The research is a descriptive correlational study that investigates new methods for the creation of innovation for institutions. The research addresses the need for organizations to generate a novel form of innovation for their competitiveness and survival. These novel methods in the generation of innovation include using an organization's big…

Collecting data for the purpose of decision making has become an integral part of the landscape of education in the United States over the past decade. Many educators are swamped with such an overwhelming amount of information that it can be difficult to sort and analyze, leaving them floundering under wave after wave of data. The SWIS facilitator…

The problem in this study was that first- and second-grade teachers are not using relevant and timely data, specifically running records, analysis of oral reading errors, self-correction rates, and word accuracy, as well as the student zone of proximal development (ZPD) in guided reading instruction. The purpose of this qualitative case study was…

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 quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

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…

One of the most significant issues in education, as defined by the U.S. Department of Education Office of Accountability (2018), is disproportionality in exclusionary discipline. Disproportionality is defined as the over- and under-representation of racial/ethnic minorities in relation to their overall enrollment (Ahram et al., 2011). Currently,…

Principals at Hunter School District, a pseudonym, lacked capacity for using data, a reflection of the district's lack of a culture of data-driven decision-making. HSD was located in New York City, with 23 schools serving 11,600 students; students were 90% Black or Latino with 90% coming from low-income families and 20% living in temporary…

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…

This study aimed to address the state of data driven decision practices within the Division of Student Affairs at South County College. Framed by an exploratory qualitative case study, this project conducted semi-structured interviews of directors of student affairs and a document analysis of annual reports of the seven departments that constitute…

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…

In an increasingly data-driven society, making decisions with data is a requirement not only for research scientists but also for navigating life more generally (Kjelvik & Schultheis, 2019). An informed citizenry must be prepared to discover patterns, predict outcomes, make decisions with data, and evaluate data-based claims for legitimacy and…

The Conservative Dual Criteria (CDC) method is known to improve decision-making accuracy in users when interpreting graphed data. The effectiveness of this method with in-service special education teachers, however, has not been investigated. The present study examined the effects of a virtual training package designed to improve the data-based…

The American School Counselor Association (ASCA) calls on school counselors to take part in collaborative work experiences using data to address problems of practice. School counselors experience professional isolation leading to underperformance (Elliot et al., 2004; Stone-Johnson, 2015). School structures that lack collaborative experiences for…