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Troussas, Christos; Giannakas, Filippos; Sgouropoulou, Cleo; Voyiatzis, Ioannis – Interactive Learning Environments, 2023
Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…
Descriptors: Computer Assisted Instruction, Cognitive Style, Cooperative Learning, Models
Poitras, Eric; Butcher, Kirsten R.; Orr, Matthew; Hudson, Michelle A.; Larson, Madlyn – Interactive Learning Environments, 2022
This study mined student interactions with visual representations as a means to automate assessment of learning in a complex, inquiry-based learning environment. Log trace data of 143 middle school students' interactions with an interactive map in Research Quest (an inquiry-based, online learning environment) were analyzed. Students used the…
Descriptors: Middle School Students, Electronic Learning, Maps, Science Instruction
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
Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
Radosavljevic, Slavica; Radosavljevic, Vitomir; Grgurovic, Biljana – Interactive Learning Environments, 2020
The goal of higher vocational education is professional training of students. Teaching contents related to practical training are the most important for preparing students for work in real-life conditions. The mobile learning model presented in this paper analyzes the possibility of implementing augmented reality in the process of educating…
Descriptors: Telecommunications, Handheld Devices, Computer Simulation, Models
Álvarez, Ainhoa; Martín, Maite; Fernández-Castro, Isabel; Urretavizcaya, Maite – Interactive Learning Environments, 2016
Currently, most of the educational approaches applied to higher education combine face-to-face (F2F) and computer-mediated instruction in a Blended-Learning (B-Learning) approach. One of the main challenges of these approaches is fully integrating the traditional brick-and-mortar classes with online learning environments in an efficient and…
Descriptors: Teaching Methods, Higher Education, Blended Learning, Conventional Instruction
Pribeanu, Costin; Balog, Alexandru; Iordache, Dragos Daniel – Interactive Learning Environments, 2017
Augmented reality (AR) technologies could enhance learning in several ways. The quality of an AR-based educational platform is a combination of key features that manifests in usability, usefulness, and enjoyment for the learner. In this paper, we present a multidimensional model to measure the quality of an AR-based application as perceived by…
Descriptors: Computer Simulation, Educational Technology, Measurement, Educational Quality
Sadeghi, Hamid; Kardan, Ahmad A. – Interactive Learning Environments, 2016
Group formation task as a starting point for computer-supported collaborative learning plays a key role in achieving pedagogical goals. Various approaches have been reported in the literature to address this problem, but none have offered an optimal solution. In this research, an online learning environment was modeled as a weighted undirected…
Descriptors: Foreign Countries, Cooperative Learning, Group Dynamics, Online Courses
Huang, Xiaoxia – Interactive Learning Environments, 2017
Previous research has indicated the disconnect between example-based research focusing on worked examples (WEs) and that focusing on modeling examples. The purpose of this study was to examine and compare the effect of four different types of examples from the two separate lines of research, including standard WEs, erroneous WEs, expert (masterly)…
Descriptors: Teaching Methods, Problem Solving, Academic Achievement, Cognitive Processes
Jacobson, Michael J.; Kim, Beaumie; Pathak, Suneeta; Zhang, BaoHui – Interactive Learning Environments, 2015
This research explores issues related to the sequencing of structure that is provided as pedagogical guidance. A study was conducted that involved grade 10 students in Singapore as they learned concepts about electricity using four NetLogo Investigations of Electricity agent-based models. It was found that the low-to-high structure learning…
Descriptors: Grade 10, High School Students, Energy, Pretests Posttests
Baloian, Nelson; Pino, Jose A.; Hardings, Jens – Interactive Learning Environments, 2011
The discovery or re-construction of scientific explanations and understanding based on experience is a complex process, for which school learning often uses shortcuts. On the basis of the example of analyzing real seismic measurements, we propose a computer-facilitated collaborative learning scenario which meets many of the requirements for…
Descriptors: Computer Assisted Instruction, Seismology, Educational Environment, Models
Capuano, Nicola; Gaeta, Matteo; Marengo, Agostino; Miranda, Sergio; Orciuoli, Francesco; Ritrovato, Pierluigi – Interactive Learning Environments, 2009
Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA)…
Descriptors: Distance Education, Online Courses, Laboratories, Individualized Instruction
Capuruco, Renato A. C.; Capretz, Luiz F. – Interactive Learning Environments, 2009
There have been a number of frameworks and models developed to support different aspects of interactive learning. Some were developed to deal with course design through the application of authoring tools, whereas others such as conversational, advisory, and ontology-based systems were used in virtual classrooms to improve and support collaborative…
Descriptors: Learning Activities, Web Based Instruction, Online Courses, Computer Assisted Instruction
Liang, Hai-Ning; Sedig, Kamran – Interactive Learning Environments, 2009
Interactive learning environments (ILEs) are increasingly used to support and enhance instruction and learning experiences. ILEs maintain and display information, allowing learners to interact with this information. One important method of interacting with information is navigation. Often, learners are required to navigate through the information…
Descriptors: Computer Interfaces, Hypermedia, Models, Evaluation Methods
South, Joseph B.; Gabbitas, Bruce; Merrill, Paul F. – Interactive Learning Environments, 2008
In this paper we discuss how the Brigham Young University Technology Assisted Language Learning Group (BYU TALL Group) develops video-based dramatic narratives to increase the amount of context we provide to English as a second language (ESL) learners. First, we discuss the problem of decontextualization in education, the contextualism…
Descriptors: Case Studies, Educational Technology, Second Language Learning, Second Language Instruction
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