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Navigating Media & AI: Critical Principles and Pedagogies

NCTE seeks chapters for a new edited collection about multimodal generative AI in ELA teaching and learning.

Call for Manuscripts

The widening use of generative AI is creating a sea change in literacy education, and the potentials and possibilities are numerous. This historical moment comes over 30 years after the New London Group, in their seminal work, introduced their concept of a pedagogy for multiliteracies and urged educators to consider widening understandings of literacies that embraced the multimodal. Now, generative AI has created a potential opening for ELA classrooms to continue the legacy of expansive definitions of literacies through the use of these new, new literacies.

In the modern world, multimodality and media are predominant. This rise of image-, sound-, and video-generating AI platforms has created both immensely difficult challenges and rich opportunities for classroom teachers who seek to empower students with the ability to critically analyze media texts—especially the kinds of texts that populate their own social media ecosystems. On the one hand, teachers are encountering issues of fake news, AI “slop,” and multimodal plagiarism. Teachers worry about students’ discernment and “cognitive laziness” on media platforms, as all of us are growing accustomed to finding synthetic media among other human-generated content on our feeds. On the other hand, teachers see opportunities for engaging uses of AI-generated media to support thoughtful learning for their students that meets them where they are, such as encouraging students to add multimodal dimensions to their compositions or helping students to visualize or play with text in ways that are newly accessible due to multimodal AI tools.

This edited collection on Navigating Media & AI: Critical Principles and Pedagogies is about planning for and using multimodal generative AI to support ELA teaching and learning in thoughtful, discerning, and critical ways. Centering NCTE’s ELA AI Framework: Guiding Responsible Classroom AI Use for teachers in grades 6–12, this edited collection explores the potential of AI as “bridge rather than a barrier to meaningful learning” (p. 2). We aim to provide strategies that use AI in ELA contexts for engaging students in intellectual pursuits, supporting all learners, enacting culturally relevant and sustaining pedagogies, and enhancing student voice and agency in humanizing ways. As with the framework, we aim to “foster resilient, tech-savvy, and deeply reflective students who are prepared to lead with their own voices in this digital age” (p. 3).

As such, this edited collection both deeply grapples with the ethical and critical tensions that arise from an AI-infused media ecosystem, and also at the same time critically imagines and explores the ways that teachers can innovate with AI in classrooms to center social-justice driven teaching and learning—particularly around engaging with media, multimodal composing, literary interpretation and aesthetic inquiry, writing of all genres, and all forms of artistic and aesthetic expression. We focus particularly on issues around multimodality, media, literary representation, aesthetics of meaning-making, and artistic expression because collectively these are foundational areas of ELA instruction and are essential for continuing to bolster humanistic inquiry and engagement in the 21st century.

We invite critical and nuanced exploration of the principles and practices for planning for and using AI in ELA classrooms and related contexts. This volume is aimed at practicing and preservice teachers of all experience levels who are thinking about how to engage with AI tools and ecologies in their ELA classroom. We invite authors to describe complex ideas in clear, engaging, and nuanced ways. We strongly encourage submissions from practicing teachers and other practitioners who are using generative AI tools in their classrooms and school settings.

Below we describe two chapter types we are soliciting: critical principles and pedagogies.

This section will feature ideas about how to think about AI responsibly and expansively while designing curriculum, assessments, and inclusive differentiation strategies.

Possible Principles chapters include:

  • How does multimodal generative AI work, how does it differ from other forms of AI, and what do these kinds of definitions mean for classrooms—moving beyond seeing AI as tools toward understanding AI as an already omnipresent ecological system.
  • Ethical consideration for multimodal AI tools (e.g., training data, navigating or mitigating potential biases, context for use, concerns around intellectual property).
  • Practices or critical tools for identifying or unpacking AI in media circulating online.
  • Specific tools for analyzing particular modalities of synthetic texts (e.g., considering how images are synthesized from other images or representative of certain genres).
  • Information about breaking down how to use generative AI in critical multimodal ways, including how to disrupt algorithms that might otherwise reinforce stereotypes and harm.
  • Principles and practices for how to design ELA curricula that include and utilize multimodal generative AI—what to think about while planning, what are the steps to designing strong units, etc.
  • Ways that assessments can use multimodal generative AI to center student voice, agency, and humanity rather than detracting from one or all of these imperatives.
  • Strategies for how teachers can talk to administrators, parents, and community members about how they are ethically, safely, and critically using AI to generate multimodal texts.
  • What teachers should know about how to code and/or the math, statistics, and computer science behind multimodal generative AI, especially as it connects to critical practices that help users support diverse representation as well as human voice and agency.
  • Frameworks that help teachers think about how multimodal generative AI is connected to and useful with key ELA content—for example, how teachers might think about multimodal generative AI with regards to media-infused writing processes or compositions; literary devices, figurative language, and/or media tools; aesthetic literacies; creative writing; conducting literary analyses of novel-length texts; sociolinguistic analysis and engaging with a range of languages and language varieties; conducting research; and critical semiotic analysis.
  • Multimodal-specific strategies for supporting multilingual learners, emergent bilingual learners, and English language learners with ELA content using generative AI.
  • Tools and procedures for designing plans for culturally relevant and sustaining pedagogies using generative AI in ELA classrooms.
  • Tools and procedures for designing assessments, curriculum, or pedagogies that differentiated, adapt, or personalize student learning through multimodal generative AI, particularly for students with disabilities.

 

Classroom enactments that present snapshots of classroom activities and routines, thickly described, which help us feel as if we are in the classroom and experiencing the pedagogy.

Possible Pedagogies chapters include:

  • Portraits of classes using literary/aesthetic/multimodal tools to critically analyze multimodal AI texts.
  • Support for differentiating processes of learning through multimodal AI.
  • Students using AI tools to create images, music, or multimedia.
  • Multilingual learners using generative AI for multimodal compositions that include translanguaging practice.
  • Portraits of culturally relevant teaching and learning in classrooms using generative AI and media.
  • Examples of youth creating literary magazines, zines, and other publications as part of ELA or in extracurricular clubs that have featured engaging creatively with aesthetics and AI.
  • Examples of teaching multimodal critical AI prompting practices with students, including how students revised, refined, and edited prompts to move toward more justice-driven outputs.
  • Descriptions of implementing multimodal performance assessments, exhibitions of student work, or other kinds of assessments where generative AI supported personalization, differentiation, cultural responsiveness, and/or students’ humanity and voice.
  • Methods of engaging AI media literacy.
  • Pedagogical methods for using tools of multimodal literary analysis and/or critical discourse analysis and AI in classrooms.
  • Pedagogical activities that use digital humanities research methods for the English classroom with students, including but not limited to machine learning, topic modeling, word frequencies, cluster analysis, computational stylistics, principle components analysis, multidimensional scaling, network analysis, and computational discourse analysis.
  • Accounts of teacher learning in professional communities to improve practice with multimodal generative AI in ELA classrooms.
  • Portraits of other innovative and critical uses of multimodal generative AI in ELA classrooms.

 

Please submit chapters of up to 5,000 words following APA style using the form below by October 31, 2026.

Please note the rapid timeline for this collection:

  • Full chapters solicited October 2026
  • First revisions due early December 2026
  • Second (final) revisions by mid-January 2027

Have questions? Please direct inquiries via email to booksteam@ncte.org.

We invite chapter submitters to read and reference NCTE frameworks for considering use of AI, including ELA AI Framework: Guiding Responsible Classroom AI Use as well as other resources shared below.

In addition to chapters in the collection, authors will be invited to share digital or media-based resources such as lessons, materials, or models in a collection on the Hack Your Stack (https://bit.ly/hackyourstack1) page.

 

  • Max. file size: 100 MB.