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Elmoazen, Ramy; Saqr, Mohammed; Khalil, Mohammad; Wasson, Barbara – Smart Learning Environments, 2023
Remote learning has advanced from the theoretical to the practical sciences with the advent of virtual labs. Although virtual labs allow students to conduct their experiments remotely, it is a challenge to evaluate student progress and collaboration using learning analytics. So far, a study that systematically synthesizes the status of research on…
Descriptors: Learning Analytics, Higher Education, Medical Education, Student Behavior
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McEneaney, John; Morsink, Paul – Journal of Learning Analytics, 2022
Learning analytics (LA) provides tools to analyze historical data with the goal of better understanding how curricular structures and features have impacted student learning. Forward-looking curriculum design, however, frequently involves a degree of uncertainty. Historical data may be unavailable, a contemplated modification to curriculum may be…
Descriptors: Curriculum Design, Learning Analytics, Educational Change, Computer Software
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Lisa Stark; Andreas Korbach; Roland Brünken; Babette Park – Journal of Computer Assisted Learning, 2024
Background: Both learning and problem solving are major goals of complex problem solving in engineering education. The order of knowledge construction and problem solving in learning through problem solving, however, has not been explained in current literature. Objectives: To understand their relationships, this study compared the effects of…
Descriptors: Metacognition, Multimedia Instruction, Multimedia Materials, Eye Movements
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Cheng, Ching-I. – Journal of Computer Assisted Learning, 2023
Background: Taiwan's higher education institutions prioritize interdisciplinary knowledge and cultural competence in cultural design, emphasizing the value of immersion in the local environment to develop cultural competence. However, challenges arise from the disappearance of traditional local lifestyles and limitations of traditional outdoor…
Descriptors: Foreign Countries, Learning Analytics, Handheld Devices, Computer Oriented Programs
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Cock, Jade; Marras, Mirko; Giang, Christian; Käser, Tanja – International Educational Data Mining Society, 2021
Interactive simulations allow students to independently explore scientific phenomena and ideally infer the underlying principles through their exploration. Effectively using such environments is challenging for many students and therefore, adaptive guidance has the potential to improve student learning. Providing effective support is, however,…
Descriptors: Prediction, Concept Formation, Scientific Concepts, Physics
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Oscar Yecid Aparicio-Gómez; Olga Lucia Ostos-Ortiz; Constanza Abadía-García – Journal of Technology and Science Education, 2024
In today's educational environment, the convergence of emerging technologies and active methodologies has become a fundamental driver of change in university education. Emerging technologies, such as artificial intelligence, virtual reality, machine learning, and data analytics, are redefining the dynamics of higher education. Active…
Descriptors: Technological Advancement, Technology Uses in Education, Higher Education, Problem Based Learning
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Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making
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Amaya, Edna Johanna Chaparro; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2023
Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…
Descriptors: Learning Analytics, Guidelines, Student Attitudes, Learning Processes
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Hanall Sung; Mitchell J. Nathan – British Journal of Educational Technology, 2024
Collaborative learning, driven by knowledge co-construction and meaning negotiation, is a pivotal aspect of educational contexts. While gesture's importance in conveying shared meaning is recognized, its role in collaborative group settings remains understudied. This gap hinders accurate and equitable assessment and instruction, particularly for…
Descriptors: Cooperative Learning, Motion, Human Body, Learning Analytics
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Li, Shan; Huang, Xiaoshan; Wang, Tingting; Pan, Zexuan; Lajoie, Susanne P. – Journal of Learning Analytics, 2022
This study examines the temporal co-occurrences of self-regulated learning (SRL) activities and three types of knowledge (i.e., task information, domain knowledge, and metacognitive knowledge) of 34 medical students who solved two tasks of varying complexity in a computer-simulated environment. Specifically, we explored how task complexity…
Descriptors: Correlation, Metacognition, Task Analysis, Difficulty Level
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Yiqiu Zhou; Jina Kang – Journal of Learning Analytics, 2023
Collaboration is a complex, multidimensional process; however, details of how multimodal features intersect and mediate group interactions have not been fully unpacked. Characterizing and analyzing the temporal patterns based on multimodal features is a challenging yet important work to advance our understanding of computer-supported collaborative…
Descriptors: Attention Control, Cooperative Learning, Data Analysis, Computer Assisted Instruction
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Hernández-Lara, Ana Beatriz; Perera-Lluna, Alexandre; Serradell-López, Enric – Education & Training, 2021
Purpose: With the growth of digital education, students increasingly interact in a variety of ways. The potential effects of these interactions on their learning process are not fully understood and the outcomes may depend on the tool used. This study explores the communication patterns and learning effectiveness developed by students using two…
Descriptors: Game Based Learning, Learning Analytics, Computer Mediated Communication, Asynchronous Communication
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Pence, Harry E. – Education Sciences, 2020
Chemical educators are facing a new generation of instructional technologies that impact classroom teaching. New technologies, like smartphones, cloud computing and artificial intelligence take learning beyond the classroom; 3D printing, virtual reality, and augmented reality provide new ways to teach the virtualization skills that are important…
Descriptors: Chemistry, Educational Technology, Telecommunications, Handheld Devices
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Shahzad, Muhammad; Nadeem, Muhammad Asif; U-Nisa, Zaib – Pakistan Journal of Distance and Online Learning, 2021
The study was conducted in three phases that is testing, using multimedia and observation of the controlled group. Major objective of the research were to assess the implications of software development design on learners and to identify effects of interactive multimedia environment on learning patterns of learners' at graduate level. The…
Descriptors: Educational Environment, Multimedia Instruction, Instructional Effectiveness, Hypermedia
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Cherner, Todd; Halpin, Peter – Journal of Interactive Learning Research, 2021
Virtual reality (VR) is an emerging technology that is gaining traction in K12 education. Whereas well-designed and engaging VR experiences may be considered educational, teacher educators with content-area expertise are uniquely positioned to analyze the actual content provided by those experiences when determining VR's educational value.…
Descriptors: Content Analysis, Computer Software, Computer Simulation, Preservice Teachers
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