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Validating the Computer Attitude Questionnaire NSF ITEST (CAQ N/I)
PROCEEDINGS
Leila Mills, University of North Texas, United States ; Jenny Wakefield, Anjum Najmi, Dean Surface, UNT, United States ; Rhonda Christensen, Gerald Knezek, University of North Texas, United States
AACE Award
Society for Information Technology & Teacher Education International Conference, in Nashville, Tennessee, USA ISBN 978-1-880094-84-6 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Abstract
Abstract: This paper is a report on the validation of a new version of the Computer Attitude Questionnaire (CAQ) which is an instrument for measurement of student attitudes toward computers (comfort and learning with), empathy, creativity, and school. This new version, called CAQ N/I, was developed in response to a request for a more brief instrument to be used for a National Science Foundations’ Innovative Technology Experience for Students and Teachers (NSF ITEST) program research project. The CAQ N/I was found to have strong internal consistency reliability, content validity, and criterion-related validity. Cronbach’s Alpha for the instrument scales ranged from .71 to .87 with two samples of data spanning grades 6 to 12. The CAQ N/I was judged to be “acceptable” to “very good” for measurement of student attitudes toward learning with computers in middle and high school years. Appendix A presents the CAQ N/I.
Citation
Mills, L., Wakefield, J., Najmi, A., Surface, D., Christensen, R. & Knezek, G. (2011). Validating the Computer Attitude Questionnaire NSF ITEST (CAQ N/I). In M. Koehler & P. Mishra (Eds.), Proceedings of SITE 2011--Society for Information Technology & Teacher Education International Conference (pp. 1572-1579). Nashville, Tennessee, USA: Association for the Advancement of Computing in Education (AACE). Retrieved August 9, 2024 from https://www.learntechlib.org/primary/p/36522/.
Keywords
References
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Gender Differences in Conceptualizations of STEM Career Interest: Complementary Perspectives from Data Mining, Multivariate Data Analysis and Multidimensional Scaling
Gerald Knezek, University of North Texas
Journal of STEM Education Vol. 16, No. 4 (Dec 23, 2015)
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Slides
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