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Hamdaoui, Nabila; Idrissi, Mohammed Khalidi; Bennani, Samir – International Journal of Game-Based Learning, 2021
Over the last years there has been a growing interest in the use of educational games as learning tools. Educational games have proven to contribute in enhancing student motivation, increasing their engagement and providing them with personalized and adaptive learning. Learner modeling is a prerequisite when it comes to adaptive learning; it is…
Descriptors: Educational Games, Mathematical Logic, Models, Data Analysis
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
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Slater, Stefan; Baker, Ryan S.; Wang, Yeyu – International Educational Data Mining Society, 2020
Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…
Descriptors: Data Analysis, Engineering, Classification, Models
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Danial Hooshyar; Nour El Mawas; Yeongwook Yang – Knowledge Management & E-Learning, 2024
The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…
Descriptors: Artificial Intelligence, Course Content, Tests, Scores
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Dæhli, Olav; Kristoffersen, Bjørn; Lauvås, Per, Jr.; Sandnes, Tomas – Electronic Journal of e-Learning, 2021
Data modeling is an essential part of IT studies. Learning how to design and structure a database is important when storing data in a relational database and is common practice in the IT industry. Most students need much practice and tutoring to master the skill of data modeling and database design. When a student is in a learning process,…
Descriptors: Game Based Learning, Educational Games, Computer Games, Information Technology
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Seymoens, Tom; Van Audenhove, Leo; Van den Broeck, Wendy; Mariën, Ilse – Journal of Media Literacy Education, 2020
This paper presents "the DataBuzz Project." "DataBuzz" is a high-tech, mobile educational lab, which is housed in a 13-meter electric bus. Its specific goal is to increase the data literacy of different segments of society in the Brussels region through inclusive and participatory games and workshops. In this paper, we will…
Descriptors: Data Analysis, Literacy, Program Descriptions, Laboratories
Snow, Erica L. – International Educational Data Mining Society, 2015
Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…
Descriptors: Intelligent Tutoring Systems, Models, Individualized Instruction, Needs Assessment
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Hsu, Yu-Chang; Ching, Yu-Hui – Canadian Journal of Learning and Technology, 2015
Mobile learning has become increasingly popular in the past decade due to the unprecedented technological affordances achieved through the advancement of mobile computing, which makes ubiquitous and situated learning possible. At the same time, there have been research and implementation projects whose efforts centered on developing mobile…
Descriptors: Electronic Learning, Instructional Design, Classification, Models
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Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Leddo, John – Journal of Instruction Delivery Systems, 1996
Describes work to develop a computer game to teach scientific reasoning. A framework for intelligent tutoring games is presented that includes developing a model of scientific knowledge, developing a model of the phenomenon, developing hypotheses, collecting data, analyzing data, and drawing conclusions. Student attitudes are also discussed. (LRW)
Descriptors: Computer Games, Data Analysis, Educational Games, Intelligent Tutoring Systems
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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Kommers, Piet, Ed.; Issa, Tomayess, Ed.; Issa, Theodora, Ed.; McKay, Elspeth, Ed.; Isias, Pedro, Ed. – International Association for Development of the Information Society, 2016
These proceedings contain the papers and posters of the International Conferences on Internet Technologies & Society (ITS 2016), Educational Technologies (ICEduTech 2016) and Sustainability, Technology and Education (STE 2016), which have been organised by the International Association for Development of the Information Society and…
Descriptors: Conferences (Gatherings), Foreign Countries, Internet, Educational Technology
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