An Empirical Study on Multi-Agents Improving Postgraduates’ Research Questioning Ability

Research questioning ability is an important foundation for the cultivation of postgraduates’ academic capabilities, and has a significant influence on the establishment of research directions and the improvement of research quality. However, current postgraduates generally face problems such as unclear concepts of research questions, lack of questioning strategies, and low quality of questions. Therefore, this paper first designed research questioning activities supported by multi-agents and developed the multi-agents research questioning tool “ZhiXue Yanyou”. Subsequently, this paper adopted a combination of questionnaire surveys, expert scoring, and semi-structured interviews to conduct the pre-test and post-test quasi-experiment with unequal groups. The results showed students had a relatively high overall satisfaction with the use of “ZhiXue Yanyou”; multi-agents can effectively improve students’ research questioning ability, assisting them in mastering research question theoretical knowledge, applying questioning strategies, and improving question quality, but their role in supporting high-level cognitive processes such as question evaluation, judgment of question importance, and in-depth analysis of professional fields was limited. Finally, this paper conducted in-depth discussions from three aspects: adaptability of multi-agents, cognitive gap, and development of literacy, highlighting the application potential of multi-agents in the cultivation of postgraduates’ research abilities, and providing valuable references for the optimization design and practical application of AI educational tools in the future.