Self-perceived Dispositions that Predict Challenges during Student Teaching: A Data Mining Analysis
AbstractIn a sample of 277 teacher candidates who completed a 15-item teacher disposition survey, 12 teacher candidates faced considerable challenges during their student teaching practicum. The objective of this study was to predict such challenging experiences from the participantsâ€™ self-perceived dispositions to teach. The group that faced challenges had a 15-item total disposition score that was significantly lower than their counterpart that did not face challenges. Utilizing CART data mining analyses, the challenges were best predicted by lower scores on Item 6 â€œCollaborating with my Master teacher and University Supervisor will help me become a better teacher.â€ The results from this study hold important implications for the teacher education community in relation to curriculum development and the student teaching practicum.