Teachers' use of student data to inform instruction is commonly accepted as sound educational practice, and this data use is only likely to grow as more data, as well as more-complex data, become increasingly available to educators. However, numerous studies reveal inconsistent data use among teachers and an overall lack of the preparation and…

Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These…

This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning…

This "Just in Time" research is in response to recent discussions on the EDUCAUSE Higher Education Information Security Council (HEISC) discussion list about data breaches in higher education. Using data from the Privacy Rights Clearinghouse, this research analyzes data breaches attributed to higher education. The results from this…

Many researchers who are interested in studying students' online self-regulated learning (SRL) have heavily relied on self-reported surveys. Data mining is an alternative technique that can be used to discover students' SRL patterns from large data logs saved on a course management system. The purpose of this study was to identify students' online…

Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

As data-based decision making is receiving increased attention in education, more and more school performance feedback systems (SPFSs) are being developed and used worldwide. These systems provide schools with data on their functioning. However, little research is available on the characteristics of the different SPFSs. Therefore, this study…

There is extensive research on the benefits of making data-informed decisions to improve learning, but these benefits rely on the data being effectively interpreted. Despite educators' above-average intellect and education levels, there is evidence many educators routinely misinterpret student data. Data analysis problems persist even at districts…

A statewide survey of the infrastructure of teacher education program assessment systems in North Carolina, which include electronic portfolios as a component in the assessment system, measured their ability to meet current and anticipated future data demands for state approval and national accreditation. Almost two-thirds of the 46 teacher…

This paper describes a study of success factors in high enrollment courses in a K-12 virtual school learning environment. The influence of variables: time student spent in the learning management system (LMS), number of times logged into the LMS, teacher comment, participation in free or reduced lunch programs, student status in the virtual school…

This paper describes and evaluates a computerized system, MATCH, which is being used in South Carolina to match or link student records from year to year. The functioning of MATCH and its specific features are described, and its use in matching student test scores is detailed. The problem of mismatched records and the use of visual editing to…

Database Tomography (DT) is a textual database-analysis system consisting of algorithms for extracting multiword phrase frequencies and proximities from a large textual database, to augment interpretative capabilities of the expert human analyst. Describes use of the DT process, supplemented by literature bibliometric analyses, to derive technical…

Data administration (DA) is a position that has emerged with the growth of information technologies. A review of DA literature confirms that, although DA is widely associated with database management systems (DBMS), there is no standard DA job description, DA staffing and location within the organization vary, and DA functions range in description…

This paper discusses the transfer ready concept and includes data demonstrating the accuracy and efficiency of the new transfer ready model, in contrast to the current Student-Right-to-Know model. It explains the process of calculating the percentage rates of transfer directed students (those enrolled in both transfer English and math in their…