4.8.4 Cross cultural instrumentation for gifted education research and programming: Purdue’s repository
In this session, we showcase a recent website available through our center that contains a collection of instruments that researchers can download and use in their own research and that practitioners can use in their identification, programming, and evaluation efforts. A brief overview of these instruments, their psychometric properties, and the populations and cultures with which they have been studied will be presented together with complete references of development of and research with these instruments and a demonstration of the website where they are available. We will share TOF, MCA, SPOCQ, HOPE Scale (not downloadable), CPS—Revised, among others.
Author(s):
Marcia Gentry
mgentry@purdue.edu
Purdue University
United States
professor of Educational Studies, directs the Gifted Education Research Institute at Purdue University. She actively participates in NAGC and AERA, frequently contributes to the literature, has national and international partnerships, and regularly serves as a speaker and consultant. Marcia received multiple grants in support of her work with low-SES, Native American, and underrepresented gifted youth. Her research interests include student attitudes toward school; using cluster-grouping and differentiation to meet the needs of gifted youth while helping all students achieve at high levels; non-traditional settings for talent development; and the development and recognition of talent among underserved populations.
Nielsen Pereira
npereira@purdue.edu
College of Education, Department of Educational Studies
United States
Assistant Professor of Gifted, Creative, and Talented Education at Purdue University. His research interests include design and assessment of learning in varied gifted and talented education contexts; understanding gifted and talented student experiences in talent development programs in and out of school; identification and talent development of English Language Learners; and conceptual, contextual, and measurement issues in the identification of gifted and talented populations.
Rachael Kenney
rhkenney@purdue.edu
Purdue University
United States
is an Associate Professor of Mathematics Education at Purdue University with a joint appointment in the Department of Mathematics and Department of Curriculum and Instruction. Her research focuses on learners’ interactions with the language of mathematics and teachers’ uses of informal assessment for differentiation and learning. Her publications attend to learners from a variety of contexts, including ELLs, students who struggle in mathematics, and pre-service teachers. Dr. Kenney has worked on two grants supported by the Jacob K. Javits Gifted and Talented Students Education Program and led professional development workshops in gifted education.
C. Matthew Fugate
fugatec@uhd.edu
University of Houston, Downtown
United States
Assistant Professor, University of Houston, Downtown (Ph.D. Purdue University, 2014; Master’s UConn) Matthew worked as an elementary teacher, gifted and magnet coordinator for Houston Independent School District. Matthew’s research focuses on twice exceptionality. He examined the relationship between working memory and creativity among gifted ADHD students; coping mechanisms of twice-exceptional girls in secondary school concerning academics and interpersonal relationships; and he is a team member working to increase research, identification, and service of gifted Native Americans. He has presented to parents and teachers across the United States on topics including creativity, 2E, underserved populations, and Total School Cluster Grouping.
Yukiko Maeda
ymaeda@purdue.edu
Purdue University
United States
Associate Professor of Research Design and Methodology. Her research promotes understanding, establishing and disseminating best practices in the use of data in educational research. She is expertise in meta-analysis and multilevel modeling. Her recent research contributions include understanding data use at school settings for decision making and identifying and presenting remedies for methodological issues for data analysis.