📄 Research Article
Inquiry-Based Learning in STEM Education: The Impact of Generative AI-Based Chatbots on Primary School Students' Problem Posing Ability in Science
Synthesis: This quasi-experimental study (N = 97 Chinese third-graders, split by class) compared GenAI-based chatbots against search engines for fostering science problem posing in inquiry-based learning. Chatbots significantly improved problem quality (t = 2.47, p = 0.015) and overall problem posing ability (t = 3.07, p = 0.003), produced a more integrated epistemic network structure (ENA), and reduced cognitive load while raising technology acceptance.
Key Findings
- Chatbots beat search engines for problem posing. The experimental chatbot group outperformed the search-engine control on problem quality (t = 2.47, p = 0.015) and total problem posing ability (t = 3.07, p = 0.003), with no significant difference in the number or category of posed questions.
- More integrated cognitive networks. Epistemic network analysis (ENA) showed the chatbot group developed a broad, high-density, integrated network (e.g., applying → scientific-question contexts), whereas the control group exhibited local clustering.
- Lower cognitive load, higher acceptance. The chatbot group reported lower cognitive load and higher technology acceptance than the search-engine group.
- Three rounds of progressive inquiry. Following three rounds of progressive problem-based inquiry learning, students' problem posing ability increased significantly in both groups (number and quality dimensions), with chatbots amplifying the effect.
Implications
This provides empirical evidence for introducing GenAI tools into inquiry-based learning in primary science. The chatbot's advantage — improving question quality and integrating cognitive networks while reducing cognitive load — positions conversational AI as a scaffold for inquiry and questioning rather than a mere answer-provider. For primary STEM education, it shows GenAI can support the generative, questioning dimension of inquiry that has been underemphasized.
Connected Concepts
- Generative AI
- Conversational AI
- K 12
- STEM Education
- Inquiry Based Learning
- Network Analysis
- Metacognition
- Student Experience
Connected Articles
- Penny Transition Network Analysis Efl Writing 2026 — Transition network analysis of learner-chatbot interactions
- Network Analysis — Network analysis methods in AIED
- Conversational AI Agents Umbrella Review 2026 — Umbrella review of conversational AI agents
Citation
Dai, Z., Huang, F., Xiong, J., Yang, Y., Zhang, Q., & Peng, X. (2026). Inquiry-based learning in STEM education: the impact of generative AI-based chatbots on primary school students' problem posing ability in science. International Journal of STEM Education, 13, 44.