Restricted Research - Award List, Note/Discussion Page

Fiscal Year: 2021

213  University of North Texas  (84509)

Principal Investigator: Acar,Selcuk

Total Amount of Contract, Award, or Gift (Annual before 2011): $ 964,081

Exceeds $250,000 (Is it flagged?): Yes

Start and End Dates: - 6/30/23

Restricted Research: YES

Academic Discipline: Educational Psychology

Department, Center, School, or Institute: College of Education

Title of Contract, Award, or Gift: Measuring Original Thinking in Elementary Students: A Text-Mining Approach

Name of Granting or Contracting Agency/Entity: U.S. Department of Education

Program Title: N/A
CFDA Linked: Education Research, Development and Dissemination


1.1.1 (SAM); IRB Protocol #20-337; Topic and Project Type: Cognition and Student Learning; Measurement. Purpose: Measuring original thinking in children has a long history. However, manual scoring of the test limits its accessibility—because many schools may not afford the costs and logistics of such tests—and introduces measurement error into the scores. Therefore, fewer children are measured for original thinking, which leads directly to the under-representation of minorities and low-SES learners in gifted and talented programs. There is a need for screening tools that allow measuring original thinking in a large number of students quickly and at lower cost. This research aims to provide a more enhanced measurement of original thinking called Measurement of Original Thinking in Elementary Students (MOTES) which adopts the text-mining models, which were only tested with adults so far, to elementary students. To this end, we propose to develop a massive corpus of text (target: 1 million unique words) that is built to approximate the semantic language-space of a child within the range of grades 3 to 5, which is the time when creativity assessment in applied research and schools is most utilized. These corpora will then be used to score the four different divergent thinking (DT) tasks. After administering these tasks to a large and diverse sample of elementary school students, they will be scored using text-mining methods and examined in terms of fairness of the individual items and reliability and validity of the scales. This new scoring platform will be available to researchers and practitioners who can obtain instant scores, for free or for very low cost.

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