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You searched for +publisher:"Rice University" +contributor:("Warren, Joe D."). Showing records 1 – 2 of 2 total matches.

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Rice University

1. Tang, Lei. Data-Driven Tools for Introductory Computer Science Education.

Degree: PhD, Engineering, 2018, Rice University

The software industry spends a tremendous amount of effort and resources on software testing and maintenance to improve the quality of software. However, a large portion of the cost may be saved by training high-quality software developers with better Computer Science education. Skilled software developers can not only produce code of fewer bugs and better design but also identify and fix issues more effectively. Therefore, in this thesis, we researched building useful educational tools for facilitating Computer Science education, particularly in introductory programming courses. Since understanding the code execution is the first step of writing high-quality code and software testing, in the first study, we built a web-based interactive tool to teach students necessary comprehension and analysis skills to understand the program execution. Secondly, we built an automated tool for students to interactively practice writing test cases and debugging programs. The tool gauges the test coverage of students' test sets using a large corpus of buggy programs we collected in our previous course sessions. The tool returns the buggy programs as immediate feedback which students' test sets failed to catch. Students need to study those returned buggy programs to gradually improve the testing coverage of their test sets. In the third project, we built a tool that automatically generates high-quality test cases to construct concise test sets for testing students' coding assignment solutions. The tool utilizes heterogeneous historical student incorrect implementations to guide the test case search process. Its generated test cases are expected to provide better test coverage than instructor built tests cases. To validate the effectiveness of our tools, we conducted studies in introductory programming courses among students at Rice and online students of our Massive Open Online Courses (MOOC). The studies showed that, compared with studying traditional Computer Science curriculum, students made significant improvements in understanding basic Computer Science concepts and software testing skills by interacting with our educational tools. Advisors/Committee Members: Warren, Joe D. (advisor).

Subjects/Keywords: Computer Science Education; Interactive Learning; Software Testing; Visualization; Web-based Tool; Automatic Test Case Generation; Data-Driven; Automated Programming Assessment System

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tang, L. (2018). Data-Driven Tools for Introductory Computer Science Education. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/105845

Chicago Manual of Style (16th Edition):

Tang, Lei. “Data-Driven Tools for Introductory Computer Science Education.” 2018. Doctoral Dissertation, Rice University. Accessed November 17, 2019. http://hdl.handle.net/1911/105845.

MLA Handbook (7th Edition):

Tang, Lei. “Data-Driven Tools for Introductory Computer Science Education.” 2018. Web. 17 Nov 2019.

Vancouver:

Tang L. Data-Driven Tools for Introductory Computer Science Education. [Internet] [Doctoral dissertation]. Rice University; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1911/105845.

Council of Science Editors:

Tang L. Data-Driven Tools for Introductory Computer Science Education. [Doctoral Dissertation]. Rice University; 2018. Available from: http://hdl.handle.net/1911/105845


Rice University

2. Qiu, Kunfeng. Exporting, Converting and Importing Between Learning Management Systems.

Degree: MS, Engineering, 2016, Rice University

Learning Management Systems (LMS) are ubiquitous in higher education. In addition to the traditional LMSs used inside schools, Massive Open Online Course (MOOC) platforms, such as Coursera and edX, are forming a new generation of LMSs. The ongoing changes in platforms force instructors to frequently migrate their course content from one LMS to another. In 2015-2016, Rice University migrated content of open-enrollment online courses on Coursera to on-campus courses hosted on Canvas. Such migrations are not easy tasks. There is neither a standard structure for LMSs, nor a standard format for content stored in an LMS. Different LMSs have different features and data formats. This research presents a migration tool that automatically downloads and migrates the whole course, including wiki pages, videos, quizzes and assignments, from Coursera to Canvas. Advisors/Committee Members: Warren, Joe D (advisor).

Subjects/Keywords: LMS; Coursera; Canvas; migration; XML; JSON

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Qiu, K. (2016). Exporting, Converting and Importing Between Learning Management Systems. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/95998

Chicago Manual of Style (16th Edition):

Qiu, Kunfeng. “Exporting, Converting and Importing Between Learning Management Systems.” 2016. Masters Thesis, Rice University. Accessed November 17, 2019. http://hdl.handle.net/1911/95998.

MLA Handbook (7th Edition):

Qiu, Kunfeng. “Exporting, Converting and Importing Between Learning Management Systems.” 2016. Web. 17 Nov 2019.

Vancouver:

Qiu K. Exporting, Converting and Importing Between Learning Management Systems. [Internet] [Masters thesis]. Rice University; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1911/95998.

Council of Science Editors:

Qiu K. Exporting, Converting and Importing Between Learning Management Systems. [Masters Thesis]. Rice University; 2016. Available from: http://hdl.handle.net/1911/95998

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