Expert Consensus Framework for a Flipped AI-Chatbot Environmental Education Module

12 experts contributed via the Fuzzy Delphi Method to develop an instructional framework for a Flipped AI-Chatbot Learning module. The dataset, created by Xiaoyu Wang and last updated in March 2026, outlines key instructional objectives, strategies, and evaluation mechanisms for enhancing Environmental Literacy. It is a small dataset, 5.5 KB in size, stored in an XLS file.

Use Cases

• Designing student-centered environmental education curricula based on the expert-validated instructional framework.
• Developing AI chatbot interactions for pre-class learning based on the module's specified strategies.
• Evaluating the effectiveness of flipped learning modules in promoting pro-environmental behaviors.
• Integrating generative AI tools into higher education pedagogy for personalized learning.

Strengths

• Framework is based on consensus from 12 experts using the Fuzzy Delphi Method.
• Dataset is openly licensed under CC-BY-4.0.
• Specific instructional objectives and evaluation mechanisms are detailed in the description.

Limitations

• Row count and column-level documentation are unknown, limiting suitability assessment.
• The dataset is very small (5.5 KB), indicating limited scope and likely a conceptual framework rather than empirical data.
• Description metadata is limited; actual data structure and content require manual inspection after download.

Provenance

Source

Xiaoyu Wang via figshare.

Collection Method

Developed using the Fuzzy Delphi Method (FDM) with expert consensus.

Freshness

Last updated 2026-03-18 17:27:38; freshness should be verified.

Geography

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