Knowledge in science is a socially constructed phenomena. As Driver et. Al (1994) note, the language of science is not that of observing natural phenomena, but it is instead the language of the constructions which we use to explain it. There is no equation of force sitting out there in nature. It is a construction based on our observations of our environment. More over, it has been negotiated by generations of scientist into the form of F=MA that we see today.
We must acknowledge that such complex social constructions are not available in the environment for our students to simply access. We can lead them to the data that generated them, and they may recognize patterns within it, but the specific language of science must be learned through a process of cognitive apprenticeship and enculturation into the values and language of the discipline. As science educators, we can begin this process by modelling the believes, language, and processes of the scientific community for our students.
Within networked communities, participants engage in the ongoing construction of knowledge and meaning within a discipline. These communities are often a combination of students, amateur enthusiasts, and professionals. Each group can meaningfully contribute to the ongoing dialogue of the field. Students pose questions and may link ideas to novel metaphors and models. Amateur enthusiasts may find novel processes that reduce cost and barriers to entry. Professional have a wealth of knowledge and experience to share but might also be able to crowd source data and ideas to advance a given field.
To illustrate the above, let’s consider the Scratch programming environment. In this free, web-based, programming environment any of the above categories of participants are able to create programs with relative easy by using a drag and drop interface. Projects are readily shared throughout the community and Scratch enables commenting on, favouriting, and remixing of projects. The coding of each project is readily viewable by all participants and often provides scaffolding for more novice programmers to use to create their own projects. Complex projects may be designed by expert programmers but can be explored by novices. Forums allow novices to seek advice or for groups to collaborate together on a single project.
Driver, R., Asoko, H., Leach, J., Scott, P., & Mortimer, E. (1994). Constructing scientific knowledge in the classroom. Educational researcher, 23(7), 5-12.
I really liked your point that, ” Within networked communities, participants engage in the ongoing construction of knowledge and meaning within a discipline. These communities are often a combination of students, amateur enthusiasts, and professionals.”. I think through the sharing of ideas that these networked communtities can construct knowledge in may ways, and one way in through reflecting on what is proposed and perhaps adding to these ideas or questioning them for possible misconceptions. I think even within netwroked communities (an perhaps especially within them) critical thinking is an important component as the variety of viewpoints may lead some towards misconception if the ideas are taken “carte blanche” without reflection or further investigation. Are amateur enthusiasts viewed as less relaible as proferssionals and is this misleading? Do we trust or havefaith in one knowledge builder over another due to status and is this prudent? Does a “professional” necessarily have more clout than an amateur enthusiast for example. I wonder if we are teaching students the specific skills in order to be sound critical thinkers or if we are expecting it to happen organically through trial and error? Just a thought. Thank you for your comments.
To address you question of who we see as reliable in netwroked communities, I think it is important to recognize that, most of the time, it is not readily apparent what an individuals professional standing is. As such, critical thinking is certainly important. It is up to the user in a networked community to assess the value of any information they receive. Credentials can certainly make us more will to take someone at their word, but the true determinant of the value of information in a networked community seems to simply be “does it work?”.
I liked reading about your Scratch connection. I am enjoying delving into that new realm (new for me anyways!) with my students this year and watching them explore, create, and build on the ideas of others adding their own personal flair. I also appreciate how the Scratch learning community is setup and think their tutorials provide a great structure to get students started building with enough options to personalize their creations throughout. It has been really meaningful for me to watch leaders emerge in my class during our time with Scratch who are not traditional leaders in our classroom in other subjects. Even some students who seem to be struggling with math or at least not on the top are better understanding degrees, angles, and space (x, y) than some of my students who I thought would better understand these concepts. I created some screencasts with a few of my students talking about their creations in Scratch and the benefits of pair programming. You can see my post here: http://mrskostiuksclass.edublogs.org/2017/03/16/how-to-scratch-videos/ if you are interested!
I have encountered the same thing with unlikely leaders. It seems that scratch really helps students to shine when they use trail and error approaches and rapid, iterative, prototyping. The traditionally strong math students tend to be cautious and deliberate. As such, their projects can be more constrained and might make use of fewer of the more interesting features.
Scratch appears to be a really interesting sandbox space where students are able to dive in, try things out and emerge with a tangible product. You differentiate that students use either trial and error versus more deliberate math based methods of interacting with the program. I’m curious to know your thoughts on the teacher’s role in guiding students to use the program.
Should the teacher instruct students to specifically use the trial and error method and to shy away from applying mathematics?
Or rather should the teacher simply stand back and let students explore as they wish even when knowing that the trial and error method often yields better results in the end?
I think this is a great case for “just-in-time” teaching. I like to have my students grapple with a problema nd see what they come up with. I provide hints, tips, and short cuts for scratch as they start hitting dead ends.
You mention that Scratch projects are readily available for remixing. This feature of the Scratch community is one of its social affordances for learning in a networked environment. I wonder in what ways do you envision, within the TELE that “the specific language of science must be learned through a process of cognitive apprenticeship and enculturation into the values and language of the discipline?” I liked your example of “citizen science” or amateur enthusiasts who contribute to the construction of scientific knowledge as well as students who ask questions and may make novel links. Thank you for discussing Driver in the context of Scratch.
Also, if communities of learners, cognitive apprenticeship, and enculturation into the scientific community of practice are of interest class, please check out interesting reads from Lave and Wengner, Brown and Campione, and Barbara Rogoff’s work.
In terms of science specifically, the inquiry method of problem solving seems like a gateway to scientific thinking. This would need to be developed into explaining with evidence, proving the reliability of your data/source, and formulating new lines of inquiry.
In the elementary setting, especially with th egrade 6 evidence and invesitgation unit, the analogy to a detective might be useful. A mock trail could be set up where students must argue for their intepretation using convincing evidence. The pack and forth between “prosection” and “defense” might serve as an interesting starting point for metacognitive development around questioning one’s own assumptions, biases, and methods.
I did have an opportunity to read some of Brown’s work one of my previous core courses (situated cognition and cognitive apprenticeship were the main topics.) I found it particularly resonant in an age where students are constantly questioning “when will I ever use this”. If we can introduce students to the discourse of a field early, it might be much easier for them to come to understanding the relevance of different tools and ways of thinking ot that field.