Reconstructing Gen Z digital historical literacy through AI-based pedagogy in higher education
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History learning plays an important role in fostering historical awareness, national identity, and critical thinking. However, in reality, history learning still relies heavily on memorisation, resulting in underdeveloped digital history literacy among students, particularly in the areas of source verification, bias awareness, and visual reconstruction of events in the face of widespread misinformation. This study aimed to reconstruct digital history literacy among Generation Z by developing and implementing an artificial intelligence (AI)-based learning model for students in the Department of History Education at PGRI Argopuro University in Jember. This study employed an exploratory, sequential, mixed-methods approach to measure digital history literacy before and after model implementation. Results showed that implementing AI-based learning, including adaptive digital assistance, AI-based source analysis, visual history reconstruction, and digital inquiry learning, significantly improved students' digital history literacy from moderate to high levels. Qualitatively, students demonstrated development in critical thinking, creativity in creating visual history reconstructions, and ownership in designing digital history research. The theoretical contribution of this study is the development of a conceptual framework for AI-based digital historical literacy that integrates source verification, bias analysis, and visual historical reconstruction. In practice, these findings suggest the pedagogical and ethical integration of AI into history teaching in higher education to strengthen students' digital literacy in the modern information age.
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