitive process, such as writing, rely heavily on the externalized environment. The written word allows us to expand our working memory artificially andto use space to organize ideas in unique ways.
If cognition is occuring at least partly outside the body, might it not follow that if we can control the form external cognition takes we may be able to directly affect the related internal representations?
I do certainly agree with you that a standardized notational system is incredibly useful. Consistent practice with such a system leads to automaticity of effort and may free up more working memory for critical reflection on the content instead of just focussing on the form of the notes. I wonder if there is there woudl be any benefit in attempting to standardize such techniques early in a students schooling. If done late the students’ Umwelts (Winn, 2003) might be to different to accept standardization. If introduced early, however, it might be possible to build a common language around note taking, mathematical problem solving steps, etc. that might yield surprising efficiencies
In regards to your comment that, “Students were able to reason more accurately when observing a model/simulation instead of having to use their working memory to represent and manipulate representations of the earth and sun”, I wonder how you view hands-on madels as comared to simulated models in terms of student learning. Do you find that using technology driven simulations or models are as beneficial as constructing models or creating simulations? I ask as an elementary educator as I know that younger students benefit from building models and discussing their ideas as they create these models, which leads to deeper understandings. Thank you for your interesting post.
Good Morning Michelle,
I think it really depends on what the goals are. Digital simulations are excellent in the discovery phase. Parameters can be constrained to focus students on specific phenomena while excluding others. Physical models often allow a greater degree of freedom. Once the basics are established, applying principles to physical models helps students to test their beliefs more dynamically and try to figure out potential user errors. In my recent project on the seasons, students used digital simulations to gather data and create a hypothesis. Once they had a theory that agreed with their data, they attempted to prove it using physical models. Many students failed to maintain the correct tilt of the earth and observed that the overhead sun angle never changed through out the year. They had to work on trouble shooting their use of physical models and this really reinforced that the tilt of the earth was the key to the seasons.
I see building models as a culminating step. Once students have gathered data, created a theory, and tested it, the building of a model helps them to identify all of the factors that might influence the outcome. They are, in essence, trying to teach themselves at this point. The building of a model is then a final application of knowledge towards a useful end (Edelson, 2001) which would hopefully transform their knowledge from declarative in to procedural which would allow them to apply it more readily in the future.
Edelson, D.C. (2001). Learning-for-use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching,38(3), 355-385. http://ezproxy.library.ubc.ca/login?url=http://dx.doi.org/ 10.1002/1098-2736(200103)38:33.0.CO;2-M
Your post raises some interesting ontological questions regarding the physical being and the virtual environment: The tablet might serve as a kind of tether. The presence of the device, and the fact that data collect with it will return to the artificial environment, serves to continually remind students of the presence of the artificial environment waiting for them back in the classroom. Despite not being present, the artificial environment still acts upon the cognition of the student and influences how they behave in the real environment. I agree that line between the artificial/virtual/physical is being blurred.
It is interesting to hear about your WISE lesson, Regarding the seasons topic, where are the students ideally collecting the data from? If one was to look at the WISE experience with the seasons, as an interesting exercise, are there words that could be supplied here: would cognition be linked to our physical being (embodiment) [WISE lesson ] , coupled to our environment (embeddedness) [WISE lesson ], and that we influence, and influenced by our environment (adaptation) [WISE lesson ]. I am intrigued by this notion of the cognitive tether.
Thank you for your post, Samia
Good Morning Professor,
The data are collected through a variety of digital simulations. Students are given some starter dates and parameters to collect. Some may be directly observed in the simulations and others must be calculated. Though the simulations overlap some, each focuses on a differect aspect such as the relationship between observed sun height and light intensity, the effect of various tilts on the seasons, or the observed path of the sun as a result of changes in lattitude. I have linked the simulations below should anyone wish to explore them.
Embeddedness is certainly an interesting concept to look at with regards to the WISE environment. The WISE developers encourage the use of group work yet Winn (2003) notes that deep coupling with the artificial environment may rely on minimizing distractions. One would think that group work would, by nature, be disruptive to the goals of coupling/embeddedness but this does not seem to be the case. In my, granted limited, observations, motivated groups of students quickly form a community of inquiry. They realize that the environment is more readily explored and accessible when students define roles and become expert in the various simulations and tools. One student may be entering data, while another calculates, and a third preps the simulation for the next run. There seems to be a sort of group buy-in in these situations in which a strong community of inquiry actually reinforces embeddedness through a mutually negotiated and shared artifical environment. This group environment may differ significantly from other groups’ but shares a certain homogeneity between group members despite individual differences in their Umwelts. When the community of inquiry is weak or unfocused though, I have noticed that they tend to spiral out of the artificial environment quickly and lack a sense of coupling to the artificial environemt. It really seems as though groups are either growing closer as a functioning unit or further apart. They never really appear to be static.
It might be a worthwhile line of inquiry to examing how effective group formation research can inform or enhance the results of embedded learning through the additional of socialy consructed knowledge and environments.