Measuring undergraduate students' conceptions of artificial intelligence in education using a convergent mixed-method approach

• In Event: RTD- Measuring undergraduate students' conceptions of artificial intelligence in education using a convergent mixed-method approach

Short Description

This study employed a convergent mixed-method approach to measure undergraduate students’ conceptions of artificial intelligence (AI) in education using a traditional survey instrument and the emerging draw-a-picture technique. Thus, the purpose of this study is to design, develop, and validate an instrument for undergraduates and provide more nuanced convergent validity evidence with the draw-picture technique. In this proposal, we provide preliminary results and drawings to illustrate the potential of the research findings.

Authors

• Contributor: Li Cheng, University of Florida

• Contributor: Kristine Antonyan, University of Florida

• Presenter: Muhammad Shahroze Rehman, University of Florida

• Contributor: Poorya Shidfar, University of Florida

• Presenter: Minyoung Lee, University of Florida

• Contributor: James Nichols, Santa Fe College

• Presenter: Brian Abramowitz, University of Florida

• Contributor: Karthikeyan Umapathy, University of North Florida

• Presenter: Albert Dieter Ritzhaupt, University of Florida

• Presenter: Pavlo Antonenko, University of Florida