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Balancing Curricular and Pedagogical Needs in Computational Construction Kits: Lessons From the DeltaTick Project
Author(s) -
WILKERSONJERDE MICHELLE,
WAGH ADITI,
WILENSKY URI
Publication year - 2015
Publication title -
science education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.209
H-Index - 115
eISSN - 1098-237X
pISSN - 0036-8326
DOI - 10.1002/sce.21157
Subject(s) - computer science , mathematics education , netlogo , computational thinking , curriculum , science education , coding (social sciences) , domain (mathematical analysis) , pedagogy , psychology , programming language , sociology , mathematical analysis , social science , mathematics
To successfully integrate simulation and computational methods into K–12 STEM education, learning environments should be designed to help educators maintain balance between (a) addressing curricular content and practices and (b) attending to student knowledge and interests. We describe DeltaTick, a graphical simulation construction interface for the NetLogo modeling environment designed to make computational model construction a more accessible and responsive part of science and mathematics curricular activities through domain‐specific, customizable construction libraries. With DeltaTick, learners assemble and reassemble predefined sets of “behavior blocks” to build simulations that represent a particular domain of study. When needed, blocks can be added, adjusted, or replaced to better reflect student knowledge, interests, or questions. We present coding analyses and vignettes from DeltaTick enactments in middle and high school classrooms to illustrate ways these features allowed learners to explore core curricular ideas, while also accommodating emergent student or classroom needs. From these findings, we posit two principles, curricular example space and levels of responsivity , for the design of computational modeling environments intended for classrooms. We argue that this design approach can bring into better alignment the complex relationships between computational modeling activities, student knowledge, curricula, and teacher supports in K–12 classrooms.

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