Human vs. Automated Coding Style Grading in Computing Education | Zendy

James Perretta | Zendy; Westley Weimer | Zendy; Andrew DeOrio | Zendy

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Human vs. Automated Coding Style Grading in Computing Education

Author(s) -

James Perretta,

Westley Weimer,

Andrew DeOrio

Publication year - 2020

Publication title -

papers on engineering education repository (american society for engineering education)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.18260/1-2--32906

Subject(s) - grading (engineering) , rubric , computer science , static analysis , coding (social sciences) , style analysis , style sheet , style (visual arts) , natural language processing , artificial intelligence , programming language , mathematics education , psychology , statistics , engineering , world wide web , mathematics , civil engineering , archaeology , history , investment management , incentive , xml , microeconomics , economics

Andrew DeOrio is a teaching faculty member at the University of Michigan and a consultant for web and machine learning projects. His research interests are in ensuring the correctness of computer systems, including medical and IOT devices and digital hardware, as well as engineering education. In addition to teaching software and hardware courses, he teaches Creative Process and works with students on technology-driven creative projects. His teaching has been recognized with the Provost’s Teaching Innovation Prize, and he has twice been named Professor of the Year by the students in his department.

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