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Gurcan, Fatih; Cagiltay, Nergiz Ercil – Interactive Learning Environments, 2023
Today's dynamic distance learning environments offer a flexible, comfortable, and lifelong learning experience, independent of space and time. In this way, it also supports and develops existing traditional training programs. The increasing importance of knowledge, skills and learning in today's technological life cycle has led to an increase and…
Descriptors: Educational Research, Trend Analysis, Distance Education, Data Analysis
Mubarak, Ahmed Ali; Ahmed, Salah A. M.; Cao, Han – Interactive Learning Environments, 2023
In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…
Descriptors: MOOCs, Learner Engagement, Performance, Student Behavior
Chen, Bodong; Resendes, Monica; Chai, Ching Sing; Hong, Huang-Yao – Interactive Learning Environments, 2017
As collaborative learning is actualized through evolving dialogues, temporality inevitably matters for the analysis of collaborative learning. This study attempts to uncover sequential patterns that distinguish "productive" threads of knowledge-building discourse. A database of Grade 1-6 knowledge-building discourse was first coded for…
Descriptors: Elementary Education, Knowledge Level, Databases, Coding
Kazanidis, Ioannis; Theodosiou, Theodosios; Petasakis, Ioannis; Valsamidis, Stavros – Interactive Learning Environments, 2016
Database files and additional log files of Learning Management Systems (LMSs) contain an enormous volume of data which usually remain unexploited. A new methodology is proposed in order to analyse these data both on the level of both the courses and the learners. Specifically, "regression analysis" is proposed as a first step in the…
Descriptors: Foreign Countries, Online Courses, Course Evaluation, Electronic Learning
Chang, Hsin-Yi – Interactive Learning Environments, 2017
Two investigations were conducted in this study. In the first experiment, the effects of two types of interactivity with a computer simulation were compared: experimentation versus observation interactivity. Experimentation interactivity allows students to use simulations to conduct virtual experiments, whereas observation interactivity allows…
Descriptors: Computer Simulation, Interaction, Scaffolding (Teaching Technique), Experiments
Lu, Owen H. T.; Huang, Jeff C. H.; Huang, Anna Y. Q.; Yang, Stephen J. H. – Interactive Learning Environments, 2017
As information technology continues to evolve rapidly, programming skills become increasingly crucial. To be able to construct superb programming skills, the training must begin before college or even senior high school. However, when developing comprehensive training programmers, the learning and teaching processes must be considered. In order to…
Descriptors: Learner Engagement, Outcomes of Education, Online Courses, Educational Research
Novak, Elena; Johnson, Tristan E.; Tenenbaum, Gershon; Shute, Valerie J. – Interactive Learning Environments, 2016
The study explored instructional benefits of a storyline gaming characteristic (GC) on learning effectiveness, efficiency, and engagement with the use of an online instructional simulation for graduate students in an introductory statistics course. A storyline is a game-design element that connects scenes with the educational content. In order to…
Descriptors: Teaching Methods, Statistics, Educational Games, Instructional Effectiveness
Casquero, Oskar; Ovelar, Ramón; Romo, Jesús; Benito, Manuel; Alberdi, Mikel – Interactive Learning Environments, 2016
The main objective of this paper is to analyse the effect of the affordances of a virtual learning environment and a personal learning environment (PLE) in the configuration of the students' personal networks in a higher education context. The results are discussed in light of the adaptation of the students to the learning network made up by two…
Descriptors: Case Studies, Higher Education, Educational Technology, Technology Uses in Education
Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao – Interactive Learning Environments, 2016
To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…
Descriptors: Reading Strategies, Prediction, Models, Quasiexperimental Design
Asoodar, Maryam; Marandi, Seyyedeh Susan; Vaezi, Shahin; Desmet, Piet – Interactive Learning Environments, 2016
In this study we explored the effect of podcasting on the motivation of the students in an online English for Academic Purposes (EAP) course at the university level (N = 179). By using a mixed-method approach, we analyzed the data collected on the learners' impressions about using podcasts as a learning tool. The particular aim of this study was…
Descriptors: Foreign Countries, English for Academic Purposes, Electronic Learning, Handheld Devices
Tirado, Ramón; Hernando, Ángel; Aguaded, José Ignacio – Interactive Learning Environments, 2015
Interactive relationships in online learning communities can influence the process and quality of knowledge building. The aim of this study is to empirically investigate the relationships between network structures and social knowledge building in an asynchronous writing environment through discussion forums in a learning management system. The…
Descriptors: Foreign Countries, Educational Technology, Electronic Learning, Computer Assisted Instruction