Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 5 |
| Since 2007 (last 20 years) | 12 |
Descriptor
| Comparative Analysis | 13 |
| Mathematics Instruction | 13 |
| Sampling | 13 |
| Algebra | 5 |
| Correlation | 5 |
| Mathematical Concepts | 5 |
| Teaching Methods | 5 |
| Computer Assisted Instruction | 4 |
| Foreign Countries | 4 |
| Learning Processes | 4 |
| Middle School Students | 4 |
| More ▼ | |
Source
Author
| Amisha Jindal | 3 |
| Ashish Gurung | 3 |
| Erin Ottmar | 3 |
| Ji-Eun Lee | 3 |
| Reilly Norum | 3 |
| Sanika Nitin Patki | 3 |
| Shaughnessy, J. Michael | 2 |
| Abidin, Zainal | 1 |
| Briesch, Amy M. | 1 |
| Buteau, Chantal | 1 |
| Canada, Dan | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 10 |
| Journal Articles | 8 |
| Speeches/Meeting Papers | 3 |
| Reports - Descriptive | 2 |
| Reports - Evaluative | 1 |
Education Level
| Secondary Education | 7 |
| Middle Schools | 6 |
| Junior High Schools | 5 |
| Elementary Education | 3 |
| Higher Education | 3 |
| Postsecondary Education | 2 |
| Grade 7 | 1 |
| Grade 8 | 1 |
| High Schools | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Group Embedded Figures Test | 1 |
What Works Clearinghouse Rating
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Maulidia, Farrah; Saminan; Abidin, Zainal – Malikussaleh Journal of Mathematics Learning, 2020
Students' creativity and self-efficacy in solving mathematical problems remain low. Students with Field Dependent (FD) and Field Independent (FI)cognitive styles have different creativity and self-efficacy. One learning model that is believed to increase students' creativity and self-efficacy is Problem Based Learning (PBL) model. This study aimed…
Descriptors: Creativity, Self Efficacy, Problem Based Learning, Islam
Çetinkaya, Seher – Higher Education Studies, 2017
In Turkey due to changes in the age starting school implemented during the 2012-2013 academic year, children ages from 60 months to 84 months were subject to the same educational program in the same class. By the 2015-2016 academic year these children were at the end of 4th class. This research aimed to investigate the Turkish and mathematic…
Descriptors: Foreign Countries, Academic Achievement, Self Esteem, Self Concept
Tran, Dung; Lee, Hollylynne; Doerr, Helen – Mathematics Education Research Group of Australasia, 2016
The research reported here uses a pre/post-test model and stimulated recall interviews to assess teachers' statistical reasoning about comparing distributions, when enrolled in a graduate-level statistics education course. We discuss key aspects of the course design aimed at improving teachers' learning and teaching of statistics, and the…
Descriptors: Faculty Development, Thinking Skills, Graduate Students, Statistics
Briesch, Amy M.; Hemphill, Elizabeth M.; Volpe, Robert J.; Daniels, Brian – School Psychology Quarterly, 2015
Although there is much research to support the effectiveness of classwide interventions aimed at improving student engagement, there is also a great deal of variability in terms of how response to group-level intervention has been measured. The unfortunate consequence of this procedural variability is that it is difficult to determine whether…
Descriptors: Classroom Observation Techniques, Intervention, Comparative Analysis, Observation
Stephenson, W. Robert; Froelich, Amy G.; Duckworth, William M. – Teaching Statistics: An International Journal for Teachers, 2010
This article shows that when applying resampling methods to the problem of comparing two proportions, students can discover that whether you resample with or without replacement can make a big difference.
Descriptors: Statistical Analysis, Mathematical Concepts, Mathematics Instruction, Sampling
Buteau, Chantal; Jarvis, Daniel H.; Lavicza, Zsolt – Canadian Journal of Science, Mathematics and Technology Education, 2014
In this article, we outline the findings of a Canadian survey study (N = 302) that focused on the extent of computer algebra systems (CAS)-based technology use in postsecondary mathematics instruction. Results suggest that a considerable number of Canadian mathematicians use CAS in research and teaching. CAS use in research was found to be the…
Descriptors: Computer Assisted Instruction, Mathematics Instruction, National Surveys, Foreign Countries
Noll, Jennifer; Shaughnessy, J. Michael – Journal for Research in Mathematics Education, 2012
Sampling tasks and sampling distributions provide a fertile realm for investigating students' conceptions of variability. A project-designed teaching episode on samples and sampling distributions was team-taught in 6 research classrooms (2 middle school and 4 high school) by the investigators and regular classroom mathematics teachers. Data…
Descriptors: Sampling, Mathematics Teachers, Middle Schools, High Schools
Pendleton, Kenn L. – Mathematics Teacher, 2009
The use of random numbers is pervasive in today's world. Random numbers have practical applications in such far-flung arenas as computer simulations, cryptography, gambling, the legal system, statistical sampling, and even the war on terrorism. Evaluating the randomness of extremely large samples is a complex, intricate process. However, the…
Descriptors: Numbers, Mathematics Instruction, Mathematical Concepts, Comparative Analysis
Shaughnessy, J. Michael; Canada, Dan; Ciancetta, Matt – International Group for the Psychology of Mathematics Education, 2003
This paper summarizes the thinking of 84 middle school mathematics students' about variability in three stochastics tasks that involve repeated trial. Differences in students' acknowledgment of variability were found, depending on whether the task was from a sampling environment, or a probability environment. Students tended to neglect variability…
Descriptors: Middle Schools, Probability, Sampling, Student Attitudes
Hoshiko, Brandon; Jaciw, Andrew; Ma, Boya; Miller, Gloria I.; Wei, Xin – Empirical Education Inc., 2007
The authors sought evidence of the effectiveness of the TI-Navigator classroom networking system for the second year of a two-year research study of Texas Instruments classroom technology. This randomized control trial compared Algebra I and Geometry instruction using the TI-Navigator system, which includes the TI-84 Silver Edition graphing…
Descriptors: Educational Technology, Technology Uses in Education, Instructional Effectiveness, Graphing Calculators

Peer reviewed
Direct link
