Investigation and analysis of the current situation and learning willingness of science and technology journal editors on generative artificial intelligence

Background: This study aims to investigate the cognitive status and willingness to learn about generative artificial intelligence (GenAI) of science and technology (sci-tech) journal editors, and to propose corresponding training strategies to enhance their core competitiveness and promote the development of sci-tech journals in the artificial intelligence (AI) era. Methods: A questionnaire survey was conducted among editors of Chinese sci-tech journals, focusing on the respondents' understanding and attitudes towards GenAI and its usage boundaries, their willingness to learn GenAI technology, preferences for learning methods, and choices for improving learning outcomes and interest. Results: A total of 238 valid questionnaires were collected. The respondents were primarily female editors aged 31-50 with editorial or associate editor titles. Editors, 98.74% of whom had varying degrees of knowledge about GenAI, and 88.66% of whom believed that GenAI would partially replace their work in the future. Only 10.92% of the editors had a clear understanding of the usage boundaries of GenAI in academic publishing, while 84.87% considered it essential to learn GenAI technology. In terms of learning needs for GenAI technology, the most requested knowledge content was methods, techniques, examples of use and policy regulations, followed by technical theories and historical development processes. The preferred learning formats were on-site centralized training, online expert lectures, watching educational videos, regular training at work units, self-study and practice, and live exchanges with experts. The methods to enhance learning effectiveness and interest, in order of priority, include: establishing a learning communication group for constant updates, applying for relevant research projects, formulating incentive policies by the workplace, forming study groups with colleagues or like-minded peers at work, participating in competitions and awards organized by educational training institutions, and writing academic papers. Conclusion: Sci-tech journal editors have a high level of awareness regarding GenAI but lack knowledge of policy guidelines. They have an urgent need to learn GenAI technology, and it is essential to adopt diversified and practical learning strategies along with personalized learning formats to improve learning efficiency. Encouraging the editorial and publishing societies to lead professional and standardized GenAI training programs, and increasing incentives from relevant organizations and institutions to boost editors' enthusiasm for learning, while emphasizing international training is crucial.