<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>A Typology of Models for Integrating Computational Thinking in Science (CT+S)</dc:title><dc:creator>Krakowski, Ari; Greenwald, Eric; Duke, Jake; Comstock, Meghan; Roman, Natalie</dc:creator><dc:corporate_author/><dc:editor>null</dc:editor><dc:description>In order to expand opportunities to learn computer science (CS),there is a growing push for inclusion of CS concepts and  practices,  such  as  computational  thinking  (CT),  in  required subjects  like  science.  Integrated,  transdisciplinary  (CS/CT+X) approaches have shown promise for broadening access to CS and CT learning opportunities, addressing potential self-selection bias associated with elective CS coursework and afterschool programs, and promotinga more expansive and authentic contextualization of   CS   work.   Emerging   research   also   points   to   pedagogical strategies  that  can  transcend  simply  broadening  access,  by  also working    to    confront    barriers    to    equitable   and   inclusive engagement in CS. Yet, approaches to integration vary widely, and there is little consensus on whether and how different models for CS and CT integration contribute to desired outcomes. There has also  been  little  theory  development  that  can  ground  systematic examination of the affordances and tradeoffs of different models. Toward that end, we propose a typology through which to examine CT  integration  in  science  (CT+S).  The  purpose  of  delineating  a typology   of   CT+S   integration   is   to   encourage   instantiation, implementation,    and    inspection    of    different    models    for integration, and to promote shared understanding among learning designers,    researchers,    and    practitioners    working    at    the intersection of CT and science. For each model in the typology, we characterize  how  CT+S integration  is  accomplished, the  ways in which CT learning supports science learning, and the affordances and   tensions for   equity   and   inclusion that   may   arise   upon implementation in science classrooms.</dc:description><dc:publisher/><dc:date>2021-05-25</dc:date><dc:nsf_par_id>10233641</dc:nsf_par_id><dc:journal_name>RESPECT 2021: IEEE STCBP Conference for Research on Equity and Sustained Participation in Engineering, Computing, and Technology</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/</dc:doi><dcq:identifierAwardId>1657002</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>