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Showing 1 to 15 of 35 results Save | Export
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Zeynep Gül Dertli; Bahadir Yildiz – Anatolian Journal of Education, 2025
Mathematical modelling and modelling activities are important for making sense of mathematical concepts in different extracurricular and daily life contexts. However, teachers may have difficulties in designing these activities in a way to establish meaningful relationships with real life, in accordance with the modeling process and the objectives…
Descriptors: Prompting, Engineering, Mathematical Models, Mathematics Activities
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Vagelis Plevris – Journal of Civil Engineering Education, 2025
Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.
Descriptors: Civil Engineering, Engineering Education, Artificial Intelligence, Technology Uses in Education
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Juhaina Awawdeh Shahbari – International Journal of Science and Mathematics Education, 2025
The modeling approach is used to prepare students to become responsible citizens and face the challenges and demands of modern times, mainly when they engage in modeling activities using digital tools. This study investigates the features of digital tools used in modeling processes among prospective teachers. Thirty-two prospective mathematics…
Descriptors: Models, Technology, Preservice Teachers, Mathematics Teachers
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Todd Cherner; Teresa S. Foulger; Margaret Donnelly – TechTrends: Linking Research and Practice to Improve Learning, 2025
The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…
Descriptors: Artificial Intelligence, Natural Language Processing, Decision Making, Models
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Liqing Qiu; Lulu Wang – IEEE Transactions on Education, 2025
In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Questioning Techniques, Student Evaluation
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Xueqiao Zhang; Chao Zhang; Jianwen Sun; Jun Xiao; Yi Yang; Yawei Luo – IEEE Transactions on Learning Technologies, 2025
Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…
Descriptors: Artificial Intelligence, Instructional Design, Technology Uses in Education, Cognitive Ability
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Stefan 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
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Gamze Türkmen – Journal of Educational Computing Research, 2025
Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…
Descriptors: Artificial Intelligence, Natural Language Processing, Trust (Psychology), Electronic Learning
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Chang Cai; Gaoxia Zhu; Min Ma – Education and Information Technologies, 2025
Interdisciplinary learning requires students to integrate knowledge and methods from different disciplines, prompting advanced skills development and knowledge construction by connecting diverse subjects. Artificial Intelligence (AI), with its rich information base and abilities to track learning and provide personalized support, has the potential…
Descriptors: Artificial Intelligence, Technology Uses in Education, Interdisciplinary Approach, Influence of Technology
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Mostafa Al-Emran; Bassam Abu-Hijleh; AbdulRahman A. Alsewari – Education and Information Technologies, 2025
Generative Artificial Intelligence (AI) refers to advanced systems capable of creating new content by learning from vast datasets, including text, images, and code. These AI tools are increasingly being integrated into various sectors, including education, where they have the potential to enhance learning experiences. While the existing literature…
Descriptors: Artificial Intelligence, Technology Integration, Information Systems, Success
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Afef Saihi; Mohamed Ben-Daya; Moncer Hariga – Education and Information Technologies, 2025
The integration of AI-chatbots into higher education offers the potential to enhance learning practices. This research aims to explore the factors influencing AI-chatbots adoption within higher education, with a focus on the moderating roles of technological proficiency and academic discipline. Utilizing a survey-based approach and advanced…
Descriptors: Technology Uses in Education, Artificial Intelligence, Higher Education, Technology Integration
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Haozhe Jiang; Ritesh Chugh; Darren Turnbull; Xiaoqin Wang; Suting Chen – International Journal of Science and Mathematics Education, 2025
Despite the burgeoning adoption of informal learning in people's daily lives, the actual effects of informal learning activities, especially technology-related informal learning activities, are much less reported than those of formal learning. Furthermore, there is a notable lack of research on the effects of technology-related informal…
Descriptors: Technology Uses in Education, Informal Education, Mathematics Education, Mathematics Activities
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Xiaodong Wei; Lei Wang; Lap-Kei Lee; Ruixue Liu – Journal of Educational Computing Research, 2025
Notwithstanding the growing advantages of incorporating Augmented Reality (AR) in science education, the pedagogical use of AR combined with Pedagogical Agents (PAs) remains underexplored. Additionally, few studies have examined the integration of Generative Artificial Intelligence (GAI) into science education to create GAI-enhanced PAs (GPAs)…
Descriptors: Artificial Intelligence, Technology Uses in Education, Models, Science Education
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Kamil Çelik; Ahmet Ayaz – Educational Technology Research and Development, 2025
Technological advancements in recent years have accelerated the development of information and communication technologies, introducing numerous innovations. One prominent innovation is the concept of the metaverse, which has gained significant popularity and is increasingly influencing various sectors, including the economy, art, entertainment,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Computer Science Education
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Yang Zhang; Yangping Li; Weiping Hu; Huizhi Bai; Yuanjing Lyu – Journal of Science Education and Technology, 2025
Scientific creativity plays an essential role in science education as an advanced cognitive ability that inspires students to solve scientific problems inventively. The cultivation of scientific creativity relies heavily on effective assessment. Typically, human raters manually score scientific creativity using the Consensual Assessment Technique…
Descriptors: Eye Movements, Artificial Intelligence, Creativity, Scientific Concepts
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