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Bussani, Andrea; Comici, Cinzia – Physics Teacher, 2023
Data analysis and interpretation has always played a fundamental role in the scientific curricula of high school students. The spread of digitalization has further increased the number of learning environments whereby this topic can be effectively taught: as a matter of fact, the ever-growing diffusion of data science across diverse sectors of…
Descriptors: Learning Analytics, High Schools, Data Interpretation, Data Science
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Lezhnina, Olga; Kismihók, Gábor – International Journal of Research & Method in Education, 2022
In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students' attitudes towards information…
Descriptors: Student Attitudes, Scientific Literacy, Numeracy, Foreign Countries
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Alam, Md. I.; Malone, Lauren; Nadolny, Larysa; Brown, Michael; Cervato, Cinzia – Journal of Computer Assisted Learning, 2023
Background: The substantial growth in gamification research has connected gamified learning to enhanced engagement, improved performance, and greater motivation. Similar to gamification, personalized learning analytics dashboards can enhance student engagement. Objectives: This study explores the student experiences and academic achievements using…
Descriptors: Academic Achievement, Game Based Learning, Introductory Courses, STEM Education
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Eser, Mehmet Taha; Çobanoglu Aktan, Derya – International Journal of Educational Methodology, 2021
Science literacy, which is included in Programme for International Student Assessment (PISA) as an assessment area, is an important research and discussion area of science education literature with all its dimensions. In this study, the clustering results of the students from 34 Organization for Economic Cooperation and Development (OECD)…
Descriptors: Data Analysis, Learning Analytics, Science Education, Scores
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Peffer, Melanie E.; Ramezani, Niloofar; Quigley, David; Royse, Emily; Bruce, Chloe – CBE - Life Sciences Education, 2020
Epistemological beliefs about science (EBAS) or beliefs about the nature of science knowledge, and how that knowledge is generated during inquiry, are an essential yet difficult to assess component of science literacy. Leveraging learning analytics to capture and analyze student practices in simulated or game-based authentic science activities is…
Descriptors: Learning Analytics, Beliefs, Scientific Principles, Inquiry