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Diagnostics and rubrics for assessing learning across the computational science curriculum

Authors:	J Russell Manson Robert J Olsen

Institution:	1. Escuela Superior de Ingeniería, The Basque Country University (EHU), Bilbao, Spain;2. Electrical & Computer Engineering, Christian Brothers University (CBU), Memphis, TN, USA;3. Instituto Colombiano de Aprendizaje (INCAP), Bogotá, Colombia;1. Media, Technology, and Society Program, Northwestern University, USA;2. Department of Communication Studies, Northwestern University, USA;1. University of Miami, United States;2. University of Utah, United States;3. Peking University, China;1. EPSH, Universidad de Zaragoza, Carretera de Cuarte s/n, 22071 Huesca, Spain;2. jeKnowledge, Universidade de Coimbra, Rua Larga, P-3004-516, Coimbra, Portugal;3. CFisUC, Department of Physics, Universidade de Coimbra, Rua Larga, P-3004-516, Coimbra, Portugal;4. Biomedical Institute for Research on Light and Image, IBILI, Universidade de Coimbra, Azinhaga Santa Comba, Celas, 3000-548, Coimbra, Portugal

Abstract:	We describe our experiences with learning assessment in a new computational science program. We report on the development and pilot testing of assessment tools in both core and cognate courses. Specifically, we detail a diagnostic assessment that predicted success in our introductory computational science course with reasonable reliability; we give an account of our use of an existing assessment tool to investigate how introducing computational thinking in a cognate course influences learning of the traditional course material; and we discuss rubric development for project evaluation.

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