FACL Module: Expert Consensus Framework for AI-Enhanced Environmental Education

Xiaoyu Wang's dataset outlines a Flipped AI-Chatbot Learning (FACL) module for environmental education, developed using the Fuzzy Delphi Method with consensus from 12 experts. The data, stored in an XLSX file of 178.1 KB, was last updated on March 18, 2026. It provides a structured instructional framework integrating generative AI and flipped learning to address low student engagement and motivation.

Use Cases

• Developing personalized, student-centered learning modules based on the FACL instructional framework.
• Evaluating the effectiveness of AI chatbot interactions for pre-class preparation in environmental education.
• Designing active learning strategies for in-class sessions to promote critical thinking and pro-environmental behaviors.
• Applying the Fuzzy Delphi Method consensus results to structure educational objectives and evaluation mechanisms.

Strengths

• Framework developed with consensus from 12 experts using the Fuzzy Delphi Method.
• Data is openly licensed under CC-BY-4.0.
• File size is 178.1 KB, indicating a focused and manageable dataset.

Limitations

• Row count and specific column-level documentation are absent; field semantics must be inferred after download.
• The dataset's scope is limited to a conceptual framework and instructional design, not containing raw student or environmental measurement data.

Provenance

Source

Xiaoyu Wang via figshare.

Collection Method

Developed using the Fuzzy Delphi Method to gather expert consensus.

Freshness

Last updated 2026-03-18 17:27:28; freshness should be verified.

Geography

Context suggests a focus on China, but explicit geographic coverage is not stated.