Zobrazeno 1 - 10
of 4 695
pro vyhledávání: '"Martinez-Maldonado A"'
Autor:
Figueroa-Quintana JR; Medicine, San Juan Bautista School of Medicine, Caguas, PRI., Rajput S; Medicine, San Juan Bautista School of Medicine, Caguas, PRI., Chow DJ; Medicine, San Juan Bautista School of Medicine, Caguas, PRI., Estapé ES; Research, San Juan Bautista School of Medicine, Caguas, PRI.; Research, Medical Sciences Campus, University of Puerto Rico, San Juan, PRI.
Publikováno v:
Cureus [Cureus] 2024 Sep 06; Vol. 16 (9), pp. e68776. Date of Electronic Publication: 2024 Sep 06 (Print Publication: 2024).
Autor:
Jin, Yueqiao, Yang, Kaixun, Yan, Lixiang, Echeverria, Vanessa, Zhao, Linxuan, Alfredo, Riordan, Milesi, Mikaela, Fan, Jie, Li, Xinyu, Gašević, Dragan, Martinez-Maldonado, Roberto
Learning analytics dashboards (LADs) simplify complex learner data into accessible visualisations, providing actionable insights for educators and students. However, their educational effectiveness has not always matched the sophistication of the tec
Externí odkaz:
http://arxiv.org/abs/2411.15597
Autor:
Yan, Lixiang, Gašević, Dragan, Zhao, Linxuan, Echeverria, Vanessa, Jin, Yueqiao, Martinez-Maldonado, Roberto
Multimodal Learning Analytics (MMLA) leverages advanced sensing technologies and artificial intelligence to capture complex learning processes, but integrating diverse data sources into cohesive insights remains challenging. This study introduces a n
Externí odkaz:
http://arxiv.org/abs/2411.15590
The rapid integration of generative artificial intelligence (GenAI) technology into education necessitates precise measurement of GenAI literacy to ensure that learners and educators possess the skills to engage with and critically evaluate this tran
Externí odkaz:
http://arxiv.org/abs/2411.00283
Autor:
Yan, Lixiang, Martinez-Maldonado, Roberto, Jin, Yueqiao, Echeverria, Vanessa, Milesi, Mikaela, Fan, Jie, Zhao, Linxuan, Alfredo, Riordan, Li, Xinyu, Gašević, Dragan
Visual learning analytics (VLA) is becoming increasingly adopted in educational technologies and learning analytics dashboards to convey critical insights to students and educators. Yet many students experienced difficulties in comprehending complex
Externí odkaz:
http://arxiv.org/abs/2409.11645
Autor:
Jin, Yueqiao, Yan, Lixiang, Echeverria, Vanessa, Gašević, Dragan, Martinez-Maldonado, Roberto
Integrating generative AI (GAI) into higher education is crucial for preparing a future generation of GAI-literate students. Yet a thorough understanding of the global institutional adoption policy remains absent, with most of the prior studies focus
Externí odkaz:
http://arxiv.org/abs/2405.11800
Autor:
Jin, Yueqiao, Echeverria, Vanessa, Yan, Lixiang, Zhao, Linxuan, Alfredo, Riordan, Tsai, Yi-Shan, Gašević, Dragan, Martinez-Maldonado, Roberto
Multimodal Learning Analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements
Externí odkaz:
http://arxiv.org/abs/2402.19071
Data storytelling (DS) is rapidly gaining attention as an approach that integrates data, visuals, and narratives to create data stories that can help a particular audience to comprehend the key messages underscored by the data with enhanced efficienc
Externí odkaz:
http://arxiv.org/abs/2402.12634
Autor:
Alfredo, Riordan, Echeverria, Vanessa, Jin, Yueqiao, Yan, Lixiang, Swiecki, Zachari, Gašević, Dragan, Martinez-Maldonado, Roberto
The rapid expansion of Learning Analytics (LA) and Artificial Intelligence in Education (AIED) offers new scalable, data-intensive systems but also raises concerns about data privacy and agency. Excluding stakeholders -- like students and teachers --
Externí odkaz:
http://arxiv.org/abs/2312.12751
Generative artificial intelligence (GenAI), exemplified by ChatGPT, Midjourney, and other state-of-the-art large language models and diffusion models, holds significant potential for transforming education and enhancing human productivity. While the
Externí odkaz:
http://arxiv.org/abs/2312.00087