THE PREDICTIVE POWER OF PRESERVICE TEACHERS' READINESS LEVELS FOR ARTIFICIAL INTELLIGENCE SUPPORTED INSTRUCTIONAL DESIGN ON LESSON PLANNING COMPETENCIES
Abstract
The purpose of this study is to examine the predictive power of pre-service teachers' readiness levels for artificial intelligence-supported instructional design on their lesson planning competencies. The sample of the study, in which the relational survey model, one of the quantitative research designs, consisted of 412 pre-service teachers from different departments studying at the Faculty of Education of a state university in Turkey. "Artificial Intelligence Assisted Instructional Design Readiness Scale" and "Lesson Planning Competency Scale" were used as data collection tools. Descriptive statistics, independent sample t-test, one-way ANOVA, Pearson correlation and multiple regression analyses were used to analyze the data. The findings revealed that pre-service teachers had high levels of both AI-supported instructional design readiness and lesson planning competencies. In addition, it was determined that their level of AI-supported instructional design readiness predicted their lesson planning competencies significantly and strongly. These results point to the need to support pre-service teachers' digital pedagogical competencies and the importance of increasing artificial intelligence-based instructional design-oriented practices in teacher training programs.
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DOI: http://dx.doi.org/10.46827/ejes.v12i11.6402
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