<?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>Development of a Lean Computational Thinking Abilities Assessment for Middle Grades Students</dc:title><dc:creator>Wiebe, Eric; London, Jennifer; Aksit, Osman; Mott, Bradford W.; Boyer, Kristy Elizabeth; Lester, James C.</dc:creator><dc:corporate_author/><dc:editor/><dc:description>The recognition of middle grades as a critical juncture in CS education has led to the widespread development of CS curricula and integration efforts. The goal of many of these interventions is to develop a set of underlying abilities that has been termed computational thinking (CT). This goal presents a key challenge for assessing student learning: we must identify assessment items associated with an emergent understanding of key cognitive abilities underlying CT that avoid specialized knowledge of specific programming languages. In this work we explore the psychometric properties of assessment items appropriate for use with middle grades (US grades 6-8; ages 11-13) students. We also investigate whether these items measure a single ability dimension. Finally, we strive to recommend a "lean" set of items that can be completed in a single 50-minute class period and have high face validity. The paper makes the following contributions: 1) adds to the literature related to the emerging construct of CT, and its relationship to the existing CTt and Bebras instruments, and 2) offers a research-based CT assessment instrument for use by both researchers and educators in the field.</dc:description><dc:publisher/><dc:date>2019-02-27</dc:date><dc:nsf_par_id>10100678</dc:nsf_par_id><dc:journal_name>Proceedings of the 50th ACM Technical Symposium on Computer Science Education</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation>456 - 461</dc:page_range_or_elocation><dc:issn/><dc:isbn/><dc:doi>https://doi.org/10.1145/3287324.3287390</dc:doi><dcq:identifierAwardId>1640141; 1138497</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>