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,…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

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…

Many students in the Unites States enter college without having decided on a focus for their studies, and thus are faced with choosing from a large number of potential majors and associated very complex sets of degree requirements which can include many courses in other areas of study. Academic advisors use academic planning tools to help students…

As a digital learning medium, serious games can be powerful, immersive educational vehicles and provide large data streams for understanding player behavior. Educational data mining and learning analytics can effectively leverage big data in this context to heighten insight into student trajectories and behavior profiles. In application of these…

The digital evaluation field is a new area that arises in the core of education and studies highlight the importance of editing data as well as using ICT to drive internal school improvement. Data- Driven Decision Making (DDDM in advance) executes relatively simple models on carefully targeted data extracted through target questionnaires. This…

Most recent research on teacher evaluation examines evaluation's measurement properties and accountability uses. Less research studies how evaluation data can improve teaching and student learning. In other contexts, researchers have examined how teachers use data to improve their practice. From general research on teachers' data use, we apply the…

A "Cone of Uncertainty" has become ubiquitous in hurricane forecasting, encompassing the likeliest possible path that a storm might take as it approaches landfall. These forecasts are crucial because they help government agencies at all levels prepare even in these far-from-certain future conditions. Although individual institutions have…

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…

Engaging in culturally responsive practices is considered best practice in classroom instruction, particularly within diverse schools, however, when making data-based decisions, there is little guidance for culturally responsive practitioners on how to engage in this work. This article introduces a model of culturally responsive data-based…

The current study describes the process of a participatory consultation framework, the Participatory Culture Specific Intervention Model (PCSIM), to plan and implement a data-based decision-making framework. The framework integrates proactive and systematic identification of emotional and behavioral needs as well as cognitive psychology techniques…

Since the introduction of the specific learning disability (SLD) classification in federal special education legislation, there has been considerable ambiguity and controversy about the criteria that should be used in the determination of SLD (Kavale & Flanagan, 2007; Zumeta et al., 2014). Various models have been introduced to identify…

This article studies the relationship between teachers' perceptions of distributive leadership and inquiry-based work in primary schools and the resulting impact on those teachers' capacity to contribute to educational change. The path analysis that tests the proposed model relies on questionnaire data collected from 787 teachers in 65 primary…

The schools in the United States undergo reforms that involve the integration of data-intensive improvement process known as strategic improvement plans (SIPs). This process requires digital systems to set goals, create interventions, use and analyse student data, monitor and report SIPs. A challenge with digital systems is the integration of a…

This paper describes the approach used by two demonstration sites to implement Pyramid Model Practices at fidelity and address behavioral issues without the use of suspension and expulsion. The article describes the critical features of implementation used by public school preschool centers to improve the implementation of evidence-based social…