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Soyoung Park; Pamela M. Stecker; Sarah R. Powell – Intervention in School and Clinic, 2024
This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…
Descriptors: Student Evaluation, Individualized Instruction, Mathematics Instruction, Progress Monitoring
Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2021
This is the fourth in a series of statistical articles for mathematics teachers. In this article, the authors discuss topics in General Mathematics in Unit 2 Topic 1 (Univariate data analysis and the statistical investigation process) and topics in Essential Mathematics, Unit 2 Topic 1 (Representing and comparing data).
Descriptors: Mathematics Education, Mathematics Instruction, Data Analysis, Graphs
Irene Mauricio Cazorla; Miriam Cardoso Utsumi; Sandra Maria Magina – International Electronic Journal of Mathematics Education, 2023
This article aims to present a first approximation of the conceptual field of measures of central tendency (MCT), grounded in the theory of conceptual fields. We propose six situations according to type of variable, data presentation (raw or grouped) and amount of data. We revisit specific situations for the mean and exemplify several…
Descriptors: Mathematics Education, Mathematical Concepts, Data, Elementary School Mathematics
Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
Corinne Thatcher Day – Mathematics Teacher: Learning and Teaching PK-12, 2025
Since data collection technologies has become a part of daily life, measurement and data requirements now permeate many state mathematics standards, beginning as early as kindergarten and extending through high school. For example, the Standards for Mathematical Content, recommend that kindergarteners "describe and compare measurable…
Descriptors: Middle School Mathematics, Middle School Students, Middle School Teachers, High School Students
Tytler, Russell; Ferguson, Joseph; White, Peta – Learning: Research and Practice, 2020
Increasingly, learning in science and mathematics is considered in terms of induction into the multimodal language practices of the disciplinary community. A strong strand of research in this tradition has involved students being challenged to invent multimodal language forms, and their ideas refined through structured guidance. Often, however,…
Descriptors: Science Instruction, Mathematics Instruction, Inquiry, Teaching Methods
Sarafoglou, Alexandra; van der Heijden, Anna; Draws, Tim; Cornelisse, Joran; Wagenmakers, Eric-Jan; Marsman, Maarten – Psychology Learning and Teaching, 2022
Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…
Descriptors: Bayesian Statistics, Thinking Skills, Undergraduate Students, Psychology
Wilkerson, Michelle Hoda; Laina, Vasiliki – ZDM: The International Journal on Mathematics Education, 2018
Publicly-available datasets, though useful for education, are often constructed for purposes that are quite different from students' own. To investigate and model phenomena, then, students must learn how to repurpose the data. This paper reports on an emerging line of research that builds on work in data modeling, exploratory data analysis, and…
Descriptors: Middle School Students, Thinking Skills, Data Analysis, Statistics
Viswanathan, Sree Aurovindh; VanLehn, Kurt – IEEE Transactions on Learning Technologies, 2018
Effective collaboration between student peers is not spontaneous. A system that can measure collaboration in real-time may be useful, as it could alert an instructor to pairs that need help in collaborating effectively. We tested whether superficial measures of speech and user interface actions would suffice for measuring collaboration. Pairs of…
Descriptors: Cooperative Learning, Data Collection, Data Analysis, Speech Communication
Tran, Dung; Tarr, James E. – International Journal of Science and Mathematics Education, 2018
Through the lenses of statistical investigations and cognitive demands, we examined bivariate data tasks offered in US high school mathematics textbook series--a popular representative of three curriculum types: traditional, integrated, and hybrid. We developed a framework grounded in literature of association topics for the inclusion and…
Descriptors: High Schools, Secondary School Mathematics, Mathematics Instruction, Textbooks
Ferguson, Sarah – Mathematics Teaching in the Middle School, 2019
Building sets, video games, and scatterplots may seem unrelated, but when they are combined into a problem-based learning (PBL) lesson, these elements join to create a unique learning experience. PBL lessons drive instruction by focusing learning and activities around a central challenge or question while providing a relevant, captivating, and…
Descriptors: Mathematics Instruction, Teaching Methods, Problem Based Learning, Problem Solving
Gudivada, Venkat N. – Educational Technology, 2017
Various types of structured data collected by learning management systems such as Moodle have been used to improve student learning outcomes. Learning analytics refers to an assortment of data analysis methods used for this task. These methods typically do not consider unstructured data such as blogs, discussions, e-mail, and course messages.…
Descriptors: Data Collection, Data Analysis, Educational Research, Technology Uses in Education
Aksoy, Esra; Narli, Serkan; Aksoy, Mehmet Akif – International Journal of Research in Education and Science, 2018
In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…
Descriptors: Academically Gifted, Talent Identification, Data Collection, Mathematics Instruction
Moltudal, Synnøve; Høydal, Kjetil; Krumsvik, Rune Johan – Designs for Learning, 2020
Adaptive Learning Technologies (ALT) and Learning Analytics (LA) are expected to contribute to the customisation and personalisation of pupil learning by continually calibrating and adjusting pupils' learning activities towards their skill and competence levels. The overall aim of the study presented in this paper was to obtain a comprehensive…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
Bush, Sarah B.; Albanese, Judith; Karp, Karen S. – Mathematics Teaching in the Middle School, 2016
Historically, some baby names have been more popular during a specific time span, whereas other names are considered timeless. The Internet article, "How to Tell Someone's Age When All You Know Is Her Name" (Silver and McCann 2014), describes the phenomenon of the rise and fall of name popularity, which served as a catalyst for the…
Descriptors: Mathematics Instruction, Grade 6, Prediction, Data Collection