Historical Dataset of Williston Basin 7 School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Math Proficiency Trends,Graduation Rate Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (2022-2023),Asian Student Percentage Comparison Over Years (2022-2023),Hispanic Student Percentage Comparison Over Years (2022-2023),Black Student Percentage Comparison Over Years (2022-2023),White Student Percentage Comparison Over Years (2022-2023),Two or More Races Student Percentage Comparison Over Years (2022-2023),Comparison of Students By Grade Trends

Usable Math is a free & open interactive website where you'll find learning modules designed to develop mathematical problem solving skills among young learners in grades 3 to 7. Visit UsableMath.org.

New York City Results on the New York State Mathematics Tests, Grades 3 - 8 Notes: As of 2006, the New York State Education Department expanded the ELA and mathematics testing programs to Grades 3-8. Previously, state tests were administered in Grades 4 and 8 and citywide tests were administered in Grades 3, 5, 6, and 7. In 2006, NYSED treated District 75 students as a distinct geographic district. For 2007-2011, District 75 students are represented in their home districts and boroughs. Spreadsheets for District and Borough do not include District 75 students in 2006. Starting in 2010, NYSED changed the scale score required to meet each of the proficiency levels, increasing the number of questions students needed to answer correctly to meet proficiency.

Historical Dataset of Indian Creek Middle School Grades 7 & 8 is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1990-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1990-2023),Asian Student Percentage Comparison Over Years (1996-2010),Hispanic Student Percentage Comparison Over Years (1996-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1992-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2002-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2012-2023),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2012-2023)

Historical Dataset of Lake County SD 7 School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Graduation Rate Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (1991-2023),Asian Student Percentage Comparison Over Years (1991-2022),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (2004-2009),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Comparison of Students By Grade Trends

Dataset Card for Vietnamese Grade School Math Dataset

  Dataset Summary

The dataset includes multiple-choice math exercises for elementary school students from grades 1 to 5 in Vietnam.

  Supported Tasks and Leaderboards





  Languages

The majority of the data is in Vietnamese.

  Dataset Structure





  Data Instances

The data includes information about the page paths we crawled and some text that has been post-processed. The structure will be… See the full description on the dataset page: https://huggingface.co/datasets/hllj/vi_grade_school_math_mcq.

Analysis of ‘2006 - 2011 NYS Math Test Results By Grade - Boro - All Students’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a25ce45c-3b87-4b15-b994-b65b6ab91f58 on 13 November 2021.

--- Dataset description provided by original source is as follows ---

New York City Results on the New York State Mathematics Tests, Grades 3 - 8 Notes: As of 2006, the New York State Education Department expanded the ELA and mathematics testing programs to Grades 3-8. Previously, state tests were administered in Grades 4 and 8 and citywide tests were administered in Grades 3, 5, 6, and 7. In 2006, NYSED treated District 75 students as a distinct geographic district. For 2007-2011, District 75 students are represented in their home districts and boroughs. Spreadsheets for District and Borough do not include District 75 students in 2006. Starting in 2010, NYSED changed the scale score required to meet each of the proficiency levels, increasing the number of questions students needed to answer correctly to meet proficiency.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘2006 - 2011 NYS Math Test Results By Grade - Boro - By Gender’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/31ab4310-cbc3-4e9e-9832-8bac45a7efb7 on 13 November 2021.

--- Dataset description provided by original source is as follows ---

New York City Results on the New York State Mathematics Tests, Grades 3 - 8 Notes: As of 2006, the New York State Education Department expanded the ELA and mathematics testing programs to Grades 3-8. Previously, state tests were administered in Grades 4 and 8 and citywide tests were administered in Grades 3, 5, 6, and 7. In 2006, NYSED treated District 75 students as a distinct geographic district. For 2007-2011, District 75 students are represented in their home districts and boroughs. Spreadsheets for District and Borough do not include District 75 students in 2006. Starting in 2010, NYSED changed the scale score required to meet each of the proficiency levels, increasing the number of questions students needed to answer correctly to meet proficiency.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘2006 - 2011 NYS Math Test Results By Grade 2006-2011 - District - All Students’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/699ac33d-2326-4ba7-b51c-a0cb70ea33e0 on 13 November 2021.

--- Dataset description provided by original source is as follows ---

New York City Results on the New York State Mathematics Tests, Grades 3 - 8 Notes: As of 2006, the New York State Education Department expanded the ELA and mathematics testing programs to Grades 3-8. Previously, state tests were administered in Grades 4 and 8 and citywide tests were administered in Grades 3, 5, 6, and 7. In 2006, NYSED treated District 75 students as a distinct geographic district. For 2007-2011, District 75 students are represented in their home districts and boroughs. Spreadsheets for District and Borough do not include District 75 students in 2006. Starting in 2010, NYSED changed the scale score required to meet each of the proficiency levels, increasing the number of questions students needed to answer correctly to meet proficiency.

Rows are suppressed (noted with ‘s’) if the number of tested students was 5 or fewer.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘2006 - 2011 NYS Math Test Results By Grade - District - By Race- Ethnicity’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/0eb87b06-c9f5-4cfd-b896-11995ec89374 on 12 November 2021.

--- Dataset description provided by original source is as follows ---

New York City Results on the New York State Mathematics Tests, Grades 3 - 8 Notes: As of 2006, the New York State Education Department expanded the ELA and mathematics testing programs to Grades 3-8. Previously, state tests were administered in Grades 4 and 8 and citywide tests were administered in Grades 3, 5, 6, and 7. In 2006, NYSED treated District 75 students as a distinct geographic district. For 2007-2011, District 75 students are represented in their home districts and boroughs. Spreadsheets for District and Borough do not include District 75 students in 2006. Starting in 2010, NYSED changed the scale score required to meet each of the proficiency levels, increasing the number of questions students needed to answer correctly to meet proficiency.

Rows are suppressed (noted with ‘s’) if the number of tested students was 5 or fewer.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘2006 - 2011 NYS Math Test Results by Grade - Citywide - by Disability Status’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/357ed4e3-e302-4cdb-ae4e-7967fe3d665e on 12 November 2021.

--- Dataset description provided by original source is as follows ---

New York City Results on the New York State Mathematics Tests, Grades 3 - 8 Notes: As of 2006, the New York State Education Department expanded the ELA and mathematics testing programs to Grades 3-8. Previously, state tests were administered in Grades 4 and 8 and citywide tests were administered in Grades 3, 5, 6, and 7. In 2006, NYSED treated District 75 students as a distinct geographic district. For 2007-2011, District 75 students are represented in their home districts and boroughs. Spreadsheets for District and Borough do not include District 75 students in 2006. Starting in 2010, NYSED changed the scale score required to meet each of the proficiency levels, increasing the number of questions students needed to answer correctly to meet proficiency.

--- Original source retains full ownership of the source dataset ---

Historical Dataset of Easton Area Ms Campus Grades 7-8 Middle School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1987-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1987-2023),Asian Student Percentage Comparison Over Years (1991-2023),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (2003-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2003-2023),Reading and Language Arts Proficiency Comparison Over Years (2010-2015),Math Proficiency Comparison Over Years (2010-2015),Overall School Rank Trends Over Years (2010-2015)

Historical Dataset of United 7 School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Science Proficiency Trends,Graduation Rate Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (1991-2023),Asian Student Percentage Comparison Over Years (1996-2021),Hispanic Student Percentage Comparison Over Years (1997-2023),Black Student Percentage Comparison Over Years (2010-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Comparison of Students By Grade Trends

This data collection contains data from a large battery of mathematics and executive function tasks administered to a sample of 403 participants aged between 5 and 25 years of age. The data collection includes standardised assessments of mathematics, the Numerical Operations and Mathematical Reasoning subtests from the Weschler Individual Achievement Test (WIAT-II UK), in addition to age appropriate experimental mathematics tests of factual knowledge, procedural skill and conceptual understanding in the domain of arithmetic. Executive functions were assessed with experimental tasks measuring verbal and visuospatial short-term and working memory, inhibitory control, cognitive flexibility and selective attention. Questionnaire measures of mathematics anxiety and the Behavior Rating Inventory of Executive Function were also administered. These data underpin the following papers: Gilmore, C., Keeble, S., Richardson, S., & Cragg, L. (2015). The role of cognitive inhibition in different components of arithmetic. ZDM, 1–12. (see Related Resources) Gilmore, C., Keeble, S., Richardson, S., & Cragg, L. (submitted). The interaction of procedural skill, conceptual understanding and executive functions in early mathematics achievement. Cragg, L., Keeble, S., Richardson, S., Roome, H., & Gilmore, C. (in preparation). Direct and indirect influences of executive functions on mathematics achievement. A high proportion of children and adults struggle with learning and doing maths. To help them we need to have a clear understanding of the processes involved in mathematics. There are lots of different skills involved in successful maths performance including maths specific knowledge such as knowledge of facts, procedures, and concepts as well as other more general skills. These include holding and manipulating information in mind (working memory), flexible thinking (shifting), and focusing on relevant information and ignoring distractions (inhibition). These skills are often termed 'executive function' skills and are thought to be particularly important for learning maths. To date, this basic understanding of the importance of executive function skills has not been exploited in the classroom because our understanding is not detailed enough. This project will explore the relationship between maths and executive function skills in greater depth using a variety of different research methods. This research will reveal the ways in which executive function skills are involved in learning and doing maths and help us to understand why some children find maths easy, and other children struggle.These findings will be used to raise teachers’ awareness of the importance of considering executive functions skills when teaching maths. This study used an empirical, experimental data collection method. The sample was recruited from schools and universities in the Nottinghamshire and Leicestershire area. Data were originally collected from seventy-five 5-6-year-olds (Year 1), eighty-four 8-9-year-olds (Year 4), sixty-seven 11-12-year-olds (Year 7), sixty-seven 13-14-year-olds (Year 9) and seventy-five 18-25-year-olds. Thirty-five of the original sample of adults spoke English as a second language (ESL). Initial analyses revealed that this was influencing the results, particularly on the verbal tasks. As a result, data was collected from a further 35 monolingual adults. The Year 1 students attended one of two primary schools. The Year 4 students all attended the same primary school and the Year 7 and 9 students all attended the same secondary school. The 18-25-year-olds were all students at either Loughborough University or the University of Nottingham. Participants were assessed individually at their school or university. Each participant completed a battery of mathematics and executive function tasks lasting approximately 2 hours. For the Year 1 and Year 4 participants this was split across a number of shorter sessions. All of the experimental tasks were programmed using Psychopy software (www.psychopy.org) and presented on HP laptop computers. Further details about the tasks used and measures taken can be found in the task description and read me documents.

Self-reported social mixing patterns are commonly used in mathematical models of infectious diseases. It is particularly important to quantify patterns for school-age children given their disproportionate role in transmission, but it remains unclear how the structure of such social interactions changes over time. By integrating data collection into a public engagement programme, we examined self-reported contact networks in year 7 groups in four UK secondary schools. We collected data from 460 unique participants across four rounds of data collection conducted between January and June 2015, with 7,315 identifiable contacts reported in total. Although individual-level contacts varied over the study period, we were able to obtain out-of-sample accuracies of more than 90% and F-scores of 0.49–0.84 when predicting the presence or absence of social contacts between specific individuals across rounds of data collection. Network properties such as clustering and number of communities were broadly consistent within schools between survey rounds, but varied significantly between schools. Networks were assortative according to gender, and to a lesser extent school class, with the estimated clustering coefficient larger among males in all surveyed co-educational schools. Our results demonstrate that it is feasible to collect longitudinal self-reported social contact data from school children and that key properties of these data are consistent between rounds of data collection.

Teacher guidance can positively impact students’ learning interest and mathematical behavior engagement. As a crucial part of classroom teaching, effective teaching styles play an indispensable role in middle school students’ mathematical behavior engagement. This study addresses the gap in understanding how different teaching styles influence junior high school students’ math behavior engagement in China, by examining the underexplored mediating roles of academic self-efficacy and learning interest in this relationship, which are critical yet often overlooked factors in fostering student engagement and improving educational outcomes in mathematics. Students from grades 7 to 9 in six middle schools in Jiangsu Province, China participated in the survey. The results indicate that: (1) academic self-efficacy mediates the relationship between effective teaching styles (humorous and lively style, rigorous and logical style, caring and sharing style) and mathematical behavior engagement among Chinese middle school students; (2) math learning interest mediates the relationship between effective teaching styles (humorous and lively style, rigorous and logical style, caring and sharing style, innovative and exploratory style) and mathematical behavior engagement among Chinese middle school students. Recommendations include encouraging teachers to adopt diverse teaching styles that foster both self-efficacy and interest.

Abstract

TIMSS is an international assessment of mathematics and science at the fourth and eighth grades that has been conducted every four years since 1995. TIMSS 2015 is the sixth assessment in the TIMSS series monitoring 20 years of trends in educational achievement, together with comprehensive data on students’ contexts for learning mathematics and science. In 2015, 57 countries and 7 benchmarking entities (regional jurisdictions of countries such as states or provinces) participated in TIMSS. In total, more than 580,000 students participated in TIMSS 2015. New for TIMSS 2015, a home questionnaire was completed by fourth grade students’ parents or caregivers, in addition to the questionnaires routinely given at both fourth and eighth grades to students, teachers, school principals, and curriculum specialists. TIMSS 2015 also introduced a new, less difficult mathematics assessment at the fourth grade called TIMSS Numeracy intended to assess fundamental mathematical knowledge, procedures, and problem-solving strategies that are prerequisite for success in the TIMSS mathematics assessment at the fourth grade. The fourth grade sample in South Africa was one of the samples that were administered the TIMSS Numeracy Test instead of the standard test.

Geographic coverage

TIMSS had international coverage overall. The country/grade-specific samples are also nationally representative for students belonging to that grade. Note that the data is not representative at a school, teacher or institution level even though the contextual data contains these information.

Analysis unit

Individuals and institutions

Universe

The international target populations for the TIMSS 2015 are fourth and eighth grade of participant countries, defined as the grades that represented 4 and 8 years of formal schooling, respectively, counting from the first year of primary or elementary schooling.

Kind of data

Sample survey data

Sampling procedure

TIMSS assesses mathematics and science achievement at two grade levels and so TIMSS has two target populations—all students enrolled at the fourth grade and all students enrolled at the eighth grade. TIMSS employs a two-stage random sample design, with a sample of schools drawn as a first stage and one or more intact classes of students selected from each of the sampled schools as a second stage. Intact classes of students are sampled rather than individuals from across the grade level or of a certain age because TIMSS pays particular attention to students’ curricular and instructional experiences, and these typically are organized on a classroom basis. Sampling intact classes also has the operational advantage of less disruption to the school’s day-to-day business than individual student sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The study used the following questionnaires: Fourth Grade Student Questionnaire, Fourth Grade Teacher Questionnaire, Fourth Grade School Questionnaire, Eighth Grade Student Questionnaire, Eighth Grade Mathematics Teacher Questionnaire, Eighth Grade Science Teacher Questionnaire, and Eighth Grade School Questionnaire. Information on the variables obtained or derived from questions in the survey is available in the TIMSS 2011 user guide for the international database: Data Supplement 3: Variables derived from the Student, Teacher, and School Questionnaire data.

In 2025, 5.1 percent of GCSE entries in England were awarded the highest grade of '9', with a further 7.2 percent of entries being awarded an '8', the second-highest grade. A '3' grade was the most common individual grade level achieved by GCSE students, at 16.6 percent of all entries.

This file contains data associated with "Building Word-Problem Solving and Working Memory Capacity: A Randomized Controlled Trial Comparing Three Intervention Approaches", a publication in the Journal of Education Psychology (2022), 2022, Vol. 114, No. 7, 1633–1653. Specifically this includes data on: nesting variables, general participant information, pre, post, delayed post on working memory (WM), word-problem solving (WPS), and arithmetic.

The purpose of this study was to contrast alternative approaches to structure word-problem solving (WPS) intervention, including previously validated structured WPS intervention, the same WPS intervention with embedded working memory (WM) training, and general WM training with contiguous math practice. Second-grade students with WPS difficulty were randomly assigned to four conditions: validated structured WPS intervention (Pirate Math), Pirate Math with embedded WM training, general WM training with contiguous math practice, and a business-as-usual control group. Each of the three active intervention conditions involved 45 30-min sessions conducted one-to-one for 15 weeks. WM, WPS, and arithmetic were assessed before and 1-3 weeks after intervention. WPS and arithmetic were assessed again 4-6 weeks later. Multilevel models testing main effects and testing WM as a mediator of significant main effects were conducted. Baseline WM was assessed in a secondary set of moderation analyses.

This dataset contains a set of typically developing students (i.e., pretest WPS greater than or equal to the 30th percentile standard scores below 80 on both subtests of the Wechsler Abbreviated Intelligence Scale; and WM > 60th percentile). Data for this project was collected in person at schools and via email mail, with each student containing two time points worth of data in the current sample. Data were collected at: Time point 1-September-October; Time point 2-April, Time point 3- May in academic years 2016-2017, 2017-2018, and 2018-2019.
This dataset contains information related to: Cognitive Processes, Executive Function, Math, Number Problems, Shema, Word Problems, Working Memory Arithmetic, Calculation; containing data from the following measures: Story Problems (Jordan & Hanich, 2000), WASI (Wechsler, 2011), Working Memory Test Battery for Children (WMTB-C; Pickering & Gathercole, 2001)–Listening Recall and Counting Recall, Automated Working Memory Assessment (AWMA) Odd-One Out, Arithmetic (Addition 0-12, Addition 5-18, Subtraction 0-12, Subtraction 5-18), Second-Grade Word Problems.

Pupils from the Chinese ethnic group were most likely to meet both the expected and higher standards in reading, writing and maths in 2018/19.