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Piech, Chris; Bumbacher, Engin; Davis, Richard – International Educational Data Mining Society, 2020
One crucial function of a classroom, and a school more generally, is to prepare students for future learning. Students should have the capacity to learn new information and to acquire new skills. This ability to "learn" is a core competency in our rapidly changing world. But how do we measure ability to learn? And how can we measure how…
Descriptors: Academic Ability, Measurement, Middle School Students, Achievement Gains
Huang, Hung-Yu – Educational and Psychological Measurement, 2020
In educational assessments and achievement tests, test developers and administrators commonly assume that test-takers attempt all test items with full effort and leave no blank responses with unplanned missing values. However, aberrant response behavior--such as performance decline, dropping out beyond a certain point, and skipping certain items…
Descriptors: Item Response Theory, Response Style (Tests), Test Items, Statistical Analysis
Linkow, Tamara; Miller, Hannah; Parsad, Amanda; Price, Cristofer; Martinez, Alina – National Center for Education Evaluation and Regional Assistance, 2021
These are the appendices for the report "Study of College Transition Messaging in GEAR UP: Impacts on Enrolling and Staying in College." Five appendices are included in the document: (1) Additional Details about College Transition Messaging; (2) Additional Information about How the Study Was Designed and Implemented; (3) Supplemental…
Descriptors: College Bound Students, College Freshmen, Telecommunications, Synchronous Communication
Casabianca, Jodi M.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2018
The null hypothesis test used in differential item functioning (DIF) detection tests for a subgroup difference in item-level performance--if the null hypothesis of "no DIF" is rejected, the item is flagged for DIF. Conversely, an item is kept in the test form if there is insufficient evidence of DIF. We present frequentist and empirical…
Descriptors: Test Bias, Hypothesis Testing, Bayesian Statistics, Statistical Analysis
Virtanen, T. E.; Lerkkanen, M.-K.; Poikkeus, A.-M.; Kuorelahti, M. – Scandinavian Journal of Educational Research, 2018
Self-ratings of behavioural engagement, cognitive engagement and school burnout were used in person-centred analyses to identify latent profiles among 2,485 Finnish lower-secondary school students. Three profiles were identified: high-engagement/low-burnout (40.6% of the sample), average-engagement/average-burnout (53.9%), and…
Descriptors: Learner Engagement, Burnout, Academic Achievement, Secondary School Students
Killoren, Sarah E.; De Jesús, Sue A. Rodríguez; Updegraff, Kimberly A.; Wheeler, Lorey A. – International Journal of Behavioral Development, 2017
We examined profiles of sibling relationship qualities in 246 Mexican-origin families living in the United States using latent profile analyses. Three profiles were identified: "Positive," "Negative," and "Affect-Intense." Links between profiles and youths' familism values and adjustment were assessed using…
Descriptors: Sibling Relationship, Adolescents, Family Needs, Siblings
Karpudewan, Mageswary; Roth, Wolff Michael; Sinniah, Devananthini – Chemistry Education Research and Practice, 2016
In a world where environmental degradation is taking on alarming levels, understanding, and acting to minimize, the individual environmental impact is an important goal for many science educators. In this study, a green chemistry curriculum--combining chemistry experiments with everyday, environmentally friendly substances with a student-centered…
Descriptors: Conservation (Environment), Organic Chemistry, Science Instruction, Teaching Methods
Stone, Clement A.; Tang, Yun – Practical Assessment, Research & Evaluation, 2013
Propensity score applications are often used to evaluate educational program impact. However, various options are available to estimate both propensity scores and construct comparison groups. This study used a student achievement dataset with commonly available covariates to compare different propensity scoring estimation methods (logistic…
Descriptors: Comparative Analysis, Probability, Sample Size, Program Evaluation
Karpudewan, Mageswary; Roth, Wolff-Michael; Ismail, Zurida – Asia-Pacific Education Researcher, 2015
As an initial effort to reorient the current Malaysian chemistry curriculum, "green chemistry" was developed. In this study for the purpose of investigating the effectiveness of the green chemistry curriculum on secondary school students' understanding of chemistry concepts a quasi-experimental design was used. One-group pretest posttest…
Descriptors: Secondary School Students, Chemistry, Curriculum Development, Curriculum Evaluation
Montague, Marjorie; Krawec, Jennifer; Enders, Craig; Dietz, Samantha – Journal of Educational Psychology, 2014
The effects of a mathematical problem-solving intervention on students' problem-solving performance and math achievement were measured in a randomized control trial with 1,059 7th-grade students. The intervention, "Solve It!," is a research-based cognitive strategy instructional intervention that was shown to improve the problem-solving…
Descriptors: Middle School Students, Secondary School Mathematics, Mathematics Skills, Problem Solving
Golden, Rachel Lynn; Furman, Wyndol; Collibee, Charlene – Developmental Psychology, 2016
The sex-positive framework of sexual development hypothesizes that healthy sexual experiences can be developmentally appropriate and rewarding for adolescents despite the risks involved. Research has not examined whether risky behaviors and rewarding cognitions actually change with sexual debut at a normative or late age. This study measured the…
Descriptors: Risk, Sexuality, Comparative Analysis, Schemata (Cognition)
Wang, Qiu; Diemer, Matthew A.; Maier, Kimberly S. – Educational and Psychological Measurement, 2013
This study integrated Bayesian hierarchical modeling and receiver operating characteristic analysis (BROCA) to evaluate how interest strength (IS) and interest differentiation (ID) predicted low–socioeconomic status (SES) youth's interest-major congruence (IMC). Using large-scale Kuder Career Search online-assessment data, this study fit three…
Descriptors: Bayesian Statistics, Socioeconomic Status, Student Interests, Gender Differences
Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente – Journal of Educational and Behavioral Statistics, 2013
In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…
Descriptors: Regression (Statistics), Foreign Countries, Educational Quality, Educational Research
Proctor, Thomas P.; Kim, YoungKoung Rachel – College Board, 2010
The purpose of this paper is to provide information about how students' scores change when they retake the PSAT/NMSQT as juniors or take the SAT in the spring after they take the PSAT/NMSQT as juniors. Two research questions guided this study and motivated the approach for analysis of the data: How do scores change for students who took the…
Descriptors: Scores, Achievement Gains, Bayesian Statistics, College Entrance Examinations
Pardos, Zachary A.; Heffernan, Neil T. – International Working Group on Educational Data Mining, 2009
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collected in many ITS systems consist of answers to a group of questions of a given skill often presented in a random sequence. Following work that identifies which items…
Descriptors: Data Analysis, Bayesian Statistics, Statistical Analysis, Problem Sets
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