I was rather perturbed by a component of the CTSiM model. In
particular, I was bothered by the part where students compare their model to an
“expert” model. I appreciate that up until that point students had been doing
their own thinking and creating. It appears that there is a good amount of
scaffolding in building the individual agents and that there is an easeful way
for students to see the connections between their code and the visualization.
But then, they compare their model to an expert model, and if they are not
getting the same results, they go back and fix their model. It smacked of
students trying to get the “right” predetermined answer. I can imagine a
student doing all the work to build their model and then when it doesn’t produce
the same results as the expert’s, they ask, ‘why am I building a model in the first place?’
Early on we read a paper by Papert that discussed false
discovery. False discoveries involved a tension between true discovery and
creation and a process in which something was created, but there existed a
right and wrong way in which to discover it. I’ve also been reading papers for
another class in which the author’s strongly suggest and support students as
the intellectual authorities. That in order to have meaningful classroom
discourse and learning, the teacher should not be the authority on right or
wrong answers. Rather, the teacher should help build a community in which
students are able to rigorously critique ideas and answers to determine their
correctness. Now, these papers were discussing math classes, thus the students
rely on the logic of previously learned mathematics to investigate their
methods and answers. Possibly, this is harder to reproduce in science
classrooms because the real world is a bit “messy.” In science one often deals
with generalities and likely scenarios that model the world. For example, I
recently observed a class in which students were programming small ball robots.
The teacher discussed the fact that while a computer, when given a program,
will exactly execute that program, the Sphero robot, may appear to incorrectly follow the programmed instructions. This was due
in part to the roughness or cant of the surface, and other irregularities in
the robot or experimental environment.
So perhaps students cannot determine the correctness of their
science model based on what they previously knew about science. Thus, they need
some source with which to compare or with which to think about their results.
But why does that source have to be an expert’s model? Why couldn’t it be a
comparison between the whole class’s models? If two students got different
results, why couldn’t they discuss and compare between them and then debug? If
the class compares their models and they come to an incorrect conclusion, then
I believe the teacher needs to help them investigate their conclusion.
Additionally, the expert model models a real situation, so transitively
students are comparing to the real world. But I don’t see that being clear to
the student. And to the skeptical student, it may seem that a) the problem has
already been solved or b) that the “expertness” of the model has not been
determined.
I think this comes too close to programming the child
instead of the child programming. There will be many situations in which no
“right answer” is provided, school should help them gain the knowledge and
skills to negotiate those situations.
Ruth, the points you raised are really great! First of all, I think there are definite needs of goals when students are in the task of learning. Without having specific goals students may not be motivated enough to explore and find the correct or optimum solution. This does not mean that students would need to build the exact model given as the expert model but means they would need to build “a” model for the scenario given. But I think the options to let students discuss and compare the results they got would certainly help them learning about different issues related with the task given which they themselves may not run into. One interesting fact about it is that sometimes due to honor codes students are not allowed to talk about solutions. I would like to know what the point is for it - is it to make sure that the student’s grades would be well distributed on the grade graph? What is wrong if the students discussed and got similar solutions? May be it is harder to assess if they have really explored enough for the concept that way. Anyways, as you pointed the need of instruction from teachers to help them investigate further on the incorrect conclusion, I think that is part of the reason why expert models are provided to assess student’s model and to provide them with the required scaffolding.
ReplyDeleteI agree that comparing the students' models to an expert model can detract from the creative and imaginative environment that programming tries to promote. I think this has to do with the hesitancy and difficulty that society has with dealing with the unknown. I recently came across this article titled "Embracing the Unknown in Radiology Education". It essentially describes how most of medical education focuses on teaching the known, particularly the content that is tested on standardized board exams. The authors push for a change in teaching method to focus on the unknown, like presenting cases with no definitive diagnosis or bringing good research questions. This experience can be uncomfortable for radiologists who are supposed to be considered experts in their field, but in today's technology-heavy world, wouldn't you rather have a doctor who knows exactly where to look or who to ask when they don't know the correct answer? Wouldn't you rather have someone who is able to think critically about what diagnostic tests or labs he will need to help him figure out the answer? If we can start embracing the unknown at a young age (like in these science classrooms), maybe future experts will experience less of this discomfort and continue engaging in lifelong learning!
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ReplyDeleteHi Ruth! This is also what I've been wondering. I don't think this question is specific to teaching computational thinking, but I think it's definitely a question worth paying serious attention to given that there is a tendency for a computer to be a black box. Why should I believe that anything on the computer has anything to do with the real world? I wonder I mean maybe expert models can be reframed as an agree-upon models given the experiments that people have done. Still, I wonder whether there can be a cycle of scientific inquiry that support students throughout the entire process. So far I haven't seen a good example of this connection in a design.
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