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Xiaona Xia – Interactive Learning Environments, 2023
Effective analysis and demonstration of these data features is of great significance for the optimization of interactive learning environment and learning behavior. Therefore, we take the big data set of learning behavior generated by an online interactive learning environment as the research object, define the features of learning behavior, and…
Descriptors: Learning Strategies, Interaction, Educational Environment, Learning Analytics
Mona Tabatabaee-Yazdi – Interactive Learning Environments, 2024
In the era of COVID-19 and right after the announcement of it as a pandemic and threat to humanity by the World Health Organization, most educational activities were globally forced to shut down their traditional teaching/learning activities. This is one of the biggest and most vital changes of educational settings which have led to migration to…
Descriptors: English (Second Language), Second Language Instruction, COVID-19, Pandemics
Guiqin Liang; Chunsong Jiang; Qiuzhe Ping; Xinyi Jiang – Interactive Learning Environments, 2024
With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students…
Descriptors: Academic Achievement, Prediction, Engineering Education, Online Courses
Ma, Ning; Li, Ya-Meng; Guo, Jia-Hui; Laurillard, Diana; Yang, Min – Interactive Learning Environments, 2023
The use of massive open online courses (MOOCs) for teacher professional development (TDP) has increased in the past decades. This study explored the key factors that influenced teachers' online course completion as a significant indicator of their success in a TPD MOOC. Six key influencing factors (self-efficacy, interaction with curriculum…
Descriptors: Inservice Teacher Education, MOOCs, Faculty Development, Pedagogical Content Knowledge
Prediction of Students' Early Dropout Based on Their Interaction Logs in Online Learning Environment
Mubarak, Ahmed A.; Cao, Han; Zhang, Weizhen – Interactive Learning Environments, 2022
Online learning has become more popular in higher education since it adds convenience and flexibility to students' schedule. But, it has faced difficulties in the retention of the continuity of students and ensure continual growth in course. Dropout is a concerning factor in online course continuity. Therefore, it has sparked great interest among…
Descriptors: Prediction, Dropouts, Interaction, Learning Analytics
Huang, Hsinfu; Lee, Chang-Franw – Interactive Learning Environments, 2022
The aim of the present study was to explore the learning usability factors of 3D modeling in virtual reality environment (VRE). Users' 3D modeling usability factors in VR were investigated through principal component analysis (PCA). Fifty industrial design students participated in the 3D modeling learning in VR experience experiment, and their…
Descriptors: Usability, Computer Simulation, Educational Technology, Geometric Concepts
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Wang, Xueyu; Wang, Jian – Interactive Learning Environments, 2023
The newborn MTI (Master of Translation and Interpreting) program in China is a new platform that induces abundant opportunities for translator training, meanwhile poses methodological and professional challenges. Thus, an interactive teaching and learning model is proposed. This study is devoted to finding out whether the interactive model…
Descriptors: Masters Programs, Translation, Teaching Methods, Language Tests
Li, Yushun; Zhao, Shuxia; Ma, Qingyan; Qian, Chunlan; Lin, Qun – Interactive Learning Environments, 2019
The overall appeal of ICT in education in China is promoting deep integration of ICT technology with teaching. From a regional point of view, intelligent terminals, such as laptop and tablet, were integrated into classroom, in Beijing, Shanghai and other developed cities. Interactive media equipment (whiteboards, interactive TVs and iPad, etc.)…
Descriptors: Foreign Countries, Interaction, Teaching Methods, Regional Schools
Johnson, Genevieve Marie – Interactive Learning Environments, 2014
In educational discourse on human learning (i.e. the result of experience) and development (i.e. the result of maturation), there are three fundamental theoretical frameworks, -- behaviourism, cognitivism and constructivism, each of which have been applied, with varying degrees of success, in online environments. An ecological framework of human…
Descriptors: Interaction, Learning Theories, Electronic Learning, Ecology
Johnson, Mark William; Sherlock, David – Interactive Learning Environments, 2014
The Personal Learning Environment (PLE) has been presented in a number of guises over a period of 10 years as an intervention which seeks the reorganisation of educational technology through shifting the "locus of control" of technology towards the learner. In the intervening period to the present, a number of initiatives have attempted…
Descriptors: Educational Environment, Intervention, Educational Technology, Locus of Control
Rodriguez, Daniel; Sicilia, Miguel Angel; Sanchez-Alonso, Salvador; Lezcano, Leonardo; Garcia-Barriocanal, Elena – Interactive Learning Environments, 2011
The online interaction of learners and tutors in activities with concrete objectives provides a valuable source of data that can be analyzed for different purposes. One of these purposes is the use of the information extracted from that interaction to aid tutors and learners in decision making about either the configuration of further learning…
Descriptors: Electronic Learning, Interaction, Tutors, Social Networks
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

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