This paper proposes the theoretical context for a course development framework to address the specific needs and challenges of teaching and learning in interdisciplinary studies (IDS). User-centred design (UCD) principles are used for this development process. Traditional course development frameworks provide a helpful guide in terms of setting…

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…

This article discusses issues concerning the spread of data-driven educational technologies in Brazil. Here, as elsewhere, educational technology continues to be promoted optimistically as the bearer of a panacea for historically-rooted social problems. Whilst some of these technologies have indeed contributed to important widening-participation…

This article discusses how each of the papers in this special issue explored some combination of subject, audience, and data scientist perspectives with an eye toward helping students situate their relationship to data. Specifically, within the data scientist perspective, the papers examined a variety of ways in which students can relate to data…

Connecting teachers' perspectives with their practice is an enduring challenge shaping what and how we understand teaching. Researchers tend to bifurcate teachers' work between their private and their public lives. These "worlds" bring particular meanings that are rendered through the analyses of visual documentations of teaching and…

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…

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 field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have 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…

Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…

National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…

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…