By the end of 2022, generative AI technologies based on large language models had become easily accessible and increasingly widespread. As disruptive technologies, their full impact and range of applications are still unfolding. Education is one of the six key areas of generative AI application identified by Chiarello et al. (2024), alongside human resources, programming, office automation, social media, and search engines. In education, generative AI offers new possibilities for teaching and assessment, such as personalized tutoring, automated feedback, and adaptive systems (e.g., Jensen et al., 2024). However, these innovations also present significant challenges that educators must navigate to ensure that all learners benefit from AI-driven innovations. Specifically, educators are called to tackle, among other things, the changing dynamics of teacher-student communication, the shifting nature of their role, ethical concerns in assessment, and the impact of generative AI on intercultural understanding in increasingly diverse education settings.
This Research Topic offers a platform for researchers and educators to reflect on the impact of these technological shifts on classroom culture and to share pedagogical experiments that enhance teaching and assessing practices. The editorial team has chosen the ‘short-paper’ format to capture fresh ideas, conversations, and pedagogical experimentations, and to allow these to be easily shared with a broader audience of researchers and teachers alike.
This multidisciplinary project welcomes contributions from teachers and researchers across a variety of fields (e.g., communication, education, computer science, economics, mathematics, and biology). We are particularly interested in practices with cross-disciplinary relevance that can shape classroom cultures at the tertiary level.The generative AI tools considered in the submissions must be available in a free or free-tier version, or commonly available as part of university-wide enterprise licenses, or similar.
Submissions may focus on, but are not limited to, themes such as the following:
• effective practices and/or lessons learned in integrating generative AI tools in classroom settings
• successful strategies to support teaching, learning, and assessment with generative AI tools
• real-time student feedback through AI-driven feedback mechanisms
• critical discussions on academic integrity, critical thinking, authorship, and other ethical concerns related to generative AI in classroom teaching, assessment, and curriculum design
• advances in instructional communication and/or pedagogical theories in the light of the integration of generative AI tools in classroom settings
• student engagement, participation, and collaborative learning in the AI-mediated classroom
• educational materials, instructional sources, and teacher professional development in the AI-mediated classroom
• development of necessary knowledge and skills (e.g., digital literacy and critical generative AI literacy) for learning in the generative AI era
• critical discussions of the challenges of generative AI to classroom culture (e.g., digital divide, power dynamics, and intercultural inequalities)
• sustainability of generative AI tools in classroom settings.
The Topic Editors seek three types of submissions:
1. Great Ideas for Teaching/Assessing with AI (GIFT-AIs)
GIFT-AIs are instructor- and student-tested ideas for effectively teaching and assessing a wide range of topics using generative AI. The goal of GIFT-AIs is to inspire readers to include and to experiment with AI in their teaching practices. A GIFT-AI may cover the following: a) original, single teaching activities; b) original teaching units that span several days or weeks; c) original teaching semester-long projects or approaches to an entire course; d) systematic, data-driven reflection of assessment practices that allow educators to monitor and support student learning as well as improve the quality of specific courses or overall programs.
GIFT-AI submissions should include the following components:
1. title (include “GIFT-AI:” at the beginning of your submission’s title)
2. intended course (subject, class size, level, modality, duration, recommended skill sets needed for students, and weekly schedule, cross-disciplinary relevance, and other relevant information)
3. objectives/learning outcomes
4. theoretical rationale (gamification, authentic assessment, collaborative learning, etc.)
5. step-by-step implementation instructions (preparation/preliminary steps, necessary learning materials, etc.)
6. debriefing, appraisal (including any limitations and/or suggested variations), and reflections
7. references
8. appendix (optional).
Frontiers in Communication accepts a wide range of article types. Suitable article types for GIFT-AI submissions may include Brief Research Report and Technology and Code.
2. Short Research Reports on Teaching/Assessing with AI (RESEARCH-AIs)
RESEARCH-AIs offer researchers already active in advancing our understanding of the use of AI in educational settings the opportunity to present recent findings and classroom-based research agendas. The goal of RESEARCH-AIs is to inform the scholarly community about current research developments, propose future research directions, and contribute to evidence-based practices for integrating AI in teaching and assessment.
RESEARCH-AI submissions should include the following components:
1. title (include “RESEARCH-AI:” at the beginning of your submission’s title)
2. abstract (100–200 words)
3. introduction (contextualization of the paper)
4. main text (comprehensive outline of the research agenda, with discussion of relevant studies, theories, or models, including research methodologies implemented and key findings)
5. conclusion (summarizing key points, highlighting the research agenda’s contributions, and suggesting future directions)
6. references
7. appendix (optional).
Frontiers in Communication accepts a wide range of article types. Suitable article types for GIFT-AI submissions may include Brief Research Report and Technology and Code.
3. Reflections on Teaching/Assessing with AI (REFLECTION-AIs)
REFLECTION-AIs are reflective pieces exploring the possibility of AI in teaching and assessing practices. They are intended to inspire meaningful, thought-provoking debates among educators, also in the style of op-ed. REFLECTION-AIs should be forward-looking, outlining potential trajectories in pedagogical practices, and/or provocative, discussing critical issues. These reflective pieces may be based on a variety of approaches (including, for instance, autoethnography, case studies, and historical analysis) and authors may include bold suggestions and proposals. Reflective pieces that critically question the inclusion of generative-AI technology in the classroom are welcomed. REFLECTION-AI submissions may be written in first person form, if relevant, and should be maintain a clear focus.
REFLECTION-AI submissions should include the following components:
1. title (include “REFLECTION-AI:” at the beginning of your submission’s title)
2. abstract (100–200 words).
3. introduction (contextualizing the reflection and presenting the specific focus guiding the reflection)
4. main argument (discussion of the central theme, with relevant examples, case studies, or personal teaching experiences, if applicable. May include an outline of possible future trajectories, critical reflections, bold suggestions, and innovative ideas).
5. conclusion
6. references
7. appendix (optional).
Frontiers in Communication accepts a wide range of article types. Suitable article types for GIFT-AI submissions may include Perspective and Opinion.
Word Count and Supplementary Material
Submissions should be a maximum of 3,000 words in length, excluding the abstract, section titles, figure and table captions, funding statement, acknowledgments, and references in the bibliography. The word count includes appendixes, except in those cases where the maximum word count of the selected journal article type exceeds 3,000 words.