ETHICAL AI INTEGRATION IN RESEARCH SOFTWARES TRAININGS
Starting June 2025, the African Online School of Applied Research Skills will embed comprehensive responsible and ethical AI usage components specifically into all research software training programs. This targeted integration focuses exclusively on enhancing how students learn to use contemporary research software platforms, recognizing that AI can significantly improve the research software training experience while maintaining ethical standards.
AOSARS will prominently display the designation “with Ethical AI Use” in each affected research software course title, demonstrating the institution’s commitment to responsible AI integration within research software education. This approach ensures that students receive comprehensive training in both research software functionality and ethical AI application within these specific technical contexts.
Addressing Research Software Training Challenges requires immediate action as traditional research software training procedures continue to burden learners with manual processes, steep learning curves, and cognitive overload when mastering platforms like SPSS, R, Python environments, NVivo, Atlas.ti, Zotero, and Mendeley. AI-driven features integrated into research software training can shorten, streamline, automate, and enhance various learning processes, making these complex tools more accessible to students.
Training Benefits Through AI Integration include enhanced learning efficiency as AI automates repetitive training tasks, reduces technical barriers in software mastery, and creates streamlined learning workflows within research software education. Most importantly, this integration empowers students to focus their intellectual resources on understanding research methodologies and data interpretation rather than struggling with technical software operations, allowing them to master both software functionality and research concepts more effectively.
This strategic shift transforms research software training by positioning AI as an educational enabler that helps students overcome technical hurdles and engage more deeply with the analytical and methodological aspects of research software applications, ultimately producing more competent and confident researchers.
