Editing Online Communities (UW COM481 Fall 2024) (section)

=== Monday November 25: Challenges and Frontiers: Dr. Regina Cheng on Feedback, Learning, and Trust ===
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'''Guest:'''
* [https://reginachangzhou.github.io/ Ruijia Cheng, PhD] (Regina, 程瑞加)

'''Resources:'''

* [https://uw.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=906c9884-acaf-4b73-a49c-b236012f397d Class Video Recording] (Requires Canvas access) (''Note:'' This video is not from our class, but it's from another lecture that Dr. Cheng gave with almost the exact same content. It should be a useful substitute for anybody unable to attend the lecture.)

'''Class plan:'''

We will be joined in class by Dr. Regina Cheng. Dr. Cheng is a Research Scientist at Apple in the ''Human Centered Machine Intelligence (HCMI)'' group. She has published a number of papers about learning, feedback, and AI in online communities—three of the top topics that folks requested most frequently in the poll. Dr. Cheng received her PhD in 2023 in the [https://www.hcde.washington.edu/ Department of Human-Centered Design & Engineering at UW], and I was honored to serve as one of the co-advisors of her dissertation work. Dr Cheng tells me she plans to present work based on the three studies below.

'''Required readings:'''

Please read '''one of the three papers below'''. Feel free to pick whichever one you're most excited about:

* Cheng, Ruijia, Sayamindu Dasgupta, and Benjamin Mako Hill. 2022. “How Interest-Driven Content Creation Shapes Opportunities for Informal Learning in Scratch: A Case Study on Novices’ Use of Data Structures.” In ''Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems'', 1–16. CHI ’22. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3491102.3502124. {{avail-free|https://doi.org/10.1145/3491102.3502124}}
* Cheng, Ruijia, and Jenna Frens. 2022. “Feedback Exchange and Online Affinity: A Case Study of Online Fanfiction Writers.” ''Proceedings of the ACM: Human-Computer Interaction'' 6 (CSCW2): 402:1-402:29. https://doi.org/10.1145/3555127. {{avail-free|https://doi.org/10.1145/3555127}}
* Cheng, Ruijia, Ruotong Wang, Thomas Zimmermann, and Denae Ford. 2024. “‘It Would Work for Me Too’: How Online Communities Shape Software Developers’ Trust in AI-Powered Code Generation Tools.” ''ACM Transaction on Interactive Intelligent Systems'' 14 (2): 11:1-11:39. https://doi.org/10.1145/3651990. {{avail-free|https://doi.org/10.1145/3651990}}

There are no reading note this work or specific questions I want you to prepare answers to. Your assignment is to come prepared with two questions based on the paper you've read. We'll be ready to call people from the cold call list, so be ready!