Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…

Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…

One part of COVID-19's staggering impact on education has been to suspend or fundamentally alter ongoing education research projects. This article addresses how to analyze the simple but fundamental example of a multi-cohort study in which student assessment data for the final cohort are missing because schools were closed, learning was virtual,…

The process of data analysis provides, undoubtedly, some of the major challenges facing organizations during the implementation of interventions in emergencies. The challenges are primarily due to the lack of direct access to beneficiaries and the rapidly evolving nature of emergencies. This paper outlines how Plan International's Making Ghanaian…

Equitable opportunities for performance measurement learning among social work graduate students can create a diverse professional pipeline toward higher performing organizations. A Foundation-University partnership was developed to "expand the bench" of students, primarily of color, trained in performance measurement with the…

This article presents the Data Science Ethos Lifecycle, a tool for engaging responsible workflow developed by an interdisciplinary team of social scientists and data scientists working with the Academic Data Science Alliance. The tool uses a data science lifecycle framework to engage data science students and practitioners with the ethical…

The purpose of the study is to analyse and identify the stages of adoption of the blended learning (BL or b-learning) methodology in higher education contexts, and to assess the relationship of these stages with a set of variables related to personal and professional characteristics, attributes perceived on BL and contextual variables. About 980…

This study of 52 undergraduates of English as a foreign language (EFL) involves an empirical assessment of the pedagogical suitability of data-driven learning (DDL) in three Taiwanese grammar classes. One class (16 students) was taught using a traditional deductive approach (TDA), and the others (one of 17 and one of 19 students) were taught using…

The increasing importance of empirical analysis in economics highlights the need for efficient ways to bring these skills to the classroom. R Markdown is a new technology that provides a solution by integrating writing, statistical work and computation into a single document. R Markdown benefits students and instructors by streamlining teaching,…

Bethune-Cookman University's Center for Undergraduate Research Excellence has operated a summer research program since 2014. An interdisciplinary team of faculty mentors and student research fellows examined variables impacting juvenile delinquency and risk of recidivism within Florida, using a database of more than 64,000 youth who aged out of…

This article examines student engagement in an inquiry-based learning activity, planned to provide students with elements in the social, epistemic, and conceptual dimensions related to the scientific practice in immunology. The activity was applied to 39 groups of students enrolled in immunology or biochemistry courses in a public university in…

Genomics is a core course for bioscience-majored undergraduates in many universities. However, the teaching of genomics faces many challenges such as the need for rapid updating of related knowledge, content overlap between genomics and molecular biology, lack of motivation of students in the traditional passive classroom-learning model, the…

The purpose of this study was to investigate the study general trends with regards to Web 2.0 technologies supporting problem-based learning (PBL) environments. A systematic literature review was applied to analyse studies published in this area, with a total of 18 articles included in the review. The content analysis method was applied in the…

School leaders are assumed to be important for the implementation of data-based decision making (DBDM), but little is known about changes in leadership during this implementation. Educational leadership was measured before, during, and after a two-year, school-wide DBDM intervention in 96 primary schools. Advanced analysis techniques were applied:…

This study explores and characterizes learners' participation patterns in MOOC forums, as well as the factors that correlate with learners' participation. Educational data mining and learning analytics methods were used to retrieve and analyze the learners' interpersonal interaction data, which had accumulated in the Coursera log files. The…