This study examined the impact of generative AI chatbots on secondary school students' historical empathy and inquiry-based learning in Sabah, Malaysia. Utilizing a quasi-experimental design, the intervention integrated AI-driven simulations into history classrooms to allow students to interact with contextualized historical personas and scenario-based simulations. Data were collected through pre- and post-intervention assessments, classroom observations, and structured student surveys across participating secondary schools. Quantitative analyses demonstrated a statistically significant improvement in students' historical empathy scores and inquiry-driven analytical skills compared to traditional instruction methods. Qualitative findings further revealed that interactive AI simulations fostered greater student engagement, contextual understanding, and critical questioning, while also highlighting the necessity of teacher facilitation to mitigate algorithmic bias and factual inaccuracies. Overall, the findings suggest that thoughtfully integrated generative AI tools can serve as transformative instruments for enhancing historical thinking and active learning in regional educational contexts.
## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…
:seedling: v1.0.0 Release created to accompany paper submission. Added Applied examples and model comparison using Sketch2DES LLM workflow method in notebooks 01-08. Evaluation of LLM workflow steps 1, 2 and end2end in notebooks 09-12 Applied example using NVidia 5090 in notebook…
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