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Direct linkStefan Küchemann; Karina E. Avila; Yavuz Dinc; Chiara Hortmann; Natalia Revenga; Verena Ruf; Niklas Stausberg; Steffen Steinert; Frank Fischer; Martin Fischer; Enkelejda Kasneci; Gjergji Kasneci; Thomas Kuhr; Gitta Kutyniok; Sarah Malone; Michael Sailer; Albrecht Schmidt; Matthias Stadler; Jochen Weller; Jochen Kuhn – npj Science of Learning, 2025
Recently, the option to use large language models as a middleware connecting various AI tools and other large language models led to the development of so-called large multimodal foundation models, which have the power to process spoken text, music, images and videos. In this overview, we explain a new set of opportunities and challenges that…
Descriptors: Artificial Intelligence, Technology Uses in Education, Models, Intermode Differences
Kok-Sing Tang – Science Education, 2024
Research in languages and literacies in science education (LLSE) has developed substantial theoretical and pedagogical insights into how students learn science through language, discourse, and multimodal representations. At the same time, language is central to the functioning of generative artificial intelligence (GenAI). On this common basis…
Descriptors: Artificial Intelligence, Meta Analysis, Science Education, Language Usage
Mengjiao Yin; Hengshan Cao; Zuhong Yu; Xianyu Pan – International Journal of Web-Based Learning and Teaching Technologies, 2024
This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…
Descriptors: Predictor Variables, Artificial Intelligence, Performance, Cluster Grouping
Shilpi Harnal; Gaurav Sharma; Anupriya; Anand Muni Mishra; Deepak Bagga; Nikhil Saini; Pankaj Kumar Goley; Kumar Anupam – Journal of Computer Assisted Learning, 2024
Background: An innovative and interactive real-world environment can be presented with augmented reality (AR) that comprises digital visual elements, audio, or other sensory information delivered via technology to enhance one's experience. AR has numerous potential applications in various everyday fields. The education sector is one such arena…
Descriptors: Bibliometrics, Computer Simulation, Artificial Intelligence, Educational Technology
Dongyu Yu; Xing Yao; Kaidi Yu; Dandan Du; Jinyi Zhi; Chunhui Jing – Interactive Learning Environments, 2024
The objective of this study was to determine the differential effects of the presentation position of the augmented reality--head worn display (AR-HWD) interface and the audiovisual-dominant multimodal learning material on learning performance and cognitive load across different learning tasks in training for high-speed train driving. We selected…
Descriptors: Artificial Intelligence, Computer Simulation, Computer Peripherals, Computer Interfaces
Weipeng Yang; Xinyun Hu; Ibrahim H. Yeter; Jiahong Su; Yuqin Yang; John Chi-Kin Lee – Journal of Computer Assisted Learning, 2024
Background: Artificial Intelligence (AI) literacy is a crucial part of digital literacy that all individuals should possess in today's technologically advanced world. Despite the potential benefits that AI education offers, little research has been done on how to teach AI literacy to children. Objectives: This study aimed to fill that gap by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Digital Literacy
Chenghao Wang; Xueyun Li – International Journal of Computer-Assisted Language Learning and Teaching, 2025
D-ID Creative Reality Studio (D-ID) is a platform for creating Artificial Intelligence (AI) presenter (digital human) videos, translating videos, and designing conversational agents. D-ID seamlessly integrates deep-learning face animation technology, large language models (LLMs), natural language processing (NLP), and speech synthesis and…
Descriptors: Artificial Intelligence, Design, Video Technology, Animation
Ai-Chu Elisha Ding – Journal of Research on Technology in Education, 2024
Multilingual learners (MLs) often struggle with science conceptual learning partly due to the abstractness of the concepts and the complexity of scientific texts. This study presents a case of a Virtual Reality (VR) enhanced science learning unit to support middle-school students' science conceptual learning. Using a transformative mixed methods…
Descriptors: Multilingualism, Science Education, Learning Processes, Computer Simulation
Gupta, Sambhav; Chen, Yu – Journal of Information Systems Education, 2022
Supporting student academic success has been one of the major goals for higher education. However, low teacher-to-student ratio makes it difficult for students to receive sufficient and personalized support that they might want to. The advancement of artificial intelligence (AI) and conversational agents, such as chatbots, has provided…
Descriptors: Inclusion, Undergraduate Students, At Risk Students, Artificial Intelligence
Leung, Chun Ming; Tsang, Eva Y. M.; Lam, S. S.; Pang, Dominic C. W. – EDUCAUSE Quarterly, 2010
Universities are increasingly looking into self-service systems with intelligent digital agents to supplement or replace labor-intensive services, such as academic counseling. The Open University of Hong Kong has developed an intelligent online system that instantly responds to enquiries about career development, learning modes, program/course…
Descriptors: Counseling Services, Learning Modalities, Foreign Countries, Natural Language Processing
