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Fergusson, Anna; Wild, Chris J. – Teaching Statistics: An International Journal for Teachers, 2021
The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data…
Descriptors: Data, Data Analysis, Skill Development, Discovery Learning
Berikan, Burcu; Özdemir, Selçuk – Journal of Educational Computing Research, 2020
This study aims to investigate problem-solving with dataset (PSWD) as a computational thinking learning implementation as reflected in academic publications. Specifically, the purpose is to specify the scope of PSWD, which overlaps with the data literacy, thinking with data, big data literacy, and data-based thinking concepts in the literature.…
Descriptors: Problem Solving, Data Analysis, Thinking Skills, Computation
Peter Organisciak; Michele Newman; David Eby; Selcuk Acar; Denis Dumas – Grantee Submission, 2023
Purpose: Most educational assessments tend to be constructed in a close-ended format, which is easier to score consistently and more affordable. However, recent work has leveraged computation text methods from the information sciences to make open-ended measurement more effective and reliable for older students. This study asks whether such text…
Descriptors: Learning Analytics, Child Language, Semantics, Age Differences
OECD Publishing, 2013
Effective teaching and teachers are key to producing high-performing students worldwide. So how can countries prepare teachers to face the diverse challenges in today's schools? The Teaching and Learning International Survey (TALIS) helps answer this question. TALIS asks teachers and schools about their working conditions and the learning…
Descriptors: Surveys, Foreign Countries, Teaching Conditions, Work Environment

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