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Clarivando Francisco Belizário Júnior; Fabiano Azevedo Dorça; Luciana Pereira de Assis; Alessandro Vivas Andrade – International Journal of Learning Technology, 2024
Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…
Descriptors: Artificial Intelligence, Educational Technology, Individualized Instruction, Cognitive Style
Clavié, Benjamin; Gal, Kobi – International Educational Data Mining Society, 2020
We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…
Descriptors: Student Behavior, Electronic Learning, Metadata, Prediction
Chiaráin, Neasa Ní – Research-publishing.net, 2022
"An Corpas Cliste" ('Clever Corpus') is an Irish language learner corpus. The corpus data comes from a purpose-built intelligent Computer Assisted Language Learning (iCALL) platform called "An Scéalaí" ('the Storyteller') and comprises both audio and text, produced by second and third level learners of Irish. Metadata (e.g. L1,…
Descriptors: Computational Linguistics, Irish, Computer Assisted Instruction, Second Language Learning
Hu, Xiangen; Cai, Zhiqiang; Hampton, Andrew J.; Cockroft, Jody L.; Graesser, Arthur C.; Copland, Cameron; Folsom-Kovarik, Jeremiah T. – Grantee Submission, 2019
In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the "learners" interact with the learning "resources" in a given learning "environment" following preset steps of learning…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Metadata, Behavior Patterns
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Slater, Stefan; Baker, Ryan; Ocumpaugh, Jaclyn; Inventado, Paul; Scupelli, Peter; Heffernan, Neil – Grantee Submission, 2016
The creation of crowd-sourced content in learning systems is a powerful method for adapting learning systems to the needs of a range of teachers in a range of domains, but the quality of this content can vary. This study explores linguistic differences in teacher-created problem content in ASSISTments using a combination of discovery with models…
Descriptors: Semantics, Mathematical Applications, Teacher Developed Materials, Correlation
Slater, Stefan; Baker, Ryan; Ocumpaugh, Jaclyn; Inventado, Paul; Scupelli, Peter; Heffernan, Neil – International Educational Data Mining Society, 2016
The creation of crowd-sourced content in learning systems is a powerful method for adapting learning systems to the needs of a range of teachers in a range of domains, but the quality of this content can vary. This study explores linguistic differences in teacher-created problem content in ASSISTments using a combination of discovery with models…
Descriptors: Semantics, Mathematical Applications, Teacher Developed Materials, Correlation
Luz, Bruno N.; Santos, Rafael; Alves, Bruno; Areão, Andreza S.; Yokoyama, Marcos H.; Guimarães, Marcelo P. – International Association for Development of the Information Society, 2015
The main purpose of this paper is to present the importance of Interactive Learning Objects (ILO) to improve the teaching-learning process by assuring a constant interaction among teachers and students, which in turn, allows students to be constantly supported by the teacher. The paper describes the ontology that defines the ILO available on the…
Descriptors: Resource Units, Metadata, Interaction, Learning Processes
Schmoelz, Alexander; Swertz, Christian; Forstner, Alexandra; Barberi, Alessandro – Science Education International, 2014
This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based…
Descriptors: Inquiry, Active Learning, Intelligent Tutoring Systems, Electronic Learning
Tam, Vincent – Interactive Technology and Smart Education, 2012
Purpose: Learning Chinese is unquestionably very important and popular worldwide with the fast economic growth of China. To most foreigners and also local students, one of the major challenges in learning Chinese is to write Chinese characters in correct stroke sequences that are considered as significant in the Chinese culture. However, due to…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Computer System Design, Computer Software
The Social Semantic Web in Intelligent Learning Environments: State of the Art and Future Challenges
Jovanovic, Jelena; Gasevic, Dragan; Torniai, Carlo; Bateman, Scott; Hatala, Marek – Interactive Learning Environments, 2009
Today's technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments…
Descriptors: Models, Interaction, Educational Technology, Design Requirements
Melis, Erica; Goguadze, Giorgi; Homik, Martin; Libbrecht, Paul; Ullrich, Carsten; Winterstein, Stefan – British Journal of Educational Technology, 2006
ActiveMath is a complex web-based adaptive learning environment with a number of components and interactive learning tools. The basis for handling semantics of learning content is provided by its semantic (mathematics) content markup, which is additionally annotated with educational metadata. Several components, tools and external services can…
Descriptors: Web Based Instruction, Intelligent Tutoring Systems, Mathematics Education, Semantics
Colace, Francesco; De Santo, Massimo; Vento, Mi – International Journal on E-Learning, 2005
Thanks to the technological improvements of recent years, distance education represents a real alternative or support to the traditional formative processes. The Internet allows the design of contents, which are able to raise the quality of the traditional formative process. However, the amount of information students can obtain from the Internet…
Descriptors: Internet, Metadata, Intelligent Tutoring Systems, Distance Education
Dietze, Stefan; Gugliotta, Alessio; Domingue, John – Journal of Interactive Media in Education, 2007
IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources--whether data or services--within the learning design is done manually at design-time on the basis of the subjective appraisals…
Descriptors: Learning Strategies, Learning Processes, Metadata, Resource Allocation
Ma, Zongmin – Information Science Publishing, 2006
Collecting and presenting the latest research and development results from the leading researchers in the field of e-learning systems, Web-Based Intelligent E-Learning Systems: Technologies and Applications provides a single record of current research and practical applications in Web-based intelligent e-learning systems. This book includes major…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Web Based Instruction, Distance Education

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