Purpose: Prior research has shown that students who are considered to be gifted generally have high levels of academic performance, motivation, creativity, critical thinking skills, and positive self-concepts. Perhaps because the general perception is that gifted students will flourish under any conditions, support for gifted children may be limited within some schools. The purpose of this project is to develop an early intervention software program to assess and provide support to gifted children in social and intellectual domains. Project Activities: In Phase I, the team developed a prototype assessment consisting of 96 items and demonstrated its technological feasibility with 400 general education students who had been pre-identified as gifted. In Phase II, the team will integrate student performance data in cognitive and academic domains to customize recommendations and provide targeted resources to teachers. To assess the implementation feasibility and technological usability of the technology, and to gather data on the promise of the product to identify gifted students and support learning, a series of pilot studies will be conducted with approximately 6,000 students from a current pool of 200,000 users of the company's existing core product. Half of the students will be randomly assigned to receive the intervention as a supplement to the curriculum whereas half will be in the business-as-usual group. Analyses will compare student performance on standardized assessments in literacy and mathematics. Product: The Computer Adaptive Triarchic Assessment and Instructional Activities for Early Childhood will be integrated within Children's Progress' core product, the Children's Progress Academic Assessment. The new software will identify gifted children in pre-kindergarten to 2nd grade through computer adaptive methods that measure children's ability profiles in analytic, practical, and creative domains. The software will enhance the connection between assessment and instruction by generating online reports with individualized recommendations based on these profiles.
