The Present and Future of Computational Thinking Computational
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The Present and Future of Computational Thinking: Computational Thinking Across the Curriculum Amber Settle, De. Paul University Co-PI: Ljubomir Perkovic The 40 th ACM Technical Symposium on Computer Science Education (SIGCSE 2009) March 7, 2009 Work supported by the National Science Foundation
Goals l Long term goal – l Incorporate computational thinking in courses across the liberal arts curriculum Project goals 1. 2. 3. 4. Develop a framework that will be used by instructors outside of information technology to understand integrate computational thinking into their courses Improve understanding of computational thinking Improve likelihood of buy-in by non-IT faculty Develop a community of educators across institutions that will implement the framework and the necessary institutional changes
Participants l Institutions: – – l De. Paul University Other Chicago-area colleges (including the Illinois Institute of Technology and the City Colleges of Chicago) By year: – – First year: School of Computing (So. C) and School of Cinema and Interactive Media (CIM) in College of Computing and Digital Media Second year: So. C and CIM plus College of Liberal Arts and Sciences (History, Anthropology), College of Commerce, and other Chicago-area institutions
First Year l Initial framework – – – l Analyze select courses and categorize computational thinking examples, starting with Denning’s Great Principles of Computing Develop course-specific computational thinking learning goals Develop assessment tools that evaluate the computational thinking learning goals Enhancement of existing courses – Five from SOC: CSC 233: Codes and Ciphers; CSC 235: Problem Solving; CSC 239: Personal Computing; ECT 250: Internet, Commerce, and Society; IT 130: The Internet and the Web – Four from CIM: ANI 201: Introduction to Visual Design; ANI 230: Modeling for Animation and Gaming; DC 201: Introduction to Screenwriting; HCI 201: Multimedia and the World Wide Web – One joint between CIM/SOC: GAM 224: Introduction to Game Design
Examples of computational thinking l Automation – – – l Computation – – l Defining sub-goals and recursive thinking (CSC 235) Randomization of grass blades in a field (ANI 230) Design – – l Action and batch processing (ANI 201) Airline order processing system (ECT 250) Grass field generation (ANI 230) Abstracting properties into classes (HCI 201) Structure of screenplays (DC 201) Evaluation – – Constructing a histogram and visualizing data (CSC 239) Image filters in bitmapped texturing as a forecasting system (ANI 230)
Examples of learning goals l l CSC 239 (Evaluation): Students can use a statistics package to generate multiple histograms from a single data set and can choose the most meaningful visualization of the symmetry or skew of the data HCI 201(Design): Students can identify a group of (e. g. visual) elements that should all have the same property and abstract them into a class; they should then be able to specify class-wide (e. g. visual) properties that achieve the desired uniformity of the visual elements.
