Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…

This mixed-methods study combined the use of qualitative, comparative case study methods with other data analysis procedures to investigate an afterschool enriched reading program for academically gifted students who had also been identified as talented readers. The Schoolwide Enrichment Model-Reading Framework (SEM-R) was used to provide…

In order to collect a thesaurus of gifted descriptors and to develop variables and item clusters appropriate for use in impact research, 847 people (404 elementary and 242 secondary school students identified as gifted, 91 elementary and 62 secondary teachers of the gifted, and 73 parents of gifted children) were interviewed. The three major…

This report discusses the outcomes of a study that investigated the relationship between student scores on the five sub-scales of the School Attitude Assessment Survey-Revised (SAAS-R) and the academic achievement of known groups of gifted achievers and gifted underachievers. The study examined whether gifted achievers and gifted underachievers…

DIFFERENCES IN ATTITUDES BETWEEN ADVANTAGED AND DISADVANTAGED STUDENTS, AND DIFFERENCES IN ATTITUDES BETWEEN INCONSISTENT STUDENTS AND THEIR ASSOCIATED MAJORITY GROUPS WERE EXPLORED. FOR THE PURPOSE OF THIS STUDY, THE INCONSISTENT STUDENT WAS DEFINED AS EITHER A STUDENT FROM AN ADVANTAGED BACKGROUND WHO WAS UNSUCCESSFUL IN SCHOOL, OR A STUDENT…