Using Introductory Computer Science As A Tool For Teaching General Problem Solving

This study examines the collaborative processes the Chicago Alliance for Equity in Computer Science (CAFÉCS) uses to conduct and use research. The CAFÉCS RPP is a partnership between Chicago Public Schools (CPS), Loyola University Chicago, The Learning Partnership, DePaul University, and University of Illinois at Chicago. Data used in this analysis comes from three years of evaluation data, and includes an analysis of team documents, meeting observations, and interviews with 25 members of the CAFÉCS RPP team. The analysis examines how three problems are being investigated by the partnership: 1) student failure rate in an introductory computer science course, 2) teachers’ limited use of discussion techniques in an introductory computer science class, and 3) computer science teacher retention. Results from the analysis indicate that the RPP engages in a formalized problem-solving cycle. The problem-solving cycle includes the following steps: First, the Office of Computer Science (OCS) identifies a problem. Next, the CAFÉCS team brainstorms and prioritizes hypotheses to test. Next, data analysis clarifies the problem and the research findings are shared and interpreted by the entire team. Finally, the findings are used to inform OCS improvement strategies and next steps for the CAFÉCS research agenda. There are slight variations in the problem-solving cycle, depending on the stage of understanding of the problem, which has implications for the mode of research (e.g hypothesis testing, research and design, continuous improvement, or evaluation).

Download Full-text

Framework for Evaluating Learning from Computer Programming Courses: Problem Solving in an Introductory Computer Science Course

Empirical Foundations of Information and Software Science IV ◽

10.1007/978-1-4684-5472-7_39 ◽

1987 ◽

pp. 487-500

Author(s):

Aboalfazi Salimi

Keyword(s):

Problem Solving ◽

Computer Science ◽

Computer Programming ◽

Introductory Computer Science ◽

Programming Courses

Download Full-text

Algorithmic Puzzles

10.1093/oso/9780199740444.001.0001 ◽

2011 ◽

Cited By ~ 3

Author(s):

Anany Levitin ◽

Maria Levitin

Keyword(s):

Problem Solving ◽

Computer Science ◽

Algorithm Design ◽

Divide And Conquer ◽

Algorithmic Problem ◽

Design Strategies ◽

Job Interviews ◽

Skill Levels ◽

Problem Solving Skills ◽

Solution Methods

While many think of algorithms as specific to computer science, at its core algorithmic thinking is defined by the use of analytical logic to solve problems. This logic extends far beyond the realm of computer science and into the wide and entertaining world of puzzles. In Algorithmic Puzzles, Anany and Maria Levitin use many classic brainteasers as well as newer examples from job interviews with major corporations to show readers how to apply analytical thinking to solve puzzles requiring well-defined procedures. The book's unique collection of puzzles is supplemented with carefully developed tutorials on algorithm design strategies and analysis techniques intended to walk the reader step-by-step through the various approaches to algorithmic problem solving. Mastery of these strategies--exhaustive search, backtracking, and divide-and-conquer, among others--will aid the reader in solving not only the puzzles contained in this book, but also others encountered in interviews, puzzle collections, and throughout everyday life. Each of the 150 puzzles contains hints and solutions, along with commentary on the puzzle's origins and solution methods. The only book of its kind, Algorithmic Puzzles houses puzzles for all skill levels. Readers with only middle school mathematics will develop their algorithmic problem-solving skills through puzzles at the elementary level, while seasoned puzzle solvers will enjoy the challenge of thinking through more difficult puzzles.

Download Full-text