An Exploration Of Educator Experiences Making Data-Driven Decisions Within A Multi-Tiered System Of Support
2024
- 889Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage889
- Downloads469
- Abstract Views420
Thesis / Dissertation Description
School districts across the country often face challenges using data to implement a multi-tiered system of support (MTSS) to meet the needs of all learners through high quality educational opportunities. This qualitative investigation explored how educators in a public school district in the northeastern United States experience the collection and analysis of data to inform decision-making within a MTSS. Guided by the theory of planned behavior and employing a phenomenological analysis, this study addressed the inconsistencies in educator training along with a lack of existing literature focused on the foundational elements of data literacy. The research questions focused on understanding data, the scope of data collected and analyzed, and the use of a MTSS. Analysis of semi-structured interviews with seven public school educators yielded four findings: (1) the existence of data in a variety of formats, (2) the lack of consistent expectations around data collection and analysis, (3) collaboration among staff to support student growth, and (4) the lack of awareness and understanding of a MTSS. The study's findings suggest that changes need to be made in the way educators are trained in collecting and analyzing data and how underperforming students are supported in educational learning environments.
Bibliographic Details
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