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Showing all 13 results Save | Export
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Zheng Zheng; Jun Wang – npj Science of Learning, 2024
While statistical learning is often studied individually, its collective representation through self-other integration remains unclear. This study examines dynamic self-other integration and its multi-brain mechanism using simultaneous recordings from dyads. Participants (N = 112) each repeatedly responded to half of a fixed stimulus sequence with…
Descriptors: Statistics Education, Cooperative Learning, Observational Learning, Learning Processes
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Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
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Udi Alter; Carmen Dang; Zachary J. Kunicki; Alyssa Counsell – Teaching Statistics: An International Journal for Teachers, 2024
The biggest difference in statistical training from previous decades is the increased use of software. However, little research examines how software impacts learning statistics. Assessing the value of software to statistical learning demands appropriate, valid, and reliable measures. The present study expands the arsenal of tools by reporting on…
Descriptors: Statistics Education, Student Attitudes, Course Descriptions, Social Sciences
Meng Li – Mathematics Education Research Group of Australasia, 2024
The profound advancements in technology have rendered novel forms of data and data visualisation increasingly accessible to individuals within society, thereby influencing daily decision-making processes. To address this change, this study sets out to review recent research on data-driven inquiries at the K-12 level from two perspectives:…
Descriptors: Visual Aids, Data Analysis, Mathematics Instruction, Statistics Education
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Ung Hua Lau; Zaidatun Tasir – Educational Technology Research and Development, 2024
An online authentic learning environment (OnALE) is proposed in this study to facilitate students' learning of inferential statistics in a real-life context. The efficacy of the OnALE, in comparison to the conventional approach relative to the students' performance, was explored. Respondents from the experimental group were purposively selected to…
Descriptors: Online Courses, Authentic Learning, Academic Achievement, Comparative Analysis
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Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
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María del Mar López-Martín; María Burgos Navarro; Verónica Albanese – Statistics Education Research Journal, 2025
To ensure the learning of mathematics, teachers must be able to analyse their students' mathematical practices when solving tasks, interpret the difficulties that students encounter, and decide how to manage students' difficulties. This competence in didactic analysis and intervention allows teachers to adapt their teaching to meet individual…
Descriptors: Statistics Education, Mathematics Instruction, Student Needs, Preservice Teachers
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Paul Christian Dawkins Ed.; Amy J. Hackenberg Ed.; Anderson Norton Ed. – Research in Mathematics Education, 2024
The book provides an entry point for graduate students and other scholars interested in using the constructs of Piaget's genetic epistemology in mathematics education research. Constructs comprising genetic epistemology form the basis for some of the most well-developed theoretical frameworks available for characterizing learning, particularly in…
Descriptors: Mathematics Education, Educational Research, Piagetian Theory, Learning Processes
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Cristina Portalés; Javier Sevilla; Pablo Casanova-Salas; Mar Gaitán; Sergio Casas – Journal of Geography in Higher Education, 2025
Data visualization is a complex matter and so is teaching it in the context of engineering and data science. Even more challenging is teaching in a midst of once in a century pandemic. In this paper, we show the results of a workshop conducted with second-year students on a university degree in data science, which took place in the context of…
Descriptors: Blended Learning, Geography Instruction, Learning Processes, Workshops
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Joel Weijia Lai; Wei Qiu; Maung Thway; Lei Zhang; Nurabidah Binti Jamil; Chit Lin Su; Samuel S. H. Ng; Fun Siong Lim – Journal of Learning Analytics, 2025
The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…
Descriptors: Artificial Intelligence, Computer Software, Learning Analytics, Introductory Courses
Mitali Thatte; Katie Makar – Mathematics Education Research Group of Australasia, 2024
This study was conducted in Maharashtra, India with children studying in a regional medium (Marathi) government school. In Marathi, the translation of the word 'about' is not very commonly used. The aim of the study was to see how the children used uncertain language about prediction while engaged in a statistical investigation and how children…
Descriptors: Mathematics Instruction, Teaching Methods, Native Language, Language of Instruction
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Jessica Sickler; Michelle Lentzner; Lynn T. Goldsmith; Lauren Brase; Randall Kochevar – International Journal of Science Education, 2024
The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports…
Descriptors: Elementary School Students, Grade 3, Grade 4, Grade 5
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Anna Khalemsky; Yelena Stukalin – Statistics Education Research Journal, 2024
The article describes the inclusive perspective of instruction of multi-stage practical projects in undergraduate non-STEM statistics and data mining courses at an academic college in Israel. The student population is highly diverse, comprising individuals from various cultural and ethnic groups. The study examines the impact of diversity on…
Descriptors: Foreign Countries, Undergraduate Students, Statistics Education, Data Science