Generative AI has rapidly become a defining force in journalism education, reshaping how knowledge is produced, taught, assessed and understood across global higher education systems. Since the emergence of tools such as ChatGPT, Copilot, DALL·E and other generative systems, educators and institutions have been confronted with urgent questions around pedagogy, academic integrity, curriculum design, and the evolving role of journalists in AI-mediated environments. While some institutions initially responded with restriction, many have since moved towards integration, developing policies and practices that embed GenAI into teaching, learning and research. Despite this shift, approaches remain uneven, and there is still limited systematic scholarship on how generative AI is transforming journalism education, professional identity and pedagogical practice.
This edited volume brings together scholarly, conceptual, empirical and practice-based work that examines the implications of generative AI for journalism education at a moment of rapid technological change. It explores how GenAI is reshaping teaching and learning, assessment design, curriculum development, newsroom training, and the broader question of what it means to educate journalists in an AI-driven information ecosystem. It also seeks to foreground emerging debates on ethics, verification, critical thinking, and the role of human editorial judgment in increasingly automated environments. In doing so, the book positions generative AI not only as a tool, but as a transformative force reshaping journalism education, professional identity and media practice.
Submissions of chapter proposals (500 words) are invited, including, but not limited to, the following areas:
Themes:
Generative AI and Teaching and Learning of Journalism and Digital Media Courses
- Pedagogical strategies for integrating GenAI in teaching and learning
- Using GenAI to promote engagement in the classroom
- Using GenAI in lecture delivery and in teaching practical skills in journalism labs
- Assessment strategies using GenAI
- Developing GenAI literacy frameworks and curriculum models
- Teaching students to critique AI outputs for news production and design courses
- Teaching adaptability, human-AI collaboration, and critical thinking
- GenAI and critical thinking
- GenAI and soft skills cultivation\
- GenAI instruction skills in journalism and media education\
- GenAI tools for news development, editing, drafting, translating, production, postproduction and audience engagement.
- Using GenAI as a research tool for assessments
Generative AI and Assessment design
- Designing assessments involving GenAI tools
- Using GenAI to develop assessments vs achieving Course Learning Outcomes (CLOs).
- Using AI to generate question banks and rubrics.
- Designing assessments that teach students how to critically evaluate, question, and validate AI-generated text, images, and data.
- Developing rubrics and methods that assess process transparency, originality, verification logs, and student reflection on the use or non-use of GenAI tools.
- Creating tasks where students use GenAI as a tool) for reporting, editing, and multimedia production—while demonstrating human editorial judgment.
- Designing Assessments that strengthen journalism ethics and fact-checking skills
- Competency-Based Assessment for AI-Enhanced Newsroom Skills (e.g. prompt design, AI-assisted research, automated transcription editing, and augmented storytelling)
- Detecting plagiarism in GenAI generated essays, audios, videos and other multimedia examples.
Proposal deadline: 21 April 2026 (500 words)
Notification of acceptance: 1 June 2026
Full chapter submission: 1 November 2027 (6,000–7,500 words, APA 7)