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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
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Scherer, Ronny; Meßinger-Koppelt, Jenny; Tiemann, Rüdiger – International Journal of STEM Education, 2014
Background: Complex problem-solving competence is regarded as a key construct in science education. But due to the necessity of using interactive and intransparent assessment procedures, appropriate measures of the construct are rare. This paper consequently presents the development and validation of a computer-based problem-solving environment,…
Descriptors: Computer Assisted Testing, Problem Solving, Chemistry, Science Tests
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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)
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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
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
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries