Big data assisted eco-learning environment framework for inclusive education

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Abstract
Big data is profoundly changing education under inclusive education. Classroom interaction, a vital component in education, is gaining increased emphasis, driving research into learning environments that better meet interaction needs. Therefore, exploring the construction of a big data-assisted eco-learning environment for classroom interaction is a prospective study. This research focuses on constructing a big data-assisted ecological learning environment based on affordance theory. It examines the relationship among learning environment, classroom interaction, and learning outcomes, using SmartPLS for validation. Through controlled experiments, surveys, teacher-student interaction analysis, and interviews, the study explores learner behavior data. Findings show the big data-assisted eco-learning environment enhances English classroom interaction, thereby further improving learning outcomes, across dimensions like learning space, resource accessibility, technical support, and emotional support. Integrating big data with ecological theory offers insights into educational digitization, supporting flexible classroom interaction, and promoting education equity, inclusivity, and sustainable education through data-driven resource management.

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