1/26 Joey: Modeling Practices in Practice

1/26 Blog Post (Joey Tedeschi)

            In the first chapter of Changing Minds, diSessa delves into unpacking the term literacy, and what it means in a traditional way versus what computational literacy might mean.  diSessa goes on to talk about the three pillars of literacy: material, mental (cognitive), and social.  The material pillar of literacy includes understanding that literacy involves external symbols, signs, depictions and representations.  She mentions the vast range of inscription forms computer technology offers as well (spreadsheets, pictures, game interfaces, CD’s, DVD’s, etc.). The mental pillar suggests that the material pillar would be useless without a way to think and interact with inscriptions via our minds.  The social pillar suggests literacy is very socially constructed and certain types of inscriptions are only implemented into society if there is a great need or benefit for them.  diSessa then goes on to talk about Galileo and how the addition of algebra into our society (a new inscription system) has helped us understand calculus by simplifying (and building on) what Galileo had written. diSesa then touches on more social niches in regards to literacy.

            Nersessian’s research paper focused on modeling practices in an ethnographic study of a neural engineering research lab.  The paper really highlighted the dynamic and social nature of the model-based reasoning process.  The conceptual innovation observed throughout the paper stems from many different models (conceptual, physical, and computational) developed by a team of unique scientists.  The team wanted to create a simulation device in vitro that can serve as a very good model to predict certain phenomena in vivo (specifically dealing with neurons).  Along the way to creating this device, there were many different phases of investigation, models created, social interactions, collaboration, revisions, and analyses involved.  The paper gave a great overview of how scientific practices are implemented in the real scientific community.

Going back to the NGSS framework, there were 8 practices deemed essential for the K-12 science and engineering curriculum.  These included:

1. Asking questions (for science) and defining problems (for engineering)

2. Developing and using models

3. Planning and carrying out investigations

4. Analyzing and interpreting data

5. Using mathematics and computational thinking

6. Constructing explanations (for science) and designing solutions (for 
engineering)

7. Engaging in argument from evidence

8. Obtaining, evaluating, and communicating information

    I would say that in Nersessian’s paper every single one of these practices were prominently involved throughout the research.  The researchers had a question about neurons and defined a problem to solve.  How can we use technology to build and better understand “a living neural network”?  They developed multiple models (conceptual, physical, computational) to help represent the phenomena and system in question.  They planned and carried out many investigations, analyzed the data and made tweaks to fix problems.  Math and computational thinking were involved in the construction of models and designing solutions.  The researchers were constantly constructing explanations and designing solutions.  Along the way they would use data and other resources to argue using evidence.  As many different researchers came together to complete the solution; they obtained, evaluated, and communicated information to each other along the way.  Also, by having this research published, this information was communicated to me as well.

    I would say that diSessa was most focused on the practice of communicating information, specifically about literacy and its different aspects.  However, in this chapter she asked questions in regards to literacy, planned and carried out an investigation into Galileo’s theories, and constructed explanations for what he meant and how a modern reader might interpret Galileo’s writing.  Math and computational thinking was definitely involved when she reproduced Galileo’s proof of Theorem 1 with algebra.  She engaged in argumentation by giving evidence of how a new inscription system can drastically change how we look at things.  She did this by using Galileo and how algebra has changed our interaction with calculus.  She also comments on how important systematic representational systems can be in aiding discovery (by allowing abstract patterns be converted into spatial, visible ones).

    Although the two readings were very different in regards to content (neuroscience research vs. literacy discussion), I found it very intriguing that both of the authors used or referenced the 8 practices in one-way or another.  This really shows how dynamic these practices can be!