The purpose of this study was to explore how teachers engaged in data use for instructional decision making. A grounded theory research design was used to analyze interviews of 10 special education teachers. Special education teachers were asked to complete an online survey and were interviewed with questions to reveal their experiences with…

This dissertation discusses the relationship between teacher sensemaking, attributions, and instructional adjustments prompted in response to student performance data. Through this qualitative observation study, this paper explores the varying perspectives of teachers, including their level of assessment literacy, and the dynamics of their…

This study aimed to discover the perspectives and experiences of elementary school teachers in rural southeast Tennessee regarding their collaborative efforts to effectively implement data-driven instruction for individual student success. The research problem is that the current collaboration efforts for teachers to implement data-driven…

Students with extensive support needs (ESN), most of whom are taught in separate settings by special educators without extensive academic preparation, have difficulty making progress in the general education curriculum. Although there is evidence that data-based decision-making improves achievement for a wide range of students, there is little…

Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation…

Decision-making is a critical topic in any management and organizational behavior course. Navigating and understanding the various processes and influences on decision-making, however, can be complicated. This article revises and expands on a common "employee ranking" format activity. It uses in-class student data to systematically…

Higher education instructors constantly rely on educational data to assess and evaluate the behavior of their students and to make informed decisions such as which content to focus on and how to best engage the students with it. Massive open online course (MOOC) platforms may assist in the data-driven instructional process, as they enable access…

Powered by educational policy recommendations around the world, studies on different aspects of data-driven decision making have soared both in number and scope in different educational contexts. However, despite the availability of diverse data, second or foreign language research has been quite tardy in the study of language teachers'…

This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…

The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…

This paper reports results from an Australian study into how teachers see features of quality in student work and connect these to next-step teaching. Data were drawn from a national 3 year project investigating teacher judgement using A-E standards. The project developed scaled exemplars of authentic student written performance assessments to…

Data-driven decision-making (DDDM) requires educational leaders and teachers to monitor and evaluate programs and processes and link results to individual and organizational outcomes. A classroom teacher's ability to collect and review data, analyze data to identify trends and strategies for student achievement, and use data to determine and…

Improving outcomes for young children with high-intensity needs requires a high-quality workforce trained in equitable, intensive, individualized instructional practices and supports incorporating culturally and linguistically responsive evidence-based practices (Gunn, 2020) and developmentally appropriate practices (DAP; NAEYC, 2021) Nationally…

The purpose of this process evaluation was to evaluate how classroom teachers, campus administrators, and instructional staff differ in their perception of data usage for educational improvement in a large suburban Independent School District (ISD) in Southeast Texas. The researcher was granted permission by the superintendent of the school…

There is evidence that data-based decision-making (DBDM) can improve outcomes for a wide range of students. However, less is known about how special education teachers are trained to use data to inform instruction that targets academic progress for students with extensive support needs (ESN). The purpose of this systematic literature review was to…