Hi Jodi,

We are still thinking about ways to use them as part of integrative analysis. right now, we use them in two main ways: First, as the main source of data for interaction analysis between the programming pairs and their game. The interaction analysis has focused on power dynamics in pair programming (this is nascent analysis), the kinds of systems thinking that the students are doing around climate change, and the ways in which students are spontaneously participating in critiquing each others games and offering/soliciting help/advice. Second, as qualitative analysis of student design choices along three lines: player interactions, mitigation topic, and the metagame (e.g. narrative, instructions). These are just our initial uses of the data. We also expect that the screen captures will help corroborate more quantitative looks at computational thinking and design choices and that we will delve deeper into micro-interactions between partners. 

Hi Barbara, that's cool stuff they have going on over there. What do you think is good about them that we could learn from? We mainly do research on student and teacher learning, the design of the curriculum is part of our research. Do you think there is something particular about their design that could enhance the experience of the teachers and young people in our project?

They also manly do teacher professional development and create curriculum.  I think it would certainly be worth talking to them to see what you might learn from them.  See http://www.bootstrapworld.org/community/index.s...  I would talk to Emmanuel Schanzer.

Hi Ben,

Students at different schools have had different experiences with climate and weather and climate change systems. But teachers are able to adapt the curriculum to their needs. In all about 5-7 days of class time is spent at the beginning learning about climate systems and climate change. Teachers do this in different ways. Originally, the goal of the project was to have students do all their learning about climate science while making their games and we provided access to various materials through a learning library, but we realized we needed to be more explicit about different components of systems (as opposed to simple causal chains) so we front loaded some of the content. After those first few days students begin learning what makes a good game and begin forays into the programming language through debugging activities. About the 11th day the students begin designing their games and they usually take about 10 class periods with some working on their games at home. That said, students come with all types of familiarity with Scratch and/or programming, but everyone is able to make some type of game. You can see some of them at buildingsystems.terc.edu 

Hi Jennie,

Thank you for your post and interest in our project  

For the website,  please try buildingsystems.terc.edu

In response to your question about our measurement to efficacy in computational thinking, our findings are suggested from our pre/post student survey. Our survey measures student self-efficacy, attitudes, and persistence in relation to game design, science, computing, and climate change. 

Hi Jenny

Try https://www.external-wiki.terc.edu/display/scratch

Hi Ben,

We are using Design-Based Research to iterate on and refine the model. We are currently in Year 2, but about the fourth iteration of the model, as our cooperating teachers have implemented at different times of year, we have been able to take information from our observations and tweak what we ask students to do. We use mixed methods to collect and analyze data. We use repeated analysis of variance on pre/post attitude/efficacy measurements as Mike outlined above as well as pre/post climate systems and computational thinking items. Qualitatively, we have selected one section from each of the teachers to observe. We select three focal pairs from classrooms to follow with screen capture/camera software as well as video tape whole class discussions and take fieldnotes daily. Teachers also keep implementation logs. Our research questions are related to the conjecture map (See Sandoval, 2014 in JLS) we iterate on as we refine the model. However, they are related to teacher take up, student learning, and the affordances and constraints of the participant structures, task structures, discourse practices, and tools and materials. For instance, we think students-as-experts positions students in productive and generative ways in classrooms and so we are studying how students seek each other out for help or spontaneously give feedback and help within the structure of our curriculum. Results are ongoing. Next year, we hope to conduct a quasi-experimental comparative study with about 15 8th grade teachers (60 classrooms).

Thank you Jenna.  It has been a privilege to work with extremely enthusiastic teachers, and engaged students.  We're learning a great deal!

Thank you, Bill.

Yes, our data (assessments and interviews) show that students not only benefit from their coding experience, but that they also know a great deal more than they are able to - or choose to - include in their final games.  If one thinks of student representations of aspects of climate science in their games as a form of modeling, they make careful choices of what science they want to include.  Creating a game to teach others is a complex task, and they are juggling the cognitive load of learning to program, learning the climate science, and conveying a message, all while trying to make an engaging experience for the player.  Professional designers of educational games struggle with this complex task!