This study aims to create learning path navigation for target learners by discovering the correlation among micro-learning units. In this study, the learning path is defined as a sequence of learning units used to realize a learning goal, and a period used for realizing the learning goal is regarded as a learning cycle. Furthermore, the learning…

The article sets out to develop the concept of attention as a key aspect to building the possible therapeutics that Bernard Stiegler's recent works have pointed to (The Automatic Society, 2016, The "Neganthropocene", 2018 and "Qu'appelle-t-on" Panser, 2018). The therapeutic aspect of pharmacology takes place through processes…

Although existing data science educational programmes develop talent and produce graduates, business-focused data science curricula comprising essential skills oriented to business and managerial data with associated analysis, remain underserved. Current pedagogy has focused either on data science or on purely analytic technical aspects. There is…

Engaging learners with complex unfamiliar datasets is a known challenge in Data Science education. One promising phenomenon investigated in related work is perspective-taking. A first-person "actor" perspective can help facilitate group and individual sensemaking by mediating observations and actions taken by learners. Here we…

In this article, the author describes the practice of active learning with Federal Reserve Economic Data (FRED). First, he outlines the broad intellectual context of learning with and about economic data, summarizing the recent scholarly contributions made to the topic. Next, the author presents several strategies for teaching with FRED in the…

Engaging in culturally responsive practices is considered best practice in classroom instruction, particularly within diverse schools, however, when making data-based decisions, there is little guidance for culturally responsive practitioners on how to engage in this work. This article introduces a model of culturally responsive data-based…

When students struggle with reading, school-based teams seek more information about why those students are struggling in order to provide instruction that will meet the students' needs. This process occurs for students needing Tier 2 or 3 instruction and students with disabilities who have reading goals. Reading specialists, special education…

The argument-based approach to validity (Kane, 2013) focuses on two steps: (1) making claims about the proposed interpretation and use of test scores as a coherent, interpretive argument; and (2) evaluating those claims based on theoretical and empirical evidence related to test performances and scores. This paper discusses the role of…

The purpose of this commentary is to push the boundaries (real and perceived) of how we think about teacher accountability, education and the purpose of schooling in contemporary times. It takes as a starting point a view that recent changes to the Every Student Succeeds Act does little to shift the underpinning logics of high-stakes teacher…

Posing statistical questions is a fundamental and often overlooked component of statistical inquiry. In this paper, we provide an overview of shared understandings regarding what constitutes a good statistical question. We then describe three approaches--a checklist for improving statistical questions, a three-phase feedback activity, and a…

The performance of statistical methods is often evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, simulations are not currently available for many practically relevant settings. We perform a simulation study for sparse networks of trials under between-trial heterogeneity and including multi-arm…

This study sought to understand the relationship between undergraduate yield and an institution's internet presence. Data were collected from 2018 "U.S. News & World Report" national university rankings, the Integrated Postsecondary Education Database (IPEDS), and summer 2018 (June-August) SEMrush data, a web metrics database housing…

While home visiting services are an important component of the early childhood (EC) landscape, few states include home visiting data in their early childhood integrated data systems (ECIDS). An ECIDS links together data from different early care and education programs to generate data used to support program and policy decisions. One reason for…

In higher education, predictive analytics can provide actionable insights to diverse stakeholders such as administrators, instructors, and students. Separate feature sets are typically used for different prediction tasks, e.g., student activity logs for predicting in-course performance and registrar data for predicting long-term college success.…

The "2nd Annual WPI-UMASS-UPENN EDM Data Mining Challenge" required contestants to predict efficient testtaking based on log data. In this paper, we describe our theory-driven and psychometric modeling approach. For feature engineering, we employed the Log-Normal Response Time Model for estimating latent person speed, and the Generalized…