Computers and Composition

Effective source use is a critical skill for first-year writing students because it prepares them for academic, professional, and civic engagement; however, existing research demonstrates that selecting appropriate sources and engaging them insightfully remains a significant challenge. While students struggle with the combined pressures to read, evaluate, and synthesize scholarly sources, we argue that online media including news articles, opinion pieces, and social media posts are a potent but underutilized resource for building students’ competence and confidence with source use. In this article, we present the methods that we have collaboratively developed as an instruction librarian and a first-year writing instructor to propose a new approach to teaching undergraduate research using online media. We detail strategies for teaching advanced search skills using Google and social media platforms like Reddit and X (formerly Twitter), as well as a “reception study” writing assignment that requires students to develop source evaluation and synthesis skills for engaging these online sources. The success of our module highlights that enabling students to build their research skills in the context of these more familiar source formats can lead them to an enriched understanding of the research process—including formulating an authentic research inquiry and engaging meaningfully with real audiences—while also building their skills in accessing, evaluating, and synthesizing diverse sources. Furthermore, by developing research skills in the context of social media platforms and online popular media sources, students gain a practical sense of the relevance of academic research skills to their daily research habits.

With respect to AI writing technologies (AIWT), we pose three foundational questions about academic dishonesty. First, do writing instructors and students perceive differences between AI agents and human agents in classroom scenarios? Second, to what extent are writing instructor and student perceptions are aligned? Third, what types of writing scenarios are perceived as academic dishonesty? Answering these questions provides a baseline of comparison not only for future studies of AIWT collaboration but also contextualizes perceptions of human-to-human collaboration. We report on a large-scale experimental survey study that answers these questions using item response theory (IRT). Our findings demonstrate that while there are differences between AI and human agents of collaborations, writing instructors and students are generally aligned in their perceptions. Using a Rasch model, we find that academic dishonesty operates along a spectrum of textual production. Regardless of whether the collaborating agent is human or AI, the more an agent produces text, the more this collaboration is perceived as academic dishonesty. Conversely, the less text that is produced, the less this scenario is perceived as academically dishonest. In our discussion, we provide a data-driven heuristic to guide instructors and administrators.

How can posthumanism help us reframe AI-mediated literacy practices? And what implications does such reframing have for cultivating AI literacy in language and literacy education? This article explores these two imperative questions through a case study analyzing two multilingual undergraduate students’ meaning-making and meaning-negotiation intra-actions with AI technologies in a writing classroom. The case study reveals a productive tension between these students’ experiments with posthumanist literacy and their entrenched humanistic assumptions. Ultimately, through the case study, the authors hope to demonstrate that reframing and re-engaging with AI literacy through a posthumanist lens may offer students and educators a relational approach to developing and cultivating AI literacy.

• AI can offer useful writing feedback when used combined with peer review. • AI and peer responses were often similar and mutually reinforcing. • When AI and peer responses differed, the perspectives were often complementary. • Evaluating AI feedback fostered student agency and AI literacy. Cycles of drafting and revising are crucial for student writers' growth, and formative assessment plays an important role. However, many teachers lack the time or resources to provide feedback on drafts. While research suggests that AI feedback is high enough quality to be used for draft feedback, especially when assignment-specific criteria are used (Steiss et al., 2024), it must be used in a human-centered process. AI has the potential to reduce educational equity gaps in writing support (Warschauer et al., 2023), but when narrowly implemented, technologies can deepen divides (Stornaiuolo, et al., 2023). Peer and AI Review + Reflection (PAIRR) combines peer review best practices with AI review in an approach that emphasizes student agency and reflection. Using a mixed methods approach, this study examined student perceptions of AI utility in the context of peer review. Results indicate that AI tools offer useful feedback when combined with peer review. Students found the similarity between AI and peer feedback reassuring, while also valuing their complementary perspectives. Moreover, by evaluating AI outputs, students developed AI literacy, gaining familiarity with AI feedback's affordances and limitations while learning ethical ways to use AI in their writing processes.

This case study investigates how two ESL graduate students, Ian and Sam, use ChatGPT in their research writing after receiving a comprehensive tutorial based on Warschauer et al.’s (2023) AI literacy framework. We analyzed their engagement with ChatGPT across prompt categories including genre, content, language use, documentation, coherence, and clarity. Data were collected from research paper drafts, ChatGPT chat histories, and interviews. Data analyses included coding ChatGPT prompts, textual analysis of drafts, and thematic analysis of interview transcripts . Results show that while both participants utilized ChatGPT for understanding genre conventions and content development, they developed distinct approaches reflecting their individual backgrounds. Ian selectively used ChatGPT for specific assistance needs, while Sam engaged more systematically, particularly for APA style and coherence checks. Both approaches maintained academic integrity and scholarly voice, demonstrating that Generative AI tools can be effectively tailored to individual needs without compromising ethical standards. This study highlights how advanced ESL writers can adapt GenAI tools to their unique writing processes, offering insights into the diverse ways AI can enhance academic writing while preserving individual agency. The findings suggest that AI integration in academic writing can be customized to support diverse writing goals and backgrounds.

In this paper, I explore first-year students' self-reported preferences for choosing source material in a digital, research-based writing setting. I argue that widespread skepticism towards online information has led to an "objectivity bias," where students prefer sources perceived as neutral and objective. Through qualitative interviews, I report that this bias may result in an overreliance on data-driven and empiricist sources, often at the expense of valuable personal narratives and experiential knowledge. I highlight the role of digital platforms and search algorithms in shaping these preferences and discuss the implications for teaching information literacy.

• Composing process focus including screen recording and think aloud protocols. • 11 explicit composing process activities are defined and described. • Establishes explicit metalanguage for digital multimodal composing teaching & research. • Includes illustrations of complexity of multimodal composing. Daily writing practices occur in digital environments and are often multimodal. Studies have attempted to interpret composing processes in these environments through text-based lenses and findings have yet to explicitly or effectively define and illustrate the complexities. This case study explores processes and activities of 5th-grade students as they compose using digital tools, multimodal resources, and navigate the opportunities those tools and resources afford. Findings suggest 11 process activities; three unique to digital multimodal environments, and all having influences of the digital and multimodal environments in which composing takes place. Results 1) demonstrate the potential to develop a specific metalanguage for digital multimodal composing, 2) begin to inform a specific digital lens for interpreting composing in these 21 st century environments and 3) help practitioners design instruction that best support student composers in classroom contexts.

• Hispanic women engage more in check-in assignments than men. • Hispanic enrollment (37.71 %) exceeds community college average. • Main themes: course perceptions, personal challenges, faculty-student relations. • Check-in assignments enhance engagement and faculty-student bonds for Hispanic women. • Advanced course students report more personal challenges, greater faculty reliance. While online community college students’ engagement with coursework, class retention, and motivation to participate are critical for academic success, these needs often go unmet for diverse and underrepresented populations, especially in the absence of culturally responsive and inclusive teaching practices. This study contributes to the limited research on culturally responsive pedagogy in online community college settings by exploring the implementation and impact of high-context communication practices in that setting, with a focus on improving engagement and academic outcomes for diverse student populations. Drawing on frameworks of culturally responsive teaching and high-context communication, the research examines the effectiveness of “check-in assignments” as a low-stakes, personalized intervention designed to foster stronger faculty-student relationships, enhance student belonging, and bridge cultural communication gaps in online learning environments. Using a mixed-methods approach, the study analyzes quantitative data on assignment engagement and qualitative themes from student responses. Findings indicate that high-context communication practices promote deeper engagement, especially among Hispanic and non-Hispanic females, while highlighting disparities in engagement among male students. Key themes—course perceptions, personal challenges, and faculty-student relationships—underscore the role of culturally informed interventions in addressing the needs of underrepresented groups and enhancing engagement and academic success. Future research could expand on these findings by exploring longitudinal outcomes and adaptive strategies for diverse learning environments.

This article explores teaching writing with generative AI as critical play where students and teachers engage in an ethically dialectical and aleatory game with generative AI. I qualitatively surveyed 24 writing teachers about how they teach writing with generative AI as well as its advantages and disadvantages. I discovered that teachers used generative AI to teach about the ethics of generative AI's design and rhetorical use to avoid plagiarism. Teachers also critically played with generative AI to teach the writing process of invention, drafting, revision, and editing. Specifically, the critical, dialectical interplay of human and machine invents in aleatory and emergent ways, creating moments of epiphany for students and teachers within the writing process for invention, drafting, revision, and editing while the real time pace of generative AI democratizes education, making writing and teaching more accessible for them.

The question of how generative Artificial Intelligence (Gen AI) will reshape communication is causing questions and concerns across the field of education, particular literacy and writing classrooms. Although important questions have surfaced surrounding the varied effects on writing instruction and ethical implications of AI in the classroom, there are calls for deeper investigations about how these tools might shape multimodal composing processes. This study builds upon this developing field by exploring how 21 university students in literacy education courses multimodally composed with generative AI and their perspectives on the use of AI in the classroom. Data sources included screen capture and video observations, design interviews, pre- and post- surveys, and multimodal products. Through qualitative and multimodal analysis, four main themes emerged for understanding preservice teachers’ multimodal composing processes: (1) composing was an iterative process of prompting guided by the AI tools, (2) composers exhibited two distinct processes when designing their projects, (3) AI shaped creative possibilities, and (4) play, humor, and surprise served a key function while composing. Preservice teachers’ perspectives also revealed insights into how AI shaped engagement with content, the importance of scaffolding AI in the classroom, and how ethics were intertwined with technical function and teaching beliefs.

• The informality of video essay narration engendered ideation in drafting and script writing for students. • Students felt more responsible and personally invested in their arguments when they narrated and dramatized them in the video making process. • While students admitted that they tended to “gloss over” written drafts when revising, the video making process prompted students to be more self-motivated in the revising process, enabling them to evaluate and develop their arguments. • Unlike oral presentations, as students viewed their video essays as audience members, they could more clearly discern if their arguments lacked coherence or depth. This self-evaluation resulted in students taking the initiative to revise their final written assignments. Although multimodal assignments have increasingly been incorporated into academic writing curricula, research into their impact on student writing remains limited. This study, conducted at a Singaporean university, required students to transform a written essay draft into a video essay and then revise their draft into a written essay assignment. By comparing students’ initial drafts and their final submissions, and analysing interviews and reflective journals, we identified significant benefits stemming from the transmediation between written and multimodal text. Specifically, we found that 1) transmediation enabled students to self-evaluate their writing as they repeatedly listened to their voiceovers, found concrete visuals to illustrate their ideas, and edited their work to fit the concise video format; 2) students broke with habitual, less useful revision practices as they were freed from the conventional and grammatical concerns of written academic text and narrated their arguments colloquially in their voiceovers; 3) students exhibited an improved awareness of audience and medium; and 4) students were more enthusiastic with the course due to the novelty of the multimodal assignment. These findings suggest that including a video essay assignment during the drafting process can serve as an effective tool in advancing students’ abilities to evaluate their own academic writing.

• Indexes are hylomorphic; they turn accidence into substance. • Indexes are authored, not merely produced. • The syntactic, alphabetic, and columnar form of indexes are rhetorically powerful. • Indexes are political because they destabilize hegemonic reading practices. This article, in the area of digital rhetoric, argues that the apparatus of the index is an authored text that bears all of the qualities of creative work. Its primary and distinguishing quality, moreover, is a hylomorphic one that bridges the temporal and material divide by taking the accidence in a text and naming it in substance. This dual nature is especially apparent in indexes that are produced by software, such as MS Word, that require the tagging of a main text to create what is called an “embedded index”; indexes of this sort exist both inside a main text and outside of it, in the tags and in the index list. Because the index both transforms (accidence to idea) and translates (from the main text to index list), the index has rhetorical force, interpreting a text for its readers. It does so as much by its content as by its formal qualities: syntactic, alphabetic, and columnar. Its persuasiveness in tandem with its intervention in the reading process, moreover, has social and political implications since the index can serve as both a means of rebellion and control for those who use and make them.

• This study explores GenAI's role in multimodal composition, including Adobe Firefly and DALL·E. • GenAI reshapes the composition stages of invention, designing, and revising. • Despite its limitations, GenAI offers alternative solutions to wicked problems. • Post-GenAI use, students critically revise and iterate their compositions. • The study contributes to future research and teaching of AI-assisted composition. This study explores the integration of generative artificial intelligence (GenAI) design technologies, including Adobe Firefly and DALL·E, into the teaching and learning of multimodal composition. Through focus group discussions and case studies, this paper demonstrates the potential of GenAI in reshaping the various stages of the composition process, including invention, designing, and revising. The findings reveal that GenAI technologies have the potential to enhance students’ multimodal composition practices and offer alternative solutions to the wicked problems encountered during the design process. Specifically, GenAI facilitates invention by offering design inspirations and enriches designing by expanding, removing, and editing the student-produced design contents. The students in this study also shared their critical stance on the revision process by modifying and iterating their designs after their uses of GenAI. Through showcasing both the opportunities and challenges of GenAI technologies, this paper contributes to the ongoing scholarly conversations on multimodal composition and pedagogy. Moreover, the paper offers implications for the future research and teaching of GenAI-assisted multimodal composition projects, with the aim of encouraging thoughtful integration of GenAI technologies to foster critical AI literacy among college composition students.