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Jiawei Xiong; George Engelhard; Allan S. Cohen – Measurement: Interdisciplinary Research and Perspectives, 2025
It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…
Descriptors: Responses, Test Items, Test Format, Grade 8
Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Kuddar, Cagla; Cetin, Sevda – International Journal of Assessment Tools in Education, 2022
The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…
Descriptors: Mathematics Achievement, Structural Equation Models, Regression (Statistics), Achievement Tests
Sahba Akhavan Niaki – ProQuest LLC, 2018
The increasing amount of available subjective text data in internet such as product reviews, movie critiques and social media comments provides golden opportunities for information retrieval researchers to extract useful information out of such datasets. Topic modeling and sentiment analysis are two widely researched fields that separately try to…
Descriptors: Models, Classification, Content Analysis, Documentation
Fu, Jianbin – ETS Research Report Series, 2016
The multidimensional item response theory (MIRT) models with covariates proposed by Haberman and implemented in the "mirt" program provide a flexible way to analyze data based on item response theory. In this report, we discuss applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the…
Descriptors: Item Response Theory, Longitudinal Studies, Test Bias, Goodness of Fit
Stains, Marilyne; Sevian, Hannah – Research in Science Education, 2015
Students' mental models of diffusion in a gas phase solution were studied through the use of the Structure and Motion of Matter (SAMM) survey. This survey permits identification of categories of ways students think about the structure of the gaseous solute and solvent, the origin of motion of gas particles, and trajectories of solute particles in…
Descriptors: Cognitive Structures, Models, Undergraduate Students, Knowledge Level
Roscoe, Matt B. – Mathematics Teaching in the Middle School, 2016
Instead of reserving the study of probability and statistics for special fourth-year high school courses, the Common Core State Standards for Mathematics (CCSSM) takes a "statistics for all" approach. The standards recommend that students in grades 6-8 learn to summarize and describe data distributions, understand probability, draw…
Descriptors: Data Analysis, Probability, Statistics, Mathematics
Ellis, Amy B.; Ozgur, Zekiye; Kulow, Torrey; Dogan, Muhammed F.; Amidon, Joel – Mathematical Thinking and Learning: An International Journal, 2016
This article presents an Exponential Growth Learning Trajectory (EGLT), a trajectory identifying and characterizing middle grade students' initial and developing understanding of exponential growth as a result of an instructional emphasis on covariation. The EGLT explicates students' thinking and learning over time in relation to a set of tasks…
Descriptors: Numbers, Mathematics, Mathematics Instruction, Middle School Students
Brooks-Russell, Ashley; Foshee, Vangie A.; Ennett, Susan T. – Journal of Youth and Adolescence, 2013
This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9 % female). Growth mixture models were…
Descriptors: Risk, Drinking, Gender Differences, Victims
Bowen, Gary L.; Hopson, Laura M.; Rose, Roderick A.; Glennie, Elizabeth J. – Family Relations, 2012
Self-report data from 2,088 sixth-grade students in 11 middle schools in North Carolina were combined with administrative data on their eighth-grade end-of-the-year achievement scores in math and reading to examine the influence of students' perceived parental school behavior expectations on their academic performance. Through use of multilevel…
Descriptors: Evidence, Middle Schools, Student Attitudes, Academic Achievement
Kozina, Ana – Educational Studies, 2015
In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…
Descriptors: Aggression, Elementary Schools, Predictive Validity, Educational Environment
Regasa, Guta; Taha, Mukerem – Journal of Education and Practice, 2015
The objectives of the study were to assess the current status of the academic performance of females in grade seven and eight and to study how perception of parents affect the academic performance of female students in Kutto Sorfella Primary School, Sodo Zuria Woreda, SNNPR, Ethiopia. To achieve the objectives of this research both qualitative and…
Descriptors: Foreign Countries, Parent Attitudes, Females, Womens Education
Sao Pedro, Michael A.; Baker, Ryan S. J. d.; Gobert, Janice D. – Grantee Submission, 2013
When validating assessment models built with data mining, generalization is typically tested at the student-level, where models are tested on new students. This approach, though, may fail to find cases where model performance suffers if other aspects of those cases relevant to prediction are not well represented. We explore this here by testing if…
Descriptors: Educational Research, Data Collection, Data Analysis, Generalizability Theory
Rubenstein, Rheta N.; Thompson, Denisse R. – Mathematics Teaching in the Middle School, 2012
Mathematics is rich in visual representations. Such visual representations are the means by which mathematical patterns "are recorded and analyzed." With respect to "vocabulary" and "symbols," numerous educators have focused on issues inherent in the language of mathematics that influence students' success with mathematics communication.…
Descriptors: Student Attitudes, Symbols (Mathematics), Mathematics Instruction, Visual Stimuli
Erdogan, Niyazi; Navruz, Bilgin; Younes, Rayya; Capraro, Robert M. – EURASIA Journal of Mathematics, Science & Technology Education, 2016
Recent studies on professional development programs indicate these programs, when sustained, have a positive impact on student achievement; however, many of these studies have failed to use longitudinal data. The purpose of this study is to understand how one particular instructional practice (STEM PBL) used consistently influences student…
Descriptors: STEM Education, Active Learning, Student Projects, Science Achievement