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Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation
Buitrago, Mauricio; Chiappe, Andres – Australasian Journal of Educational Technology, 2019
The representation of knowledge is a process widely used in education for its potential to generate deep learning, metacognition, and also in mapping the student's cognitive structure while developing a broad spectrum of thinking skills. Notwithstanding the above mentioned benefits, the development and evolution of new digital ecologies of…
Descriptors: Knowledge Representation, Educational Environment, Educational Technology, Thinking Skills
Sennott, Samuel C.; Akagi, Linda; Lee, Mary; Rhodes, Anthony – Topics in Language Disorders, 2019
Artificially intelligent tools have given us the capability to use technology to address ever more complex challenges. What are the capabilities, challenges, and hazards of incorporating and developing this technology for augmentative and alternative communication (AAC)? "Artificial intelligence" (AI) can be defined as the capability of…
Descriptors: Augmentative and Alternative Communication, Artificial Intelligence, Knowledge Representation, Thinking Skills
Knauf, Rainer; Sakurai, Yoshitaka; Tsuruta, Setsuo; Jantke, Klaus P. – Journal of Educational Computing Research, 2010
University education often suffers from a lack of an explicit and adaptable didactic design. Students complain about the insufficient adaptability to the learners' needs. Learning content and services need to reach their audience according to their different prerequisites, needs, and different learning styles and conditions. A way to overcome such…
Descriptors: Prerequisites, College Instruction, Educational Experiments, Cognitive Style
Chen, Chih-Ming – British Journal of Educational Technology, 2009
Developing personalised web-based learning systems has been an important research issue in e-learning because no fixed learning pathway will be appropriate for all learners. However, most current web-based learning platforms with personalised curriculum sequencing tend to emphasise the learner preferences and interests in relation to personalised…
Descriptors: Electronic Learning, Concept Mapping, Difficulty Level, Cognitive Processes
Reategui, E.; Boff, E.; Campbell, J. A. – Computers & Education, 2008
Traditional hypermedia applications present the same content and provide identical navigational support to all users. Adaptive Hypermedia Systems (AHS) make it possible to construct personalized presentations to each user, according to preferences and needs identified. We present in this paper an alternative approach to educational AHS where a…
Descriptors: Knowledge Representation, Hypermedia, Interaction, Profiles
Whatley, Janice – Journal of Information Technology Education, 2004
Online learning is now a reality, with distributed learning and blended learning becoming more widely used in Higher Education. Novel ways in which undergraduate and postgraduate learning material can be presented are being developed, and methods for helping students to learn online are needed, especially if we require them to collaborate with…
Descriptors: Distance Education, Online Courses, Computer Software, Teamwork
Salem, Abdel-Badeeh M. – 2000
The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Uses in Education, Curriculum Development
Lu, Chun-Hung; Wu, Chia-Wei; Wu, Shih-Hung; Chiou, Guey-Fa; Hsu, Wen-Lian – Educational Technology & Society, 2005
This paper presents a new model for simulating procedural knowledge in the problem solving process with our ontological system, InfoMap. The method divides procedural knowledge into two parts: process control and action performer. By adopting InfoMap, we hope to help teachers construct curricula (declarative knowledge) and teaching strategies by…
Descriptors: Problem Solving, Teaching Methods, Models, Educational Games

Bradford, James H.; Cote-Laurence, Paulette – Computers and the Humanities, 1995
Describes an experimental computer program that attempts to simulate a choreographers' knowledge and expertise. The user expresses a set of rules that describe some of the dynamic aspects of a dance. These rules are applied nondeterministically by a "rule driver" program. The rule driver embodies a heuristic algorithm. (MJP)
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Instruction, Computer Oriented Programs