Data-Based Decision Making in Early Childhood: Teachers’ Competencies, Beliefs, and Practices

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Data-Based Decision Making in Early Childhood: Teachers’ Competencies, Beliefs, and Practices

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2022-06

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The early literacy and language skills children develop in the preschool years provide a foundation for their reading skill development in later grades. The long-term importance of early literacy and language skills highlights the need to prioritize identifying children struggling with these skills early in their preschool years and providing them with supports. Early identification and intervention can occur with educators collecting universal screening assessment data, using the data to inform decisions about which children need additional help with skill development, and modifying and monitoring instructional supports accordingly. These assessment, data use, and instructional practices are components of data-based decision making (DBDM) in early childhood education within a multi-tiered systems of support (MTSS) framework. Within the MTSS framework, DBDM can guide teachers in identifying student needs and systematically and equitably allocating instructional resources to promote optimal outcomes for all their students. Research is needed to understand early childhood teachers’ competencies, beliefs, and practices related to DBDM for early literacy and language skills. The current study used survey responses from 188 early childhood teachers to compare two approaches for describing their DBDM competencies, beliefs, and practices. The first approach explored teachers’ competency and belief profiles and determined if differences existed in teachers’ frequency of engagement in DBDM practices based on their profile. Latent profile analysis supported a three-profile solution with primary differences in data use competencies, early literacy and language competencies, and self-efficacy beliefs. One-way ANOVAs indicated teachers in these profiles differed in their frequency of engagement in assessment, data use, and instructional practices. The second approach explored the feasibility of profiles that included competencies, beliefs, and practices. Latent profile analysis supported a three-profile solution with primary differences in early literacy and language competencies, assessment practices, data use practices, and instructional practices. Results from this study highlight the existence of individual differences in early childhood teachers’ DBDM competencies, beliefs, and practices and indicate specific areas where groups of teachers may need additional support. These results can inform the creation of tailored professional development opportunities matched to teachers’ needs to help them engage in DBDM in support of all their students.

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University of Minnesota Ph.D. dissertation. 2022. Major: Educational Psychology. Advisor: Panayiota Kendeou. 1 computer file (PDF); 209 pages.

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Will, Kelsey. (2022). Data-Based Decision Making in Early Childhood: Teachers’ Competencies, Beliefs, and Practices. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/241629.

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