Building tools to help students learn to program

作者: Philip Guo

DOI: 10.1145/3148245

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参考文章(16)
Philip J. Guo, Online python tutor Proceeding of the 44th ACM technical symposium on Computer science education - SIGCSE '13. pp. 579- 584 ,(2013) , 10.1145/2445196.2445368
Joyce Zhu, Jeremy Warner, Mitchell Gordon, Jeffery White, Renan Zanelatto, Philip J. Guo, Toward a domain-specific visual discussion forum for learning computer programming: An empirical study of a popular MOOC forum symposium on visual languages and human-centric computing. pp. 101- 109 ,(2015) , 10.1109/VLHCC.2015.7357204
Philip J. Guo, Jeffery White, Renan Zanelatto, Codechella: Multi-user program visualizations for real-time tutoring and collaborative learning symposium on visual languages and human-centric computing. pp. 79- 87 ,(2015) , 10.1109/VLHCC.2015.7357201
Mitchell Gordon, Philip J. Guo, Codepourri: Creating visual coding tutorials using a volunteer crowd of learners symposium on visual languages and human-centric computing. pp. 13- 21 ,(2015) , 10.1109/VLHCC.2015.7357193
Parmit K. Chilana, Celena Alcock, Shruti Dembla, Anson Ho, Ada Hurst, Brett Armstrong, Philip J. Guo, Perceptions of non-CS majors in intro programming: The rise of the conversational programmer symposium on visual languages and human-centric computing. pp. 251- 259 ,(2015) , 10.1109/VLHCC.2015.7357224
Philip J. Guo, Codeopticon: Real-Time, One-To-Many Human Tutoring for Computer Programming user interface software and technology. pp. 599- 608 ,(2015) , 10.1145/2807442.2807469
Parmit K. Chilana, Rishabh Singh, Philip J. Guo, Understanding Conversational Programmers: A Perspective from the Software Industry human factors in computing systems. pp. 1462- 1472 ,(2016) , 10.1145/2858036.2858323
Denae Ford, Justin Smith, Philip J. Guo, Chris Parnin, Paradise unplugged: identifying barriers for female participation on stack overflow foundations of software engineering. pp. 846- 857 ,(2016) , 10.1145/2950290.2950331
Philip J. Guo, John Doorenbos, Bradley Miller, Jeremy Warner, How High School, College, and Online Students Differentially Engage with an Interactive Digital Textbook. educational data mining. pp. 528- 531 ,(2015)