Depending on their motivational dispositions, students choose different learning strategies and vary in their persistence in reaching learning outcomes. As learning is more and more facilitated through technology, analytics approaches allow learning processes and environments to be analyzed and optimized. However, research on motivation and…

This article explores 6th-grade students' modelling with data in generating models for selecting an Australian swimming team for the (then) forthcoming 2016 Olympics, using data on swimmers' times at various previous events. We propose a modelling framework comprising four components: working in shared problem spaces between mathematics and…

Collecting data on behavior, academic skills, and Individualized Education Plan (IEP) goals is an essential step in showing student progress--but it can also be a complicated, time-consuming process. Take the worry and stress out of data collection with this ultra-practical resource, packed with the tools you need to organize, manage, and monitor…

In STEM domains, students are expected to acquire domain knowledge from visual representations that they may not yet be able to interpret. Such learning requires perceptual fluency: the ability to intuitively and rapidly see which concepts visuals show and to translate among multiple visuals. Instructional problems that engage students in…

In this paper, we describe the analysis of multimodal data collected on small collaborative learning groups. In a previous study, we asked pairs (N=84) with no programming experience to program a robot to solve a series of mazes. The quality of the dyad's collaboration was evaluated, and two interventions were implemented to support collaborative…

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,…

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…