From the Editor-In-Chief

in

Examining Effectiveness of Rapid Automatized Naming and Reading Skills in Identifying Gifted Students

Have access already?

Get access to this article:

Or get access to the particular issue:

Advertisement

Abstract

The aim of this study was to determine the effectiveness of Rapid Automatized Naming (RAN) and reading skills in distinguishing gifted students from their non-gifted peers. A total of 260 third grade students participated in the study. Of these students, 144 were gifted, while the others were not. As the data collection tools, personal information form, reading text, and the RAN test were used. The RAN test scores (time for naming shapes, colors, numbers, and letters), reading speed, and rate of accuracy in reading were the main variables of the research. In the research, correlational research was used as the method, logistic regression and MANOVA were used for the data analysis. The results of the study showed that all predictive variables (reading rate, reading accuracy, time for naming shapes and time for naming numbers) are significant predictors of giftedness, except for variables related to time for naming letters and colors, and that there was a statistically significant difference between gifted and non-gifted students in terms of the RAN scores regarding all sub-tests and reading variables. According to the research findings, it can be suggested that evidence on time for naming numbers and shapes, reading rate, and accuracy skills can be used as additional supporting components in distinguising gifted students from their non-gifted peers.

Article usage
Article Usage
Period Abstract Full PDF Total
Apr 2024 228 0 0 228
Mar 2024 211 0 0 211
Feb 2024 190 0 0 190
Jan 2024 216 0 0 216
Dec 2023 188 0 0 188
Nov 2023 258 0 0 258
Oct 2023 264 1 1 266
Sep 2023 156 0 0 156
Aug 2023 156 0 0 156
Jul 2023 199 0 0 199
Jun 2023 595 0 0 595
May 2023 307 0 0 307
Apr 2023 148 0 0 148
Mar 2023 38 0 0 38
Feb 2023 45 0 0 45
Jan 2023 80 0 1 81
Dec 2022 39 0 0 39
Nov 2022 2758 0 0 2758
Oct 2022 12973 0 0 12973
Sep 2022 4447 0 0 4447
Aug 2022 277 0 4 281
Jul 2022 307 1 1 309
Jun 2022 187 0 0 187