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Shi, Yang; Mao, Ye; Barnes, Tiffany; Chi, Min; Price, Thomas W. – International Educational Data Mining Society, 2021
Automatically detecting bugs in student program code is critical to enable formative feedback to help students pinpoint errors and resolve them. Deep learning models especially code2vec and ASTNN have shown great success for "large-scale" code classification. It is not clear, however, whether they can be effectively used for bug…
Descriptors: Artificial Intelligence, Program Effectiveness, Coding, Computer Science Education
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Dahlberg, Teresa; Barnes, Tiffany; Buch, Kim; Bean, Karen – Computer Science Education, 2010
This article describes a computer science course that uses service learning as a vehicle to accomplish a range of pedagogical and BPC (broadening participation in computing) goals: (1) to attract a diverse group of students and engage them in outreach to younger students to help build a diverse computer science pipeline, (2) to develop leadership…
Descriptors: Student Attitudes, Service Learning, Science Curriculum, Outreach Programs
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Dahlberg, Teresa; Barnes, Tiffany; Buch, Kim; Rorrer, Audrey – ACM Transactions on Computing Education, 2011
The Students and Technology in Academia, Research, and Service (STARS) Alliance is a nationally-connected system of regional partnerships among higher education, K-12 schools, industry and the community with a mission to broaden the participation of women, under-represented minorities and persons with disabilities in computing (BPC). Each regional…
Descriptors: Grade Point Average, Self Efficacy, Academic Achievement, Leadership