Below is a collection of papers on three different topics. In conjunction with the reading academic papers assignment, pick 3 papers. For convenience, I have placed a copy of all of these papers in our Box folder. Remember we can collectively edit that folder, so grab a copy for yourself, don’t edit it directly in Box if you take notes.

Also, if you haven’t read the how to read an academic paper post lately, it’s been updated with some things to note to help interpolate that reading for the CER context.

Office Hours

Aaron J. Smith, Kristy Elizabeth Boyer, Jeffrey Forbes, Sarah Heckman, and Ketan Mayer-Patel. 2017. My Digital Hand: A Tool for Scaling Up One-to-One Peer Teaching in Support of Computer Science Learning. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE ’17). Association for Computing Machinery, New York, NY, USA, 549–554. DOI:https://doi.org/10.1145/3017680.3017800

Yanyan Ren, Shriram Krishnamurthi, and Kathi Fisler. 2019. What Help Do Students Seek in TA Office Hours? In Proceedings of the 2019 ACM Conference on International Computing Education Research (ICER ’19). Association for Computing Machinery, New York, NY, USA, 41–49. DOI:https://doi.org/10.1145/3291279.3339418

Undergrad TAs

Diba Mirza, Phillip T. Conrad, Christian Lloyd, Ziad Matni, and Arthur Gatin. 2019. Undergraduate Teaching Assistants in Computer Science: A Systematic Literature Review. In Proceedings of the 2019 ACM Conference on International Computing Education Research (ICER ’19). Association for Computing Machinery, New York, NY, USA, 31–40. DOI:https://doi.org/10.1145/3291279.3339422

Julia M. Markel and Philip J. Guo. 2021. Inside the Mind of a CS Undergraduate TA: A Firsthand Account of Undergraduate Peer Tutoring in Computer Labs. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education. Association for Computing Machinery, New York, NY, USA, 502–508. DOI:https://doi.org/10.1145/3408877.3432533

Formative Assessments

Neil C.C. Brown and Amjad Altadmri. 2014. Investigating novice programming mistakes: educator beliefs vs. student data. In Proceedings of the tenth annual conference on International computing education research (ICER ’14). Association for Computing Machinery, New York, NY, USA, 43–50. DOI:https://doi.org/10.1145/2632320.2632343

Simon and Susan Snowdon. 2014. Multiple-choice vs free-text code-explaining examination questions. In Proceedings of the 14th Koli Calling International Conference on Computing Education Research (Koli Calling ’14). Association for Computing Machinery, New York, NY, USA, 91–97. DOI:https://doi.org/10.1145/2674683.2674701

Kristin Stephens-Martinez, An Ju, Krishna Parashar, Regina Ongowarsito, Nikunj Jain, Sreesha Venkat, and Armando Fox. 2017. Taking Advantage of Scale by Analyzing Frequent Constructed-Response, Code Tracing Wrong Answers. In Proceedings of the 2017 ACM Conference on International Computing Education Research (ICER ’17). Association for Computing Machinery, New York, NY, USA, 56–64. DOI:https://doi.org/10.1145/3105726.3106188

Priscilla Lee and Soohyun Nam Liao. 2021. Targeting Metacognition by Incorporating Student-Reported Confidence Estimates on Self-Assessment Quizzes. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE ’21). Association for Computing Machinery, New York, NY, USA, 431–437. DOI:https://doi.org/10.1145/3408877.3432377

Shuchi Grover. 2021. Toward A Framework for Formative Assessment of Conceptual Learning in K-12 Computer Science Classrooms. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education. Association for Computing Machinery, New York, NY, USA, 31–37. DOI:https://doi.org/10.1145/3408877.3432460

Max Fowler, Binglin Chen, Sushmita Azad, Matthew West, and Craig Zilles. 2021. Autograding “Explain in Plain English” questions using NLP. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE ’21). Association for Computing Machinery, New York, NY, USA, 1163–1169. DOI:https://doi.org/10.1145/3408877.3432539

Max Fowler, Binglin Chen, and Craig Zilles. 2021. How should we ‘Explain in plain English’? Voices from the Community. In Proceedings of the 17th ACM Conference on International Computing Education Research (ICER 2021). Association for Computing Machinery, New York, NY, USA, 69–80. DOI:https://doi.org/10.1145/3446871.3469738