@caahayes So much to say about this but most importantly “how was this data processed?” Also, expanding to ask “who are these scientists” wouldn’t hurt. After all scientists like @EdGCMproject are always accessible ! #NSTAchat
@caahayes A8. Practicing how to make claims, provide supporting evidence, and reason about it can be done in various disciplinary contexts. Hence, I would suggest collaborating with colleagues in humanities and introducing this skill in various contexts. #NSTAchat
@caahayes A7. Using models- representations, mathematical, computer-based- that allow students to bring their prior knowledge, but then engage in analysis of data and then revisit their prior conceptions. #NSTAChat
@caahayes A6. How effectively were students able to understand the premise, how robust, data-based and logical their claims are. And above all, are students just depending on their prior knowledge or were they able to weave in what they learnt by their own analysis of data. #NSTAChat
@caahayes A5. Scientific pursuits do not happen in isolation. They are integral to students’ lives and societies. Hence, analyzing claims/data must be grounded in the context. What is the data about? How does it inform our society/lives? #NSTAchat
@caahayes A4. NOS can be emphasized by formulating evidence using various forms of investigations, being open to revising your claims when new data is obtained (something models are very capable of) #NSTAChat
@caahayes A3 2/2. Models can be the window to “Big Data” where patterns can be observed over long time periods and over large scales, thus helping phenomena/ideas that are abstract to become explicit. #NSTAchat
@caahayes A3. 1/2. Models- representations- physical/mathematical/conceptual- allow learners to visualize an abstract concept/phenomena. This visualization happens through the process of analyzing evidence
#NSTAchat
@caahayes A2. analyzing and assess the credibility of claims-what data were used to make that claim
How were these data collected, processed to form evidence?
Are their certain patterns in data that can be recognized?
Do these patterns help the learner reason about the premise?
#NSTAchat
@caahayes A1 Guiding learners to identify both the premise and the conclusion to a hypothesis/study/experiment.Organizing the data-based evidence such that argument is logical
#NSTAchat
Tonight we are discussing “Evaluating Science Claims” a featured focus in the 2020 October issue of the #NSTA The Science Teacher journal. Authors who contributed to the journal are joining us tonight to share ideas, ask questions, and support each other. #NSTAchat
Excited to be a part of the 2020 CADRE cohort. Looking forward to meet other fellows on April 2. @cadre12#DRK12 thank you @corytforbes for nominating me.
Thank you NSTA participants for your support and a stimulating discussion about models and climate literacy. @FrankNiepold thank you for your input. @corytforbes thanks for the opportunity. #NSTA19