Publications

Katlynne Davis, Jason Tham, Danielle Mollie Stambler, Jialei Jiang, Jessica Campbell, Gustav Verhulsdonck, Daniel Hocutt

Article: This article examines how educators navigate tensions between efficiency-driven integration and critical approaches to generative AI literacy. Through thematic analysis of twelve institutional AI frameworks and collaborative autoethnographic reflections, we identify significant gaps between policy aspirations and pedagogical realities. While institutions converge around principles of human oversight and ethical consideration, educators face challenges including time constraints and tensions between preparing students for AI-integrated futures while maintaining critical perspectives. We propose a “slow pedagogy” approach that resists efficiency-driven integration in favor of deliberate, justice-centered engagement, offering a reflective heuristic for practitioners across educational contexts.

Lesley Wilton, Clare Brett, Stephen Ip, Rutwa Engineer & Athena Tassis

Book Chapter: This chapter describes a study investigating what AI is, what it does, and indicators of AI Literacy in Education (AILE) among graduate education students. Data was collected on the online activities of 133 learners and one instructor in six courses taking place over 5 years at a large urban university in Canada. Data covered multiple iterations of an Introduction to AI in Education (AIEd) course and an AI Ethics in Education course, and were processed in three sub-studies, i.e. (1) an “AI Applications Study”, examining students’ choices of AI tools; (2) an “AI Literacy Indicators Study”; and (3) an “AI Instructor’s Reflections Study”. The results suggest that, due to technological transience and a lack of information about AI systems, learners find it difficult to perform a critical analysis of AI. Model-card-type information appears crucial for enhancing AI literacy. Consideration of ethics is essential if AI is fully integrated into education. The “Instructor’s Reflections” study acknowledges the challenge of designing courses with such rapidly evolving technology. Suggestions for addressing AI literacy in the future are discussed.

Jason Tham

Alyson E. King (ed.)

Book: This book addresses the implications of artificial intelligence for teaching, learning and academic integrity in higher education. It explores policies about the use of Generative Artificial Intelligence (GenAI), describes how to teach writing in the era of GenAI, and how instructors can design courses and assessments that prevent plagiarism while building the necessary skills for critical thinking and writing. Together, the chapters include research results, case studies, teaching methodologies, course design ideas, analysis of power and gatekeeping, and best practices related to GAI from a diverse range of researchers from English and French Canada, the United States, England, Ukraine and Croatia. The authors approach the advent and rapid spread of GenAI in higher education by examining its use from different perspectives with a particular focus on its impact on academic integrity. Taking a communication studies approach, consideration is given to the role GenAI might play disrupting power structures in universities to improve access for students who are non-traditional or English Language Learners. The book also explores how reimagining teaching methodologies can help to mitigate academic integrity violations due to misuse of GenAI and to teach students to use GenAI with integrity as a research and brainstorming tool. Students need to learn how to assess the reliability of GenAI’s output as the develop the skills for research and writing. Methods of teaching writing and research skills using GenAI are explored in an effort to ensure that critical thinking skills are developed successfully. Most instructors who use writing-intensive assessments believe that essential critical thinking skills are developed via the writing process; often, ideas become concrete as one writes about them. Teaching with GenAI can provide opportunities for instructors to guide their students into a deeper analysis and critique of their research.

Isabel Pedersen

Journal Article: This opinion article anticipates another turn in emergent AI applications and presupposes the cultural adaptation that will be required for postsecondary educators. First, AI will be further incorporated in learning environments by advances in wearable computing. Personal devices, often wearable, will be largely hidden or added in subtle ways to people’s bodies or clothing, and designed for augmenting cognitive tasks. Second, sophisticated, work-capable AI agents are emerging; innovation is moving past chatbots and generative AI to AI agentive assistants that are designed to “help” people in highly personal and specific tasks. Simply put, AI agents designed to “work” for humans, will be in close communication with our students. Taken together, these trends mean that we can expect postsecondary learning environments to change, again.

Frontiers in Education, 21 September 2025, Section: Digital Education Volume 10 – 2025

Isabel Pedersen

Article: The growing proliferation of AI-powered chatbots has led to debates around their social roles as friend, companion or work assistant. Where is this going next?

Jialei Jiang and Gustav Verhulsdonck

Article: This qualitative study explores the integration of multimodal generative artificial intelligence (GenAI) tools, including FigJam AI and Figma AI plugins, into technical communication students’ design thinking stages of user experience (UX) design. Findings from students’ AI statements and focus group discussions indicate the positive roles of GenAI in defining and designing and identify its limitations in empathizing and evaluating. The study provides practical implications for scholars and practitioners seeking to enhance UX design with GenAI.

Andrea Slane, Isabel Pedersen

Journal Article: Development of Socially Assistive Robots (SARs) and other assistive smart technologies is commonly justified by casting aged care as approaching a crisis point, due to an aging population and ensuing strain on healthcare systems. Combined with older people’s overwhelming wish to avoid more formal care contexts for as long as possible, this confluence of factors positions SARs as means to extend independent living, and so has inspired commercial developers to market their devices directly to older consumers. Preserving respect for the ethical principle of autonomy has been central to discussion of SARs in aged care settings, some of which incorporates the ethical views of older people. Since consumer SARs are claiming to integrate into older people’s digital device consumption practices, this article argues that more attention needs to be paid to what autonomy means to older peoples as digital technology consumers. Through analysis of marketing materials and two qualitative studies focused on how older people think about potential use of consumer SARs, the participants’ ethical reasoning on autonomy is revealed to be informed by a sociotechnical discourse that on the one hand aligns with common cultural imaginaries of aging, but on the other displays a range of orientations towards consumer digital technology use on individual, collective and societal levels. The article contributes to the field a novel and nuanced understanding of the value of autonomy held by older people and their ethical reasoning concerning future consumer information technologies such as SARs.

International Journal of Social Robotics, Volume 16, pages 2277–2296, (2024)

Tanner Mirrlees

Book: This book is a first-of-its-kind critical interdisciplinary introduction to the economic, political, cultural, and technological dimensions of work in the rapidly growing digital media and entertainment industries (DMEI).

Tanner Mirrlees presents a comprehensive guide to understanding the key contexts, theories, methods, debates, and struggles surrounding work in the DMEI. Packed with current examples and accessible research findings, the book highlights the changing conditions and experiences of work in the DMEI. It surveys the DMEI’s key sectors and occupations and considers the complex intersections between labor and social power relations of class, gender, and race, as well as tensions between creativity and commerce, freedom and control, meritocracy and hierarchy, and precarity and equity, diversity, and inclusivity. Chapters also explore how work in the DMEI is being reshaped by capitalism and corporations, government and policies, management, globalization, platforms, A.I., and worker collectives such as unions and cooperatives. This book is a critical introduction to this growing area of research, teaching, learning, life, labor, and organizing, with an eye to understanding work in the DMEI and changing it, for the better.

Offering a broad overview of the field, this textbook is an indispensable resource for instructors, undergraduates, postgraduates, and scholars.

Danielle Mollie Stambler, Nupoor Ranade, Daniel L. Hocutt, Stephen Fonash, Jessica Lynn Campbell, Ann Hill Duin, Isabel Pedersen, Jason Tham, Saveena (Chakrika) Veeramoothoo & Gustav Verhulsdonck

Journal Article: As digital technologies rapidly evolve, updating and enhancing models of digital literacy pedagogy in technical and professional communication (TPC) becomes more urgent. In this article, we use “digital life” to conceptualize the ever-changing ways of knowing and being in postinternet society. Using collaborative autoethnography, we investigate features of threshold concepts in TPC pedagogy that may support models of digital literacy that are resistant to tools-based definitions, foster student agency, and facilitate accessibility, equity, and justice.

This article is published in the Technical Communication Pedagogy, Technical Communication Quarterly.

Daniel Hocutt, Nupoor Ranade, Jianfen Chen, Katlynne Davis

Despite serving as a user analysis tool for technical communicators where usability testing methods fall short, data analytics remains underdeveloped in technical and professional communication (TPC) pedagogy. In this entry, we discuss the value and means to incorporate data analytics in existing TPC courses to prepare students for the workplace, and as a way to provide an accessibility-driven framework to perform user studies through data analysis methods for practitioners.

Gustav Verhulsdonck, Jennifer Weible, Danielle Mollie Stambler, Tharon Howard, Jason Tham

Journal Article: Purpose: As technical and professional communicators (TPCs) use AI to develop content, inaccuracies due to AI limitations are introduced; it is vital TPCs evaluate AI-generated content to improve accuracy and human-centeredness. In this article, we present a human-in-the-loop AI content heuristic (HEAT: Human experience, Expertise, Accuracy, and Trust) as a rating mechanism.

Method: This exploratory case study evaluated the quality of content generated by ChatGPT from the perspective of beginner TPC students. We used multiple prompting strategies asking ChatGPT to create documentation on personas using two Darwin Information Type Architecture (DITA) information types namely, concept topics and task instructions, and we evaluated the results with HEAT.

Results: HEAT had good intraclass correlation coefficient (ICC) reliability (.743 pilot; .825 for scenarios) indicating its fitness as a heuristic for evaluating generative AI output. The findings indicate that ChatGPT was generally good at writing concept topics; however, it performed less well creating step-by-step task instructions. Expert TPC input helped develop a better prompt for improved output. We also found that tokenization in ChatGPT (the way it breaks up text) has a large role in terms of noncompliance with format specifications.

Conclusion: There is a need for TPCs to (1) develop new models for AI-assisted content creation, (2) recognize the impact of different prompting strategies on developing specific structured authoring units such as concept and task topics, and (3) be aware of the limitations of AI such as ChatGPT. Human-in-the-loop quality check mechanisms, such as HEAT, can help validate and modify AI-generated content to better serve end users.