Gee < Dewey and (Bransford Schwartz & Pea) = more concrete Dewey

Both Dewey and Gee posit that students bring with them prior experiences influencing teaching and learning, however, Dewey’s is a more abstract (typical Dewey) argument than Gee’s. Gee focused on a particular type of Dewey’s “continuity”, that concerning language development.

Bransford and Schwartz also take Dewey’s abstract notion of continuity and make it more concrete in their article on “transfer”. Whereas Dewey argued that continuity exists and that it should be used to judge the quality of learning designs, Bransford and Schwartz provide the reader with more concrete strategies (e.g. presenting students with an idea in multiple contexts so that they can identify general characteristics/ principles of the idea existing across contexts) concerning how to help students prepare for future learning (the portion of continuity occurring after a learning experience).

Finally, Pea’s “distributed intelligence” is an idea that could be used during the planning process to help students offload cognitive demand so that the learner can focus more attention upon principles/ characteristics that would prepare them for future learning. In other words, certain lessons might (intentionally or otherwise) lead students to leave the learning experience having focused too much cognitive effort on context-specific knowledge, inhibiting transfer/ continuity. If designers recognized the intelligence of resources outside the learner, it might enable the learner to walk away with a better understanding of ideas that can be applied in contexts beyond that in which the ideas were initially present.

In summary, Gee’s paper was a more specific application of Dewey’s abstract continuity; Bransford and Schwartz’, and, Pea offered implicit/ explicit strategies regarding the development of continuity/ transfer.

Connecting Dewey, Gee, Pea, and Bransford & Schwartz - the Role of Experience and Active Learning

One overarching theme over these four readings is the progressive nature of learning.  Here I mean progressive in the sense of learning builds on previous learning.  Dewey refers to this idea as the continuity of experience.  People apply their past experiences to the present, and the experiences from the present will impact future experiences.  Gee’s focus on language states that people best learn specialist languages and how to think about them when they can connect it to prior experiences.  Pea discusses the need for experience in order to realize the affordances provided by artifacts and the environment.  Bransford & Schwartz focus on the idea of “knowing with” – being able to use previous experiences to influence and interpret subsequent events.  I believe the authors would all agree that experience matters in learning.  What one has seen, heard, and read about influences how one learns.  One of the major arguments behind Gee’s second chapter, I think, follows appropriately.  Minorities and children living in poverty often perform worse in America’s education system because they haven’t been afforded the experiences that children in wealthier, Caucasian families have been afforded.  Not only have they not been exposed to the academic language favored by our education system, but they often aren’t in the place financially to have made visits to museums to learn about history, science, and other fields; they haven’t had the luxury of traveling to new cities and exploring new cultures; they haven’t had access to fancy gadgets, or even simpler gadgets for that matter, like the toddlers who play with iPads nowadays.  Because of their circumstances, the experiences of our disadvantaged populations have been severely limited, relative to middle class society, which, in turn, hinders their performance in America’s public schools.

A second overarching theme is the focus on learning as an active process.  Pea emphasizes distributed intelligence as “manifest in activity.”  Intelligence is when one actively taps into the resources of people (including themselves), the environment, and the situation.  Bransford & Schwartz’s preparation for future learning (PFL) requires individuals to actively question one’s own beliefs and ideas and choose what is worth keeping and letting go, as well as actively adapting environments to one’s needs.  Similarly, Gee argues that to be successful in today’s world, people must be able to actively transform and adapt themselves for fast-changing circumstances.  Dewey best sums this up in his discussion of traditional and progressive education.  In traditional education, students are treated as passive learners.  They are like empty jars being filled with ideas.  Progressive education, however, focuses on the learner as an active participant in the learning process.  It allows learners to bring their own experiences and perspectives into the learning environment.  In order to prepare our students for the future, we must engage them in active learning.  This means changing the way we teach and the way we assess, something that we, as a society, are beginning to challenge more and more.

The Role of Desire & Play

One of the concepts Pea discusses that we didn’t get to touch on much in the class discussion is that on the role of “desire.”  Something has to initiate the use and design of distributed intelligence.  Pea (p. 55-56) maps out four different kinds of desire: (1) task desire – in which a person uses or designs with a clear goal or intention, i.e., I am using this blanket to keep me warm; (2) mapping desire – in which a person has an idea of the goal or intention, but doesn’t know exactly how to apply a tool, i.e., This self-assembly furniture came with this piece that’s clearly a part of the final product, but I’m not sure how it fits in or how to use is; (3) habitual desire – those that occur out of habit, i.e., I use this toothbrush every morning to clean my teeth; and (4) circumstantial – in which there is no specific goal or intention, but in the given circumstance, you seize the opportunity to make use of a tool, often in a way that is untraditional, i.e., I roll up and “pop” the plastic straw I get from the fast food restaurant.  This fourth kind of desire, circumstantial, reminded me of our continued discussion of play.  It supports the ideas that (1) everyone has a desire to play, and (2) play develops distributed intelligence.  Children do a particularly great job of tapping into circumstantial desire and can often turn very simple objects into great sources of entertainment.  In one of the Promise of Play videos, one such clip showed the creation of a microphone stand with blocks.  As adults, too, we develop new, unexpected uses based on simply playing with objects, sometimes mindlessly.  For instance, people make percussions and music out of random items.  The Broadway show, STOMP, exemplifies this.  The actors/musicians use everyday objects like trashcans, sinks, and water to create music.  Through playing in different circumstances, we can exercise our creativity, tap into the distributed intelligence of people and objects that may not have been previously afforded, and create or spur new desires. 

"Knowing With" in Preschool

I found Bransford’s and Schwartz’ analysis of “knowing with” as contrasted to “knowing that,” which he defines as replicative knowledge, and “knowing how,” which he defines as applicative knowledge, particularly interesting. “Knowing with” is described as the ability to approach new situations through the lens of all previous experience and knowledge whether or not the individual can dictate exactly when they acquired those experiences and knowledge. It is the most natural form of transfer.

 They then discuss two mechanisms that act as a platform for “knowing with:” associative and interpretive. The associative platform allows learners to connect their current experience with former experiences, objects, knowledge, and sentiments. The interpretive platform allows learners to place and organize their current situations or ideas into the context of those former experiences.

This passage illuminates everyday situations I observed in the preschool class I taught last fall. Because each child came from a different home with a different family culture and, for most children, this was the first year they went to school, every student approached situations in the classroom in very different ways. They brought with them all of their assumptions about authority, play, and what a daily schedule should look like and that previous experience and knowledge provided the lens with which they saw the classroom and everything in it. Oftentimes they were not able to dictate “why” they made the decisions they did, but after talking with their parents, it was clear that their past experience- relationship with their parents, amount of free time they are given, time they go to sleep- shaped the way they were evaluating situations in the classroom. My students constantly made us of their associative, and often illogical to others, mechanism of knowing. For example, a circle-time about the color red might remind one of my students about her dog without her knowing why. However, because of their age, my students often needed help with the interpretive mechanism of knowing. They could easily learn new concepts but would need our help to put those concepts in the context of the number of the day last week and the other animals at the zoo.

Finding Balance

            As I was reading Pea’s article on distributed intelligence, I identified with the concern referenced by Salomon et. al. (Trade off #1 on p. 74-75), a need to keep in mind and distinguish between “effects with technology” vs. “effects of technology.” Pea discusses the concern that granting students extreme access to resources and technology may result in an increase in accessibility of activity but a deficit in understanding foundational concepts.

My high school did not permit the use of calculators in mathematics until pre-calculus courses with the justification that we needed to learn the concepts behind mathematical processes and formulas to truly understand what we were doing in solving mathematical problems rather than simply “plugging things into” a “magic” calculator. I have tutored many students in mathematics and can see how they may have benefitted from this policy as they often will reach for their calculator with no idea what to compute or why a computation is right for solving a problem. When they encounter a new “style” of problem, they have no starting place of how to navigate it and why they would use one formula over another. I think that, sometimes, since most of us making policies and teaching students were educated the “old fashioned” way of being forced to do things by hand and memorize math facts, we can tend to overlook the ways this has benefitted our understanding of larger math concepts. For example, memorizing addition facts to 10 has deepened our understanding of a base 10 system. Knowing that 3+4=7 fluently allows a 3rd grader to efficiently see how we can use distributive property to break down 3x7 to 3x3+3x4. At a higher-level example, my statistics course in college did not teach us how to use SPSS software. Our professor had us do the analyses by hand, asserting that this was more valuable as it would help us understand what it is each type of analysis was getting at and which analyses would be appropriate for analyzing data sets from different studies. So, during our classes we analyzed the structures of the formulas and why each one gave us the information we wanted about example data sets. I have to say, he was right. The next year, I was working in a research lab. While the lab used SPSS software and I did need some assistance in navigating it, I understood why we were running the tests we were running and how to interpret the information the software gave us.

                 On the other hand, the extreme “no calculator” policy meant that it took students longer to progress through mathematics courses in my high school and likely held many back from reaching their full potential in engaging with the field of mathematics. While it was not difficult for me to be “caught up” on SPSS software, I wasn’t ready to jump right in and use it in the lab. Both articles make a point that we live in a world that is rapidly changing and the information and technology we have available to us is rapidly growing. It would be a disservice to students to ignore this fact. After all, most of us walk around with some form of smart phone or computer in our pocket and can “google” anything we need information on most any time of day (not to mention the calculators, dictionaries, and GPS devices they also can function as). The skills to know how to quickly and efficiently access and use resources and technology that Bransford & Swartz reference in their idea of “preparation for future learning” (p.68) are certainly necessary in the world we are sending our students into. So, the question I am left with is, “how do we find a balance?” How do we prepare our students to build intelligence with technology (p.75) rather than rely on technology to do all the thinking? 

     While reading the Bransford & Schwartz, one section really stood out to me because I remember it so well in my public schooling experience. They mention how “concrete examples can enhance initial learning” because it can “be elaborated and help students appreciate the relevance of new information.” When I was in school, there were two things that happened often. Thinking of my math classes, the first would be seeing examples of real life objects tied to the math we were doing. My seventh grade geometry class would have a tin can and we would talk about surface area of this tin can. I saw first-hand how that helped students visualize a cylinder and it did, in fact, help with initial learning. But just like the article says, this contextualization can “impede transfer because information is too tied to its original context.” Basically, giving just a single context limits the concept of a cylinder and the formulae for surface area and volume of cylinders to tin cans. While some could transfer this knowledge to other real-life cylinders, it was certainly not true that all students could. Especially when it intersected with another shape (transfer of problem to problem). Imagine a water tower that looks like a cylinder with a half sphere on the bottom and a cone on top, students might have been able to do each individual shape, but combining them seemed to be too difficult. I remember students in my class were wondering if there was a formula for the volume of such a shape (which is a fantastic question that students should be asking), but instead of trying to reason through the problem, they asked the teacher for help. Some only wanted hints and then figured it out after one hint. But students who did this began with “can we have a hint?” They didn’t first try to reason abstractly (and quantitatively) – a common core standard. Instead, they wanted to know how to get the answer. A question a toddler is capable of asking.

     My question is, at what point does contextualization go from being a valuable tool for understanding to over contextualization? I’m also curious if there is a difference in value for understanding if a teacher provides the concrete example versus if a student discovers it on their own? If a student does understand better when they contextualize a problem for themselves, how would they be able use this to begin a topic (for Bransford claims it enhances initial learning)?

     I guess in my thinking, I can see it being beneficial in both ways. In my (limited) understanding of project based learning, a student can receive a project that begins with context and has a student explore (e.g. “What is the length of r1 and r2 of this belt?”

) or they can ask a student to provide multiple examples of context for a problem and explain why those examples are valid (e.g. different functions such as f(x)=sin(x), f(x) = x^2, etc. [which all of this would follow many Standards for Mathematical Practice]). 

What is knowing? (Articles on Transfer & Distributed Intelligence)

Both of the articles for this week talked about the need to think about learning as a process that does not end when an objective/goal is reached, but that learning should be expansive in that it prepares us for doing new things in new situations in the future. Pea talked about this from an explicitly design perspective, emphasizing that working with tools does not only offload intelligence to tools and thus reduce what the user must know/do, but working with tools/resources also expands possibilities for what can be accomplished (quantities of knowledge in any given situation are not fixed). Branford & Schwartz talked about learning environments from a more analytical perspective, identifying qualities and framings of tasks/settings that elicit productive activity (as well as ones that constrain it). Both talked about how people's previous experiences (Bransford & Schwartz) and desires (Pea) affect what people pay attention to and thus accomplish in any given setting.

This raises for me the question of design versus use: Can we give people initial experiences or cues that attune their perception to the designer's hoped-for affordances? In line with Bransford & Schwartz, I agree that all instructional activities should begin with eliciting learners' pre-existing ideas and intuitions (even if they are "wrong"), but is this enough to spark interest in topics such as conic sections (math)? If people are always restructuring situations as they act in them (both articles) based on their previous experiences (and Dewey told us how diverse those can be), how can we productively predict what people will do and what they will come away knowing? This might go back to designing for specific users (identifying what they see as the problem, having empathy, prototyping, revising), but what about teachers who are trying to design curriculum for kids they haven't met yet? I know in teaching we always look for formative information that we can use to shape what we do in the future with our students, but the idea that the environment always changes under human inquiry seems to theoretically prevent designing anything. Furthermore, how can we design for future learning if our students have diverse interest-driven learning trajectories (what is the trajectory for learning that comes from learning about conic sections; also, Dewey's continuity of experience comes to mind)?

Maybe the answer to this is that we want to teach for disciplinary practices (knowing how to use what resources when based upon the situation and one's goals), since both authors talked a lot about the value of activity/doing rather than on the internalization/acquisition of specific concepts. But then we would need to design for practices, which means we would have to identify practices and why/when people might find them useful, and I know for mathematics the literature on this is sparse (CCSS Mathematical Practices are not satisfactory to me). HELP!

My Critique of Ayiti:

What students are likely to learn: How hard it is to keep a family healthy, happy, and with enough money to live in Hati, and how these things are interdependent.

How students are expected to engage in content: Students make decisions about whether to ignore health problems, rest, or treat them, and then they watch the family's statistics move in response to the students' decisions. This works for money and happiness as well.

Why particular design decisions right be more or less effective at supporting student learning: I think it would be more useful if players could see where there money was coming from and where it was going. It appears that a certain amount of money is spent every season, but other than illnesses, where does the money go? How much for food, etc? Why can mom be a market woman only some of the time? Is it harder to make/keep money in the rainy season? All of this is hidden in the general way money is dispersed. I am also not sure why I have to watch the year go by with the green vine filling up... It's boring. I just want to get back to my family and making decisions.