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Mulligan, Joanne; Kirk, Melinda; Tytler, Russell; White, Peta; Capsalis, Maria – Australian Primary Mathematics Classroom, 2022
This article illustrates one of several learning sequences from the Interdisciplinary Mathematics and Science (IMS) Learning project, connecting science and mathematics learning in the primary school. Investigating Body Height involved a series of investigations conducted in Years 5 and 6 across six classes in one school. The project teachers…
Descriptors: Grade 5, Grade 6, Inquiry, Body Height
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
Haara, Frode Olav – European Journal of Science and Mathematics Education, 2022
This article reports on how a pedagogical entrepreneurship approach combined with fundamental elements of mathematical modelling may be used to strengthen students' development of mathematical literacy in upper primary school. This is done first through a review of the relationship between pedagogical entrepreneurship in mathematics, mathematical…
Descriptors: Mathematical Models, Entrepreneurship, Mathematics Instruction, Knowledge Level
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
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
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
Muir, Tracey – Mathematics Education Research Group of Australasia, 2021
National testing and reform agendas, with their focus on school improvement, has led to increased collection and scrutiny of student data. The analysis of these data usually occurs at a school level, often by school leaders. What is less common is the opportunity for students to scrutinise their individual data and take ownership over the results…
Descriptors: Mathematics Instruction, Mathematics Achievement, Foreign Countries, Computation
Kuromiya, Hiroyuki; Majumdar, Rwitajit; Ogata, Hiroaki – Educational Technology & Society, 2020
Evidence-based education has become more relevant in the current technology-enhanced teaching-learning era. This paper introduces how Educational BIG data has the potential to generate such evidence. As evidence-based education traditionally hooks on the meta-analysis of the literature, so there are existing platforms that support manual input of…
Descriptors: Evidence Based Practice, Case Studies, Learning Analytics, Data Collection
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
Bütüner, Suphi Önder; Filiz, Mehmet – International Journal of Mathematical Education in Science and Technology, 2017
The aim of this research was to investigate high achievers' erroneous answers and misconceptions on the angle concept. The participants consisted of 233 grade 6 students drawn from eight classes in two well-established elementary schools of Trabzon, Turkey. All the participants were considered to be current achievers in mathematics, graded 4 or 5…
Descriptors: High Achievement, Grade 6, Misconceptions, Foreign Countries
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
Cavanna, Jillian M. – ProQuest LLC, 2016
The idea of data use as an educational reform strategy has gained significant traction in recent years, but there is limited research that illuminates what actually happens when teachers use data in practice. This study investigates the ways a group of middle school mathematics teachers used data in their classrooms and as part of an action…
Descriptors: Mathematics Instruction, Mathematics Teachers, Middle School Teachers, Action Research
Kroon, Cindy D. – Mathematics Teaching in the Middle School, 2016
Mathematics and science are natural partners. One of many examples of this partnership occurs when scientific observations are made, thus providing data that can be used for mathematical modeling. Developing mathematical relationships elucidates such scientific principles. This activity describes a data-collection activity in which students employ…
Descriptors: Mathematics Instruction, Middle Schools, Secondary School Mathematics, Teaching Methods
Koedinger, Kenneth R.; McLaughlin, Elizabeth A. – International Educational Data Mining Society, 2016
Many educational data mining studies have explored methods for discovering cognitive models and have emphasized improving prediction accuracy. Too few studies have "closed the loop" by applying discovered models toward improving instruction and testing whether proposed improvements achieve higher student outcomes. We claim that such…
Descriptors: Educational Research, Data Collection, Task Analysis, Cognitive Processes

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