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Direct linkYuanyuan Yang; Rwitajit Majumdar; Huiyong Li; Brendan Flanagan; Hiroaki Ogata – Interactive Learning Environments, 2024
Self-directed learning (SDL) requires students to take initiative to learn and control their own learning process. Literature highlights the importance of SDL for lifelong learning. Yet, little understanding is known regarding how to support SDL at the school level, specifically for out-of-class learning context. To fill up this gap, this research…
Descriptors: Learning Analytics, Independent Study, Learning Processes, Reading Habits
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
Changhao Liang; Rwitajit Majumdar; Yuta Nakamizo; Brendan Flanagan; Hiroaki Ogata – Interactive Learning Environments, 2024
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…
Descriptors: Algorithms, Group Dynamics, Group Activities, Learning Analytics
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
Liu, Min; Li, Chenglu; Pan, Zilong; Pan, Xin – Interactive Learning Environments, 2023
More research is needed on how to best use analytics to support educational decisions and design effective learning environments. This study was to explore and mine the data captured by a digital educational game designed for middle school science to understand learners' behavioral patterns in using the game, and to use evidence-based findings to…
Descriptors: Computer Games, Educational Games, Instructional Design, Instructional Effectiveness
Hershkovitz, Arnon; Sitman, Raquel; Israel-Fishelson, Rotem; Eguíluz, Andoni; Garaizar, Pablo; Guenaga, Mariluz – Interactive Learning Environments, 2019
Many worldwide initiatives consider both creativity and computational thinking as crucial skills for future citizens, making them a priority for today's learners. We studied the associations between these two constructs among middle school students (N = 57), considering two types of creativity: a general creative thinking, and a specific…
Descriptors: Creativity, Creative Thinking, Computation, Computer Assisted Instruction
Macarini, Luiz Antonio; Lemos dos Santos, Henrique; Cechinel, Cristian; Ochoa, Xavier; Rodés, Virgínia; Pérez Casas, Alén; Lucas, Pedro Pablo; Maya, Ricardo; Alonso, Guillermo Ettlin; Díaz, Patricia – Interactive Learning Environments, 2020
The present work describes the challenges faced during the development of a countrywide Learning Analytics study and tool focused on tracking and understanding the trajectories of Uruguayan students during their first three years of secondary education. Due to the large scale of the project, which covers an entire national educational system,…
Descriptors: Program Implementation, Foreign Countries, Learning Analytics, Secondary School Students
