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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
Moore, Russell; Caines, Andrew; Elliott, Mark; Zaidi, Ahmed; Rice, Andrew; Buttery, Paula – International Educational Data Mining Society, 2019
Educational systems use models of student skill to inform decision-making processes. Defining such models manually is challenging due to the large number of relevant factors. We propose learning multidimensional representations (embeddings) from student activity data -- these are fixed-length real vectors with three desirable characteristics:…
Descriptors: Models, Knowledge Representation, Skills, Artificial Intelligence
Paquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2018
This paper summarizes key stages in development of the Structural Learning Theory (SLT) and explains how and why it is now possible to model human tutors in a highly efficient manner. The paper focuses on evolution of the SLT, a deterministic theory of teaching and learning, on which AuthorIT authoring and TutorIT delivery systems have been built.…
Descriptors: Artificial Intelligence, Models, Tutors, Learning Theories
Boyer, Kristy Elizabeth; Phillips, Robert; Ingram, Amy; Ha, Eun Young; Wallis, Michael; Vouk, Mladen; Lester, James – International Journal of Artificial Intelligence in Education, 2011
Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems research. Human-human tutoring offers a valuable model for identifying effective tutorial strategies, but extracting them is a challenge because of the richness of human dialogue. This article addresses that challenge through a machine learning…
Descriptors: Markov Processes, Intelligent Tutoring Systems, Tutoring, Program Effectiveness
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

Johnstone, A. H. – Journal of Chemical Education, 1997
Suggests that the development of good chemistry teaching and the pursuit of research have essentially the same structure. Similarities include the need for a clear focus, efficiency in time and effort, and a direction that is more often right than wrong. (DDR)
Descriptors: Artificial Intelligence, Chemistry, Cognitive Psychology, Educational Researchers
Chernyi, A. I. – International Forum on Information and Documentation, 1997
Discusses knowledge, organization, and the organization and representation of knowledge. Addresses the relevance of international auxiliary languages as problems of development and use of special sign systems. Argues that--for computer realization of intellectual processes by modeling, not imitation--the psychological mechanisms of human memory…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Software Development, Computer System Design
Aroyo, Lora; Mizoguchi, Riichiro – Journal of Interactive Learning Research, 2004
The ultimate aim of this research is to specify and implement a general authoring framework for content and knowledge engineering for Intelligent Educational Systems (IES). In this context we attempt to develop an authoring tool supporting this framework that is powerful in its functionality, generic in its support of instructional strategies and…
Descriptors: Educational Strategies, Engineering, Programming, Intelligent Tutoring Systems
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