Communicating Science in the Age of GenAI: Can Generative AI Support the Usage of Higher-Level Science Communication Strategies in Writing?

Effective science communication (SciComm) is crucial, but training scalability remains challenging. We explored whether generative AI (GenAI) could provide feedback to enhance SciComm strategies. In an online iterative distillation exercise, SciComm trainees ( N = 78) condensed their research. An experimental group ( n = 41) received jargon-oriented and GenAI feedback; controls ( n = 37) received only jargon feedback. Participants preferred revised texts, with slightly higher preference in the GenAI group. SciComm-based rubric assessment revealed GenAI-supported texts significantly improved in SciComm strategies, particularly connecting science to everyday life and narrative use. Findings highlight GenAI’s potential to enhance SciComm content and scalable feedback, supporting its careful integration into training.

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Publication Details

Journal
Science Communication
Published
2026-02-09
DOI
https://doi.org/10.1177/10755470251411176
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Communicating Science in the Age of GenAI: Can Generative AI Support the Usage of Higher-Level Science Communication Strategies in Writing?

Roy Yosef, Yael Barel-Ben David, Elad Segev
Science Communication
Artificial Intelligence in Healthcare and Education
article

Communicating Science in the Age of GenAI: Can Generative AI Support the Usage of Higher-Level Science Communication Strategies in Writing?

Roy Yosef, Yael Barel-Ben David, Elad Segev
article en

Abstract

Effective science communication (SciComm) is crucial, but training scalability remains challenging. We explored whether generative AI (GenAI) could provide feedback to enhance SciComm strategies. In an online iterative distillation exercise, SciComm trainees ( N = 78) condensed their research. An experimental group ( n = 41) received jargon-oriented and GenAI feedback; controls ( n = 37) received only jargon feedback. Participants preferred revised texts, with slightly higher preference in the GenAI group. SciComm-based rubric assessment revealed GenAI-supported texts significantly improved in SciComm strategies, particularly connecting science to everyday life and narrative use. Findings highlight GenAI’s potential to enhance SciComm content and scalable feedback, supporting its careful integration into training.

Science Communication
Holon Institute of Technology (IL), Christian-Albrechts-Universität zu Kiel (DE), Leibniz Institute for Science and Mathematics Education (DE)
Quality Education
Openalex Percentile: Top 62%
Artificial Intelligence in Healthcare and Education
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