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Kucherenko, Svitlana; Rydland, Veslemøy; Grøver, Vibeke – Early Education and Development, 2023
Research Findings: This study used sequential analysis to investigate teachers' use of literal and inferential questions and their relation to children's responses during small-group shared reading in preschool. Participants were 202 dual-language learners (age 3-5 years) and 53 preschool teachers in multiethnic preschool classrooms in Norway.…
Descriptors: Inferences, Questioning Techniques, Reading Strategies, Preschool Children
Thomas Cook; Mansi Wadhwa; Jingwen Zheng – Society for Research on Educational Effectiveness, 2023
Context: A perennial problem in applied statistics is the inability to justify strong claims about cause-and-effect relationships without full knowledge of the mechanism determining selection into treatment. Few research designs other than the well-implemented random assignment study meet this requirement. Researchers have proposed partial…
Descriptors: Observation, Research Design, Causal Models, Computation
Kenneth A. Frank; Qinyun Lin; Ran Xu; Spiro Maroulis; Anna Mueller – Grantee Submission, 2023
Social scientists seeking to inform policy or public action must carefully consider how to identify effects and express inferences because actions based on invalid inferences will not yield the intended results. Recognizing the complexities and uncertainties of social science, we seek to inform inevitable debates about causal inferences by…
Descriptors: Social Sciences, Research Methodology, Statistical Inference, Robustness (Statistics)
Daniel Rabbett – Australian Mathematics Education Journal, 2023
In this article, examples are shown to demonstrate how open-ended mathematical activities can be used in the classroom. Open-ended activities give students opportunities to apply their understanding in unfamiliar contexts without the pressure of finding one perfect solution.
Descriptors: Foreign Countries, Students, Mathematics Instruction, Mathematical Applications
Yuqi Gu; Elena A. Erosheva; Gongjun Xu; David B. Dunson – Grantee Submission, 2023
Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs incorporate a vector of subject-specific weights characterizing partial membership across clusters. With this flexibility come challenges in uniquely identifying,…
Descriptors: Multivariate Analysis, Item Response Theory, Bayesian Statistics, Models
Tim Erickson – Australian Mathematics Education Journal, 2023
This short article continues the exploration of the Common Online Data Analysis Platform (CODAP) and statistics begun in the previous article "Statistical Investigations and CODAP, Part 1: EDA." In Part 2, the author discusses the teaching of statistical inference focusing on activities for the senior secondary years. In particular, the…
Descriptors: Computer Software, Statistics Education, Statistical Inference, Secondary Education
Mary Jane Gardner; Ru Wu; Patricia R. Todd – Marketing Education Review, 2024
The influence of fonts in marketing education may be underestimated as font usage/selection may benefit both department programs and courses in terms of attracting students and enhancing student learning outcomes. Across four studies, this research examines the effects of handwritten fonts on student inferences from course information. A course…
Descriptors: Handwriting, Course Descriptions, Student Interests, Learner Engagement
Agustina Ammaturo; Jazmín Cevasco – Reading Psychology, 2024
The purpose of this study was to examine the role of the causal connectivity of the statements ("low-medium-high"), elaboration question condition ("focused on the identification of main ideas-focused on the identification of speakers' emotions") and the modality of presentation of discourse ("oral-written") in the…
Descriptors: Discourse Analysis, Causal Models, Questioning Techniques, Comprehension
Mortaza Jamshidian; Parsa Jamshidian – Journal of Statistics and Data Science Education, 2024
Using software to teach statistical inference in introductory courses opens the door for methods and practices that are more conceptually appealing to students. With an increasing number of fields requiring competency in statistics including data science, natural and social sciences, public health and more, it is crucial that we as instructors…
Descriptors: Computer Software, Computer Assisted Instruction, Teaching Methods, Statistics Education
Stella Maris Vázquez; Marianela Noriega-Biggio; Hilda Difabio-de-Anglat – European Journal of Psychology and Educational Research, 2024
The following research presents the outcomes of a cohort study investigating formal thinking skills among first and second-year secondary school students. A specially crafted instrument, the Logical Thought Performance Test for Adolescents (LTPA), was employed to gauge the level of formal thought. The LTP-A assesses various aspects, including:…
Descriptors: Secondary School Students, Foreign Countries, Thinking Skills, Logical Thinking
Jennifer Hill; George Perrett; Stacey A. Hancock; Le Win; Yoav Bergner – Statistics Education Research Journal, 2024
Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…
Descriptors: Statistics Education, Causal Models, Statistical Inference, College Students
Deon T. Benton; David Kamper; Rebecca M. Beaton; David M. Sobel – Developmental Science, 2024
Causal reasoning is a fundamental cognitive ability that enables individuals to learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or…
Descriptors: Preschool Children, Thinking Skills, Associative Learning, Abstract Reasoning
Cristina de-la-Peña; Beatriz Chaves-Yuste; María-Jesús Luque-Rojas – Reading Psychology, 2024
In today's digital context, it is essential for students' academic and personal development to improve their digital reading comprehension. A comparative analysis of digital reading comprehension between three modalities is presented: dual (multimodal), auditory, and visual (monomodal). We used an experimental design and a standardized test…
Descriptors: Electronic Publishing, Reading Comprehension, Multimedia Materials, Secondary School Students
Alison G. Lynch; Elise Lockwood; Amy B. Ellis – Research in Mathematics Education, 2024
In this paper, we explore the role that examples play as mathematicians formulate conjectures, and we describe and exemplify one particular example-related activity that we observed in interviews with thirteen mathematicians. During our interviews, mathematicians productively used examples as they formulated conjectures, particularly by creating…
Descriptors: College Faculty, Mathematical Concepts, Mathematics Education, Mathematics Instruction
Virginia Clinton-Lisell; Sarah E. Carlson; Heather Ness-Maddox; Amanda Dahl; Terrill Taylor; Mark L. Davison; Ben Seipel – Grantee Submission, 2024
The purpose of this study was to examine clusters of less-skilled college readers. College students with below average reading comprehension skills (N = 77) read and thought aloud about four texts, recalled the texts, and completed standardized assessments of reading skills. Based on the findings of cluster analyses of the cognitive processes…
Descriptors: Vocabulary, Reading Comprehension, Reading Tests, Reading Skills

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