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…

Data-based decision-making has been a frequently used policy and practice intervention used in schools to help inform the decision-making processes of educational practitioners, with the aim of improving student outcomes. Interim benchmark assessments are designed by commercial test developers to support educators in this framework. In fact, the…

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-driven decision making (DDDM) is an important teaching practice that can positively influence student achievement by using assessment data to make instructional decisions. The problem is that teachers do not always use this practice. Teachers' perspectives of DDDM can influence their data use practices. This basic qualitative study was…

The purpose of this small case-study is to gain an in depth understanding of how secondary school teachers perceive that data walls impact their teaching practices and subsequently, students' learning and growth. By drawing on a conceptual model of evidence-informed practice (EIP), this case study examined responses from secondary school teachers…

Data-informed decision-making in teachers' practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known about how teachers perceive the different steps that analytics-informed teacher inquiry entails. This paper presents the results of a study into…

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…

This paper considers elementary teachers' perceptions of data-driven decision making (DDDM) through the lens of Dewey's science of education. Dewey argues that educational science can be used to improve teaching and learning, but it must be flexible, attendant to multiple dimensions of growth, and grounded in real classroom experiences with…

Curriculum-based measurement in reading (CBM-R) is a commonly used tool for universal screening and progress monitoring in K-12 education and is one that can add value to decision-making. However, the social validity of this measure among teachers is often questioned. Reasons some teachers have traditionally opposed the use of CBM-R have included…

The purpose of this mixed-methods study is to examine the outcomes of assessment training for elementary teachers. Only 56% of the surveyed teachers (n = 283) had assessment training in their university courses, compared to 84% that received in-service training. The quantitative results indicate that frequency of assessment training is positively…

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…

This work focuses on simulation, design, development, and evaluation of a visual Learning Analytics (LA) tool -- Real-time Educational AI-powered Classroom Tool (REACT) -- to support educators' data-driven decision-making. The educational institutions face one of the biggest challenges, such as predicting student performance, detecting undesirable…

Decision-making is key for teaching, with informed decisions promoting students and teachers most effectively. In this study, we explored data-driven decision-making processes of K-12 teachers (N = 302) at times of emergency remote teaching, as experienced during the COVID-19 pandemic outbreak in Israel. Using both quantitative and qualitative…