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CloudCoder

Publisher GitHub
Description CloudCoder is an open source web-based programming exercise system (inspired by CodingBat). It is designed to make it easy for instructors of introductory programming courses to assign short exercises to students for skills development and assessment. Currently, exercises in C/C++, Java, Python, and Ruby are supported.
Resource Type URL
Data Type Programming
Creator Spacco, Jaime; Hovemeyer, David; Bonner, Shane; Lefever, Jason; Garcia, Sat; Mount, Sarah
Availability by request
Programming Language Python
Publication Year 2013
Number of Semesters 4
Data Protection Anonymized
Population CS-1
Sample Size ~430
Country USA
Educational Institution Duke
Learning Environment ITAP
Aggregation Yes
Aggregation Level Keystrokes
Related Publication @article{10.5555/2400161.2400167, author = {Hovemeyer, David and Spacco, Jaime}, title = {CloudCoder: A Web-Based Programming Exercise System}, year = {2013}, issue_date = {January 2013}, publisher = {Consortium for Computing Sciences in Colleges}, address = {Evansville, IN, USA}, volume = {28}, number = {3}, issn = {1937-4771}, abstract = {CloudCoder is a web-based programming exercise system designed for introductory programming courses. Using CloudCoder, instructors can assign practice problems to reinforce concepts and assess mastery of skills. Students access their assigned problems using a web browser. A typical problem asks the student to write a function or complete program to perform a simple task such as classifying input or performing a computation on input data. When the student submits her solution to a problem, the server tests her code against a series of test cases designed by the instructor and reports which tests executed correctly. CloudCoder is inspired by existing systems such as Codingbat, but is designed to be installed and used widely. As such, CloudCoder is open source (https://github.com/daveho/CloudCoder) and supports programming exercises in multiple languages (currently C, Java, and Python).}, journal = {J. Comput. Sci. Coll.}, month = {jan}, pages = {30}, numpages = {1} }
Fairness Score Total score: 4% (initial) Findability: 1 of 7 Accessibility: 0 of 3 Interoperability: 0 of 4 Reusability: 0 of 10
ResourceOpen Dataset