The premier Tier 3 intervention for the Pyramid Model, Prevent-Teach-Reinforce for Young Children (PTR-YC) is a research-proven, family-centered approach used in preschool settings nationwide to resolve persistent challenging behaviors. Now this bestselling PTR-YC guidebook is in a thoughtfully revised second edition, with enhancements and…

Program evaluation is important for assessing the implementation and outcomes of local, state, and federal programs. The Program Evaluation Toolkit provides tools and resources to support individuals responsible for evaluating and monitoring local, state, or federal programs. The toolkit comprises eight modules that cover critical steps in program…

In classrooms, some transitions between activities impose (quasi-)synchronicity, meaning there is a need for learners to move between activities at the same time. To make real-time decisions about when to move to the next activity, teachers need to be able to balance the progress of their students as they work at different paces. In this paper, we…

The growth of Learning Analytics (LA) as a research field has been extensively documented since its beginnings. This paper provides a broad overview of the publications that Latin American authors have published in the last years by performing a quantitative review of the literature (from 2011 to 2019). A total of 282 papers were collected and…

Institutional staff such as enrollment managers, business officers, and institutional researchers are often asked to predict enrollments. Developing any predictive model can be intimidating, particularly when there is no textbook to follow. This paper provides a practical framework for generating enrollment projection options and for evaluating…

In this ITEMS module, we provide a two-part introduction to the topic of reliability from the perspective of "classical test theory" (CTT). In the first part, which is directed primarily at beginning learners, we review and build on the content presented in the original didactic ITEMS article by Traub and Rowley (1991). Specifically, we…

Researchers have explored a variety of topics related to identifying and distinguishing among specific types of rater effects, as well as the implications of different types of incomplete data collection designs for rater-mediated assessments. In this study, we used simulated data to examine the sensitivity of latent trait model indicators of…

Purpose: The purposes of this paper are to provide a description of AI and to document and compare two applications of AI, one in program evaluation and another in an applied research study. Design/methodology/approach: Focus groups, interviews and observations were used to gather rich qualitative data which was used to detail Appreciative…

We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…

This book presents different data collection and representation techniques: elementary descriptive statistics, confirmatory statistics, multivariate approaches and statistical modeling. It exposes the possibility of giving more robustness to the classical methodologies of education sciences by adding a quantitative approach. The fundamentals of…

Information about the overall documentary filmmaking process is available; however, there is a lack of literature and educational resources about how to conduct subject research and data collection. As documentary filmmaking becomes an increasingly democratic endeavor due to technology, and information distribution and education use increases,…

A recurring debate in mixed methods research involves the relationship between research methods and research paradigms. Whereas some scholars appear to assume that qualitative and quantitative research methods each necessarily belong with particular research paradigms, others have called for greater flexibility and have taken a variety of stances…

We introduce a model which combines principles from psychometric and connectionist paradigms to allow direct Q-matrix refinement via backpropagation. We call this model dAFM, based on augmentation of the original Additive Factors Model (AFM), whose calculations and constraints we show can be exactly replicated within the framework of neural…

The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…

This report focuses on data governance at post-secondary institutions and related organizations. Data governance is defined as the formal execution and enforcement of authority over the management of data and data-related assets (Seiner, 2014). An overview of data governance at higher education institutions provides detail on elements of data…