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Nie, Rui; Guo, Qi; Morin, Maxim – Educational Measurement: Issues and Practice, 2023
The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, "Machine Learning" (ML) emerges as an increasingly important skill in the toolbox of measurement…
Descriptors: Artificial Intelligence, Electronic Learning, Literacy, Educational Assessment
Zhi Liu; Huimin Duan; Shiqi Liu; Rui Mu; Sannyuya Liu; Zongkai Yang – Educational Technology & Society, 2024
Conversational agents (CAs) primarily adopt knowledge scaffolding (KS) or emotional scaffolding (ES) to intervene in learners' knowledge gain and emotional experience in online learning. However, the ill-defined design for KS and ES, as well as insufficient understanding of their interactive effects on learning outcomes, have hindered the…
Descriptors: Electronic Learning, Achievement Gains, Knowledge Level, Emotional Experience
Lafuente, Deborah; Cohen, Brenda; Fiorini, Guillermo; Garci´a, Agusti´n Alejo; Bringas, Mauro; Morzan, Ezequiel; Onna, Diego – Journal of Chemical Education, 2021
Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…
Descriptors: Undergraduate Students, Chemistry, Electronic Learning, Artificial Intelligence
Jia, Jiyou; He, Yunfan – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is to design and implement an intelligent online proctoring system (IOPS) by using the advantage of artificial intelligence technology in order to monitor the online exam, which is urgently needed in online learning settings worldwide. As a pilot application, the authors used this system in an authentic…
Descriptors: Artificial Intelligence, Supervision, Computer Assisted Testing, Electronic Learning
Yueh-Hui Vanessa Chiang; Maiga Chang; Nian-Shing Chen – Educational Technology & Society, 2024
Generative Artificial Intelligence (AI), especially machine learning models that autonomously generate human-like content, has recently attracted significant attention in the education sector. This paper explores the potential of generative AI, including tools like ChatGPT, to shift from traditional outcome-oriented educational practices to a more…
Descriptors: Artificial Intelligence, Educational Practices, Process Education, Educational Objectives
Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction
Zemirline, N.; Bourda, Y.; Reynaud, C. – IEEE Transactions on Learning Technologies, 2012
Today, there is a real challenge to enable personalized access to information. Several systems have been proposed to address this challenge including Adaptive Hypermedia Systems (AHSs). However, the specification of adaptation strategies remains a difficult task for creators of such systems. In this paper, we consider the problem of the definition…
Descriptors: Programming, Programming Languages, Computer Software, Access to Information
Pernas, Ana Marilza; Diaz, Alicia; Motz, Regina; de Oliveira, Jose Palazzo Moreira – Interactive Technology and Smart Education, 2012
Purpose: The broader adoption of the internet along with web-based systems has defined a new way of exchanging information. That advance added by the multiplication of mobile devices has required systems to be even more flexible and personalized. Maybe because of that, the traditional teaching-controlled learning style has given up space to a new…
Descriptors: Electronic Learning, Student Needs, Cognitive Style, Internet
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
Rosson, Mary Beth, Ed. – InTech, 2010
Readers will find several papers that address high-level issues in the use of technology in education, for example architecture and design frameworks for building online education materials or tools. Several other chapters report novel approaches to intelligent tutors or adaptive systems in educational settings. A number of chapters consider many…
Descriptors: Educational Technology, Student Projects, Active Learning, Information Systems
Aroyo, Lora; Dicheva, Darina – Educational Technology & Society, 2004
The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it?…
Descriptors: Semantics, Semiotics, Internet, Electronic Learning