Pub Date : 2024-02-03DOI: 10.1016/j.compcom.2024.102830
Stacey Pigg
Research approaches that emphasize embodied practice and value the idiosyncratic uptake of writing technologies should be central to how writing researchers process the early moment of generative AI's availability to public audiences. Based on a qualitative analysis of 35 publicly available videos depicting the use of ChatGPT and Bing, the study offers a framework of descriptive codes that identify practices early adopters enact when integrating these technologies into research writing processes. The research contributes three key categories of practice that describe research writers’ interaction with generative AI across research design, writing research genres, and proofreading and editing: requesting, evaluating, and refining. This study is significant for providing an early descriptive analysis of the uptake of ChatGPT in research writing, while also identifying how disparate uses of generative AI technologies emerge from conflicting beliefs about writing, research, and invention. In particular, the study describes how experts in writing and research portray uses of and attitudes toward these technologies that often differ from students who are learning to research and write in their respective fields.
{"title":"Research writing with ChatGPT: A descriptive embodied practice framework","authors":"Stacey Pigg","doi":"10.1016/j.compcom.2024.102830","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102830","url":null,"abstract":"<div><p>Research approaches that emphasize embodied practice and value the idiosyncratic uptake of writing technologies should be central to how writing researchers process the early moment of generative AI's availability to public audiences. Based on a qualitative analysis of 35 publicly available videos depicting the use of ChatGPT and Bing, the study offers a framework of descriptive codes that identify practices early adopters enact when integrating these technologies into research writing processes. The research contributes three key categories of practice that describe research writers’ interaction with generative AI across research design, writing research genres, and proofreading and editing: <em>requesting, evaluating</em>, and <em>refining</em>. This study is significant for providing an early descriptive analysis of the uptake of ChatGPT in research writing, while also identifying how disparate uses of generative AI technologies emerge from conflicting beliefs about writing, research, and invention. In particular, the study describes how experts in writing and research portray uses of and attitudes toward these technologies that often differ from students who are learning to research and write in their respective fields.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000069/pdfft?md5=a5e337637caea208755dc6e247c71fc0&pid=1-s2.0-S8755461524000069-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139675398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-03DOI: 10.1016/j.compcom.2024.102831
Matthew A. Vetter , Brent Lucia , Jialei Jiang , Mahmoud Othman
Ethical frameworks for text generators (TGs) in education are generally concerned with personalized instruction, a dependency on data, biases in training data, academic integrity, and lack of creativity from students. While broad-level, institutional guidelines provide value in understanding the ethical dimensions of artificial intelligence (AI) for the classroom, there is a need for a more ecological understanding of how AI ethics might be constructed locally, one that takes into account the negotiation of AI between teacher and student. This article investigates how an educational ethical framework for AI use emerges through a qualitative case study of one composition student's interaction with and understanding of using ChatGPT as a type of writing partner. Analysis of interview data and student logs uncover what we term an emergent “local ethic” – a framework that is capable of exploring unique ethical considerations, values, and norms that develop at the most foundational unit of higher education – the individual classroom. Our framework is meant to provide a heuristic for other writing teacher-scholars as they interrogate issues related to pedagogy, student criticality, agency, reliability, and access within the context of powerful AI systems.
{"title":"Towards a framework for local interrogation of AI ethics: A case study on text generators, academic integrity, and composing with ChatGPT","authors":"Matthew A. Vetter , Brent Lucia , Jialei Jiang , Mahmoud Othman","doi":"10.1016/j.compcom.2024.102831","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102831","url":null,"abstract":"<div><p>Ethical frameworks for text generators (TGs) in education are generally concerned with personalized instruction, a dependency on data, biases in training data, academic integrity, and lack of creativity from students. While broad-level, institutional guidelines provide value in understanding the ethical dimensions of artificial intelligence (AI) for the classroom, there is a need for a more ecological understanding of how AI ethics might be constructed locally, one that takes into account the negotiation of AI between teacher and student. This article investigates how an educational ethical framework for AI use emerges through a qualitative case study of one composition student's interaction with and understanding of using ChatGPT as a type of writing partner. Analysis of interview data and student logs uncover what we term an emergent “local ethic” – a framework that is capable of exploring unique ethical considerations, values, and norms that develop at the most foundational unit of higher education – the individual classroom. Our framework is meant to provide a heuristic for other writing teacher-scholars as they interrogate issues related to pedagogy, student criticality, agency, reliability, and access within the context of powerful AI systems.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000070/pdfft?md5=ccba5f358a3dca6d3ecad3848e7405a0&pid=1-s2.0-S8755461524000070-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139675399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-03DOI: 10.1016/j.compcom.2024.102826
Alan M. Knowles
This article offers Rhetorical Load Sharing as a theoretical framework for placing texts on a collaborative authorship spectrum spanning from human-authored text to synthetic text. It poses human-in-the-loop writing as a baseline ethical AI collaborative writing workflow that avoids offloading the entire rhetorical load to generative AI tools and argues that machine-in-the-loop writing, in which human collaborators retain majority of the rhetorical load, is an ideal AI collaborative writing model that is suitable for the technical and professional communication classroom.
{"title":"Machine-in-the-loop writing: Optimizing the rhetorical load","authors":"Alan M. Knowles","doi":"10.1016/j.compcom.2024.102826","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102826","url":null,"abstract":"<div><p>This article offers Rhetorical Load Sharing as a theoretical framework for placing texts on a collaborative authorship spectrum spanning from human-authored text to synthetic text. It poses human-in-the-loop writing as a baseline ethical AI collaborative writing workflow that avoids offloading the entire rhetorical load to generative AI tools and argues that machine-in-the-loop writing, in which human collaborators retain majority of the rhetorical load, is an ideal AI collaborative writing model that is suitable for the technical and professional communication classroom.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000021/pdfft?md5=3ef282b93198c4044e3ed34a0f8f6612&pid=1-s2.0-S8755461524000021-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139675397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-03DOI: 10.1016/j.compcom.2024.102825
Ruth Li
In this paper, I investigate the ways human-AI collaboration could transform writing practices including feedback and revision. By closely examining an AI-generated essay, I expose potential gaps and contradictions in the essay and prompt ChatGPT to compose more nuanced writing. In inviting a dialectical negotiation with AI through iterative prompting and collaborative writing, I illuminate dissonances between content and style in the AI-generated essay. I proffer that interacting with AI language models can encourage students to engage critically with writerly choices by identifying instances in which AI-generated texts could consider alternative ideas or diverse perspectives. Ultimately, I contribute an innovative approach to collaborative storytelling with AI.
{"title":"A “Dance of storytelling”: Dissonances between substance and style in collaborative storytelling with AI","authors":"Ruth Li","doi":"10.1016/j.compcom.2024.102825","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102825","url":null,"abstract":"<div><p>In this paper, I investigate the ways human-AI collaboration could transform writing practices including feedback and revision. By closely examining an AI-generated essay, I expose potential gaps and contradictions in the essay and prompt ChatGPT to compose more nuanced writing. In inviting a dialectical negotiation with AI through iterative prompting and collaborative writing, I illuminate dissonances between content and style in the AI-generated essay. I proffer that interacting with AI language models can encourage students to engage critically with writerly choices by identifying instances in which AI-generated texts could consider alternative ideas or diverse perspectives. Ultimately, I contribute an innovative approach to collaborative storytelling with AI.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S875546152400001X/pdfft?md5=04ad86742c7804e381e679dfaa15282a&pid=1-s2.0-S875546152400001X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139675396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.1016/j.compcom.2024.102832
Anna Mills
{"title":"","authors":"Anna Mills","doi":"10.1016/j.compcom.2024.102832","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102832","url":null,"abstract":"","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000082/pdfft?md5=82b5b522b4971e076d20c8e5f66c9858&pid=1-s2.0-S8755461524000082-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139674330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-31DOI: 10.1016/j.compcom.2024.102834
Nupoor Ranade, Douglas Eyman
{"title":"Introduction: Composing with generative AI","authors":"Nupoor Ranade, Douglas Eyman","doi":"10.1016/j.compcom.2024.102834","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102834","url":null,"abstract":"","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000100/pdfft?md5=5b004ce9d1aa8bc5a54c9421e2019755&pid=1-s2.0-S8755461524000100-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139653337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-25DOI: 10.1016/j.compcom.2024.102829
Daniel L. Hocutt
This study introduces online advertising platforms as digital composing tools where persuasive rhetoric encourages users to follow links and take action on landing pages. It frames these platforms as digital spaces where human actors work alongside non-human AI agents (Duin & Pedersen, 2021 & 2023) and where rhetorical agency emerges through the activity of machine learning and artificial intelligence. It theorizes a (human) user-centered approach to composing digital ads in digital advertising platforms built around Walton, Moore & Jones’ (2019) framework of positionality, position, and power. It provides guidance for technical and professional writers in placing human users at the center of an abstracted, algorithm-driven partnership where generative AI appears poised to wrest power from both composers and users.
本研究将在线广告平台介绍为数字合成工具,在这些平台上,说服性修辞鼓励用户跟随链接并在登陆页面上采取行动。本研究将这些平台定义为数字空间,在这里,人类行为者与非人类的人工智能代理(Duin & Pedersen, 2021 & 2023)共同工作,通过机器学习和人工智能活动产生修辞代理。它围绕沃尔顿、摩尔和琼斯(Walton, Moore & Jones)(2019年)的立场、地位和权力框架,从理论上提出了一种以(人类)用户为中心的方法,用于在数字广告平台上撰写数字广告。它为技术和专业撰稿人提供了指导,帮助他们将人类用户置于抽象的、算法驱动的合作关系的中心,在这种合作关系中,生成式人工智能似乎准备从撰稿人和用户手中夺取权力。
{"title":"Composing with generative AI on digital advertising platforms","authors":"Daniel L. Hocutt","doi":"10.1016/j.compcom.2024.102829","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102829","url":null,"abstract":"<div><p>This study introduces online advertising platforms as digital composing tools where persuasive rhetoric encourages users to follow links and take action on landing pages. It frames these platforms as digital spaces where human actors work alongside non-human AI agents (Duin & Pedersen, 2021 & 2023) and where rhetorical agency emerges through the activity of machine learning and artificial intelligence. It theorizes a (human) user-centered approach to composing digital ads in digital advertising platforms built around Walton, Moore & Jones’ (2019) framework of positionality, position, and power. It provides guidance for technical and professional writers in placing human users at the center of an abstracted, algorithm-driven partnership where generative AI appears poised to wrest power from both composers and users.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000057/pdfft?md5=603042e59f8b7e4ce26eedc569bb33be&pid=1-s2.0-S8755461524000057-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139653466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-20DOI: 10.1016/j.compcom.2024.102828
Gabriel Lorenzo Aguilar
Compositionists can train students to rhetorically approach AI as a writing assistant—a metaphor that can help students maintain authority in dialogue with AI. Such an approach allows students to control the input and output from generative AI. Compositionists can teach students how to input ethical information and recognize harmful output. The students are then encouraged to converse with the AI in dialogue, sending messages back and forth until the AI generates writing that is acceptable in ethics and content. This article provides a social justice heuristic for compositions to follow in their training of students.
{"title":"Rhetorically training students to generate with AI: Social justice applications for AI as audience","authors":"Gabriel Lorenzo Aguilar","doi":"10.1016/j.compcom.2024.102828","DOIUrl":"https://doi.org/10.1016/j.compcom.2024.102828","url":null,"abstract":"<div><p>Compositionists can train students to rhetorically approach AI as a writing assistant—a metaphor that can help students maintain authority in dialogue with AI. Such an approach allows students to control the input and output from generative AI. Compositionists can teach students how to input ethical information and recognize harmful output. The students are then encouraged to converse with the AI in dialogue, sending messages back and forth until the AI generates writing that is acceptable in ethics and content. This article provides a social justice heuristic for compositions to follow in their training of students.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461524000045/pdfft?md5=ee0815efd4b8f8649fb20e4794f922b4&pid=1-s2.0-S8755461524000045-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139505490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-18DOI: 10.1016/j.compcom.2023.102809
{"title":"Erratum regarding missing Declaration of Competing Interest statements in previously published articles – Part 1","authors":"","doi":"10.1016/j.compcom.2023.102809","DOIUrl":"https://doi.org/10.1016/j.compcom.2023.102809","url":null,"abstract":"","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461523000592/pdfft?md5=0b6948004be7bf0de444c53dc103ff2e&pid=1-s2.0-S8755461523000592-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138422879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-18DOI: 10.1016/j.compcom.2023.102811
{"title":"Erratum regarding missing Declaration of Competing Interest statements in previously published articles – part 3","authors":"","doi":"10.1016/j.compcom.2023.102811","DOIUrl":"https://doi.org/10.1016/j.compcom.2023.102811","url":null,"abstract":"","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S8755461523000610/pdfft?md5=f14d89e6e56314b909a71cbb23b5231e&pid=1-s2.0-S8755461523000610-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138422888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}