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Kim, Young K.; Collins, Christopher S.; Rennick, Liz A.; Edens, David – Journal of International Students, 2017
Using a large dataset from a state education system, this study examined the experience of international college students in the United States as well as the connection to their cognitive, affective, and civic outcomes. The study utilized data from the 2010 University of California Undergraduate Experience Survey (UCUES) and a sample of 35,146…
Descriptors: Educational Experience, Foreign Students, Undergraduate Students, Research Universities
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Bainter, Sierra A.; Curran, Patrick J. – Journal of Cognition and Development, 2015
Amid recent progress in cognitive development research, high-quality data resources are accumulating, and data sharing and secondary data analysis are becoming increasingly valuable tools. Integrative data analysis (IDA) is an exciting analytical framework that can enhance secondary data analysis in powerful ways. IDA pools item-level data across…
Descriptors: Data Analysis, Integrated Activities, Inferences, Statistical Analysis
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Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
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Rhemtulla, Mijke; Little, Todd D. – Journal of Cognition and Development, 2012
Data collection can be the most time- and cost-intensive part of developmental research. This article describes some long-proposed but little-used research designs that have the potential to maximize data quality (reliability and validity) while minimizing research cost. In "planned missing data designs", missing data are used…
Descriptors: Data Collection, Reliability, Validity, Measures (Individuals)
Ives, Eugenia A. – Online Submission, 2012
The purpose of this study was to examine and better understand the social cognitive effects of digital technology on teenagers' brains and their socialization processes, as well as to learn best practices with regard to digital technology consumption. An extensive literature review was conducted on the social cognitive effects of digital…
Descriptors: Influence of Technology, Computer Uses in Education, Web 2.0 Technologies, Computer Literacy
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Burchinal, Margaret R. – Early Education and Development, 1999
Describes a variety of analytic tools available to address questions about development, including growth-curve methods, hierarchical regressions, and both primary and secondary data analysis of project and extant data. Demonstrates some of these techniques using extant data from two projects to examine questions about treatment efficacy and…
Descriptors: Black Youth, Child Development, Cognitive Development, Data Analysis
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Russo, Tracy C.; Koesten, Joy – Communication Education, 2005
This study explored relations between social network characteristics in an online graduate class and two learning outcomes: affective and cognitive learning. The social network analysis data were compiled by entering the number of one-to-one postings sent by each student to each other student in a course web site discussion space into a specially…
Descriptors: Online Courses, Graduate Study, Social Networks, Network Analysis
Horst, Donald P.; And Others – 1975
Measuring cognitive achievement gains in project evaluation is dealt with. This guide provides those concerned with project evaluation with the basic tools for conducting technically sound, interpretable evaluation studies. Exotic designs are avoided and five basic models which appear feasible to implement in real-world settings are focused on.…
Descriptors: Academic Achievement, Achievement Gains, Cognitive Development, Data Analysis