Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…

Head Start is a national program that helps young children from families with low income get ready to succeed in school. It does this by working to promote their early learning and health and their families' well-being. The Head Start Family and Child Experiences Survey (FACES) provides national information about Head Start programs and…

The Stanford Education Data Archive (SEDA) launched in 2016 to provide nationally comparable, publicly available test score data for U.S. public school districts. I introduce a special collection of six articles that each use SEDA to lend their questions and findings a national scope. Together, these articles demonstrate a range of uses of SEDA…

Physics education research (PER) has long used concept inventories to investigate student learning over time and to compare performance across various student subpopulations. PER has traditionally used normalized gain to explore these questions but has begun to use established methods from other fields, including Cohen's "d," multiple…

Although educational research and evaluation generally occur in multilevel settings, many analyses ignore cluster effects. Neglecting the nature of data from educational settings, especially in non-randomized experiments, can result in biased estimates with long-term consequences. Our manuscript improves the availability and understanding of…

This work proposes relevant ingredients to highlight the factors with significant impact on efficiency of research structures in higher education. The ingredients in question include methods and their implementation taking into account the choice and operationalization of factors as well as options of the retained methods. The methods employed in…

Recommendations from multiple professional organizations (e.g., American Psychological Association, Council for Exceptional Children, National Association of School Psychologists) suggest that collection of data on the social validity in practice and research is necessary. The purpose of this study was to systematically review the inclusion of…

One major challenge of longitudinal data analysis is to find an appropriate statistical model that corresponds to the theory of change and the research questions at hand. In the present article, we argue that "continuous-time models" are well suited to study the continuously developing constructs of primary interest in the education…

States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce differences between the original data and the…

States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce differences between the original data and the…

Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers. Using nearly 1,000 word-to-word transcriptions of fourth- and fifth-grade English language arts classes, we apply novel text-as-data methods to develop automated measures of teaching to complement classroom observations…

Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers, but conventional classroom observations are costly, prone to rater bias, and hard to implement at scale. Using nearly 1,000 word-to-word transcriptions of 4th- and 5th-grade English language arts classes, we apply novel…

The assessment and understanding of students' ideas in discourse have often been a difficult problem for teachers to tackle. Recent innovations and technologies such as text mining can provide a partial solution by generating an estimated count of important keywords which are representative of ideas within discourse. However, investigating idea…

MOOCs attract a large number of learners with largely unknown diversity in terms of motivation, ability, and goals. To understand more about learners in highly technical engineering MOOCs, this study investigates patterns of learners' (n = 337) behaviour and performance in the Nanophotonic Modelling MOOC, offered through nanoHUB-U. The authors…

The Stanford Educational Data Archive (SEDA) is the first data set to allow comparisons of district academic achievement and growth from Grades 3 to 8 across the United States, shining a light on the distribution of educational opportunities. This study describes a convergent validity analysis of the SEDA growth estimates in mathematics and…