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Aligning Ideas and Models in Cognition & Instruction
Computational tools hold promise science education, but each tool has a different way of representing information. This paper describes ontological alignment, ways to connect what students know, and how agent-based models represent scientific systems.
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Sci Educ: When Models are “Right but Wrong”
Agent-based modeling can get students thinking about mechanism. But to get students refining their models toward accurate explanations, comparing models with data is just as important.
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Exploring Local Impacts and Global Change w/ Data
A new paper describes one of the units developed as part of the Writing Data Stories project, focused on connecting the local and global effects of climate change through storytelling and data.
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Jia Xin Sun
I am a MA student and middle school science teacher interested in curriculum design. My work is on developing a framework for integrating data practices into STEM curriculum.
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Naomi Yonas
Hi! I am Naomi Yonas (she/her/hers)! I am a third-year undergraduate student studying Electrical Engineering & Computer Science at UC Berkeley.
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Brendan Henrique
My research explores critically conscious STEM education with special attention to computer science education.
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Kyla Kemble
Kyla is a 3rd year School Psychology Ph.D. student. Her research interests concern culturally responsive practices in mathematics classrooms and teacher implicit bias training.
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Zohal Shah
Zohal is a Ph.D. student. Through a collaborative approach, she aspires to understand how youth develop critical data and digital literacies through social and civic online engagement.
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Jacob Barton
After leading outdoor education trips in Colorado and Alaska, Jake started as a HS science teacher, soccer coach, and director of sustainability. He is currently a Doctoral student at Berkeley.
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John Kim
John Kim MS CCC-SLP, ATACP (he/him) is a doctoral student in the Joint Doctoral program at San Francisco State University (SFSU) & UC Berkeley in Special Education.
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