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Korepanova, Antonina; Pata, Kai – International Association for Development of the Information Society, 2023
Art education holds immense value, presenting students with complex problems and diverse solutions. While general art education has received attention from researchers, higher visual art education remains an under-discussed topic. This article aims to address this gap by examining the diversity of pattern elements that art teachers employ during…
Descriptors: Higher Education, Art Education, Visual Arts, Instructional Design
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Larry Musolino – International Society for Technology, Education, and Science, 2024
A new course development is intended for students to investigate the intersection of mathematics with seemingly disparate areas of art, music, architecture, and nature. The course is designed to allow students to explore the hidden connections between the aesthetic pleasures of art, music and nature and that of mathematical foundations and how the…
Descriptors: Interdisciplinary Approach, Art Education, Mathematics Education, Music
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Langerbein, Janine; Massing, Till; Klenke, Jens; Striewe, Michael; Goedicke, Michael; Hanck, Christoph – International Educational Data Mining Society, 2023
Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…
Descriptors: Information Retrieval, Pattern Recognition, Data Analysis, Information Technology
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Cohausz, Lea; Tschalzev, Andrej; Bartelt, Christian; Stuckenschmidt, Heiner – International Educational Data Mining Society, 2023
Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…
Descriptors: Information Retrieval, Data Processing, Pattern Recognition, Information Technology
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Chung, Cheng-Yu; Hsiao, I-Han – International Educational Data Mining Society, 2021
The distributed practice effect suggests that students retain learning content better when they pace their practice over time. The key factors are practice dosage (intensity) and timing (when to practice and how in between). Inspired by the thriving development of image recognition, this study adopts one of the successful techniques,…
Descriptors: Models, Drills (Practice), Pacing, Computer Uses in Education
Fatahi, Somayeh; Moradi, Hadi; Farmad, Elaheh – International Association for Development of the Information Society, 2015
Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of…
Descriptors: Foreign Countries, Cognitive Style, Electronic Learning, Student Behavior
Niemi, David; Gitin, Elena – International Association for Development of the Information Society, 2012
An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…
Descriptors: Higher Education, Online Courses, Academic Persistence, Identification