The impact of AI-driven learning analytics tools on scientific inquiry and collaboration in K–12 classrooms: A mixed-methods study

As artificial intelligence (AI) reshapes education, its integration with learning analytics offers new potential for enhancing inquiry-based and collaborative learning. This mixed-methods study examined the effects of an AI-driven learning analytics system in an 8-week middle school science course involving 60 students. Participants were divided into an experimental group using AI-enhanced platforms and a control group using traditional IT tools. Data were collected via pretests and post-tests, engagement logs, observations, and interviews. Findings showed that students using AI tools exhibited significantly greater gains in inquiry skills, deeper collaboration, and increased motivation. Teachers also reported improved awareness of student learning and more effective instructional decision-making enabled by real-time AI dashboards. The study underscores the value of AI-supported learning analytics in K–12 settings and suggests implications for classroom design and teacher training.