How do students’ AI interactions, dispositions, and prompt engineering skills shape human–AI collaboration in middle school STEM education?

Research from Educational Technology Research and Development (International) investigates how middle school students' AI interactions, dispositions, and prompt engineering skills influence human-AI collaboration in STEM education. The study, involving 69 eighth-grade students using ChatGPT in a five-day STEM-AI curriculum, employed a mixed-methods approach. It analyzed student-generated prompts, pre-post surveys, and competency tests to understand changes in AI interactions, dispositions, prompt engineering, and collaboration competencies, and to identify predictors of post-intervention collaboration.

Why it matters

Understanding how students interact with AI, develop prompt engineering skills, and foster positive AI dispositions is critical for integrating AI effectively into educational frameworks. This knowledge can inform the development of curricula that not only leverage AI for learning but also prepare future workforces for human-AI collaboration in various professional settings. Effective AI integration in education can drive innovation and enhance future workforce capabilities.

Key insights

• The study examined changes in students’ AI interactions, AI dispositions, prompt engineering skills, and human–AI collaboration competencies.
• It aimed to identify predictors of post-intervention human–AI collaboration competencies.
• The research utilized a mixed-methods design, including content analysis, repeated-measures MANOVA, and multiple regression analyses.
• Sixty-nine eighth-grade students participated, engaging with ChatGPT in a five-day STEM–AI curriculum.
• Data sources included student-generated prompts, pre–post surveys, and competency tests.

Source

Educational Technology Research and Development — https://link.springer.com/article/10.1007/s11423-026-10692-1