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Yang, Tzu-Chi; Chen, Sherry Y. – Interactive Learning Environments, 2023
Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…
Descriptors: Student Behavior, Educational Technology, Electronic Learning, Cognitive Style
Sonsoles López-Pernas; Mohammed Saqr; Aldo Gordillo; Enrique Barra – Interactive Learning Environments, 2023
Learning analytics methods have proven useful in providing insights from the increasingly available digital data about students in a variety of learning environments, including serious games. However, such methods have not been applied to the specific context of educational escape rooms and therefore little is known about students' behavior while…
Descriptors: Learning Analytics, Educational Games, Student Behavior, Computer Uses in Education
MOOC Performance Prediction and Analysis via Bayesian Network and Maslow's Hierarchical Needs Theory
Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
Zhang, Yuyu; Chan, Kan Kan – Interactive Learning Environments, 2023
Visual analytics (VA) technology has become a significant tool for business decision-makers to explore novel insights. One of its key features is analytical reasoning through interactive visualization that users have direct sensemaking in problem-solving processes. Few studies have examined how VA can be applied in business education for improving…
Descriptors: Visual Aids, Visualization, Learning Analytics, Data Analysis
Buitrago-Ropero, Mauricio Esteban; Ramírez-Montoya, María Soledad; Laverde, Andrés Chiappe – Interactive Learning Environments, 2023
Digital footprints (DF) offer relevant information about educational activities and processes related to strategies of academic assessment, identification of skills and psychological traits of students, and permanence and dropout trends, etc. This study analyzes scientific evidence on the use of DF in education, and shows the results of a…
Descriptors: Educational Technology, Technology Uses in Education, Learning Analytics, Social Networks
Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage
Yung-Hsiang Hu; Bo-Kai Liao; Chieh-Lun Hsieh – Interactive Learning Environments, 2024
It is known that teachers commonly utilize learning platforms equipped with Learning Analytics Dashboards (LAD) to support students in their Self-Regulated Learning (SRL) endeavors. However, students may struggle to effectively employ LAD due to a lack of sufficient metacognitive skills. Co-regulation of learning (CoRL) has been proven to…
Descriptors: Program Effectiveness, Gamification, Learning Analytics, Educational Technology
Axi Wang; Shengquan Yu; Minhong Wang; Ling Chen – Interactive Learning Environments, 2024
Teacher networks and communities have played an important role in teacher professional development. In such contexts, teachers often receive extensive feedback from peers as part of social learning. However, many teachers have difficulty identifying essential information from a large amount of peer feedback, which may impede self-reflection and…
Descriptors: Pedagogical Content Knowledge, Technological Literacy, Teacher Competencies, Peer Evaluation
Lanqin Zheng; Yunchao Fan; Lei Gao; Zichen Huang – Interactive Learning Environments, 2024
Learning analytics has received increasing attention in the field of education. However, few studies have investigated the overall impact of learning analytics interventions on learning achievements. This study aims to close this research gap and examine the sizes of the overall effects of learning analytics interventions on learning achievements…
Descriptors: Learning Analytics, Meta Analysis, Intervention, Academic Achievement
Sun, Fu-Rong; Hu, Hong-Zhen; Wan, Rong-Gen; Fu, Xiao; Wu, Shu-Jing – Interactive Learning Environments, 2022
To determine the impact of cognitive style on change of concept of engagement in the flipped classroom, a sequential analysis from the perspective of Bloom's Taxonomy was conducted to establish if significant differences existed between the learning achievements and engagement of students with different cognitive styles. The participants were…
Descriptors: Learning Analytics, Preservice Teachers, Educational Change, Learner Engagement
Quadir, Benazir; Chen, Nian-Shing; Isaias, Pedro – Interactive Learning Environments, 2022
The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…
Descriptors: Data, Educational Research, Educational Objectives, Data Analysis
Shaheen, Muhammad – Interactive Learning Environments, 2023
Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational…
Descriptors: Undergraduate Students, Programming, Computer Science Education, Educational Objectives
Martinez-Maldonado, Roberto; Elliott, Doug; Axisa, Carmen; Power, Tamara; Echeverria, Vanessa; Buckingham Shum, Simon – Interactive Learning Environments, 2022
Learning Analytics (LA) systems can offer new insights into learners' behaviours through analysis of multiple data streams. There remains however a dearth of research about how LA interfaces can enable effective communication of educationally meaningful insights to teachers and learners. This highlights the need for a participatory, horizontal…
Descriptors: Learning Analytics, Design, Teamwork, Clinical Experience
Pei, Bo; Xing, Wanli; Wang, Minjuan – Interactive Learning Environments, 2023
Multimodal Learning Analytics (MMLA) has huge potential for extending the work beyond traditional learning analytics for the capabilities of leveraging multiple data modalities (e.g. physiological data, digital tracing data). To shed a light on its applications and academic development, a systematic bibliometric analysis was conducted in this…
Descriptors: Learning Analytics, Bibliometrics, Publications, Citations (References)
Shuai He; Yu Lu – Interactive Learning Environments, 2024
Currently, generative AI has undergone rapid development. Numerous studies have attested to the benefits of Gen AI in programming, mathematics and other disciplines. However, since Gen AI mostly uses English as the intrinsic training parameter, it is more effective in facilitating the teaching of courses that use international common notation, but…
Descriptors: Instructional Effectiveness, Technology Uses in Education, Artificial Intelligence, Humanities Instruction

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