MASTERS’S STUDENTS TRAINED ON AI-ASSISTED RESEARCH TOPIC DEVELOPMENT
The African Online School of Applied Research Skills hosted a masters-level training session on 11th May, 2025, focusing specifically on sourcing and developing research topics using artificial intelligence. The event introduced a problem-centric approach to topic selection that leverages technology while maintaining scholarly rigor. Students were presented with core methodological principles for identifying viable research topics from empirically documented problems, maintaining scientific neutrality when formulating research variables, and using technology as a supportive tool for topic development rather than replacing academic judgment.
During the session, instructors demonstrated how technology could enhance the research topic sourcing process. Students observed how advanced tools could analyze documentary evidence like economic surveys and development reports to identify relevant problems suitable for research, assist in transforming these problems into appropriate research variables, and formulate research topics that align with institutional requirements and supervisor preferences.
The training featured active student participation, with attendees sharing potential research topics and engaging in discussions about identifying research gaps when selecting topics. The session clarified that viable research topics can emerge through finding methodological, contextual, or conceptual variations in existing research, not merely from discovering entirely unexplored areas.
Key takeaways emphasized technology as an accelerator for research topic development that still requires human verification, the importance of sourcing topics that strategically align with institutional requirements, and the value of problem-based approaches that ensure research relevance. This innovative methodology for topic selection represents a significant advancement in research education for the African context, equipping a new generation of scholars with sophisticated approaches to identify meaningful research topics that address complex socioeconomic challenges while maintaining academic integrity.
