The AI-literate Researcher? Cross-Disciplinary Conceptualizations of AI Literacy in Research

Artificial Intelligence (AI) is ubiquitous and has been integrated into almost all areas of life. More than ever before, AI is becoming a new paradigm in research. For instance, in data analysis, AI can discover new patterns, predict phenomena, and propose novel solutions to complex problems. Moreover, Large Language Models (LLMs) such as ChatGPT and Google Gemini can be used for academic writing for scientific publications. Hence, researchers must classify, evaluate, and integrate AI-generated information into the research process. Thus, the research process is influenced by artificial intelligence. From an educational perspective, the question arises of which AI literacy competencies researchers need to use AI in the research process effectively and take responsibility for their research to assure research integrity.

Therefore, in this project, expert panelists from the mathematical, biological, and educational sciences conceptualize AI-literate researchers by defining competency expectations using the Delphi method. Each group of experts defines its own set of competency expectations, representing each discipline. In this iterative survey process, the experts receive anonymized (statistical) feedback on their disciplinary group's conceptualization and continue elaborating it to achieve a consensus within their group.

The comparison of conceptualizations across disciplines is expected to reveal differences and similarities in competency expectations, leading to a deeper understanding of the expectations for developing AI literacy competencies among researchers. These competency expectations can then serve as a foundation for planning, designing, and enhancing informal and formal learning processes, aimed at researchers’ further education to ensure research integrity in the era of artificial intelligence.