Interactions with generative AI chatbots: unveiling dialogic dynamics, students’ perceptions, and practical competencies in creative problem-solving

• Published in: International Journal of Educational Technology in Higher Education Vol. 22; no. 1; pp. 12 - 30
• Main Authors: Song, Yu, Huang, Longchao, Zheng, Lanqin, Fan, Mengya, Liu, Zehao
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2025; Springer Nature B.V; SpringerOpen
• Subjects: Chatbots; College Students; Colleges & universities; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Creative problem-solving; Dialogue; Educational Technology; GAI-based chatbots; Generative artificial intelligence; Higher Education; Humanities; Information Systems Applications (incl.Internet); Law; Peers; Problem solving; Program Proposals; Research Article; Statistics for Social Sciences; Student attitudes; Student-human interaction; Students; University students; Creative problem-solving; GAI-based chatbots; Dialogue; Student-human interaction
• ISSN: 2365-9440; 2365-9440
• DOI: 10.1186/s41239-025-00508-2

This study explores the effectiveness of chatbots empowered by generative artificial intelligence (GAI) in assisting university students’ creative problem-solving (CPS). We used quasi-experiments to compare the performance of dialogue dynamics, learner perceptions, and practical competencies in CPS during students’ interactions with: (1) a GAI chatbot, and (2) their peers. In total, 80 postgraduate students participated. The assigned CPS task was the creation of an innovative research proposal. We found that there were significant differences in the dialogic exchanges observed between the two types of interaction. Student-GAI chatbot interactions featured more knowledge-based dialogue and elaborate discussions, with less subjective expression compared to student-peer interactions. Notably, students contributed significantly less dialogue when interacting with a GAI chatbot than they did during peer interactions. The dialogic exchanges arising from student-GAI chatbot interactions tended to follow distinct patterns, while those from student-peer interactions were less predictable. The students perceived interacting with a GAI chatbot as more useful and easier than interacting with peers. Furthermore, they exhibited higher intention levels when utilising a GAI chatbot to tackle the CPS task compared to engaging in discussions with their peers. Ultimately, practical performance was significantly enhanced through interactions with a GAI chatbot. This study implies that the prudent use of GAI-based techniques can facilitate university students’ learning achievement.