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…

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 purpose of this paper is to analyze various dimensions for measurement of human behavior. Human behaviour is complex. Behaviors, emotions, cognitions, and attitudes can rarely be described in terms of one or two variables. It is multimodal in nature. Furthermore, the traits, modalities and dimensions cannot be measured directly, but must be…

The COVID epidemic has provided an excellent example of the need to call on a wide variety of statistical tools to address a global problem, and can give students insights into some of the dimensions of data science. Here, we describe some of the characteristics of data that students encounter as citizens. We set out some teaching ideas, which…

Acting to dismantle structural racial inequities begins with identifying and clearly naming the challenges being faced. Data play a powerful role in this process. Several recent publications synthesize data sources, research findings, and expert recommendations to inform and guide equity improvement efforts. A five-part "Statement of the…

Tracking and using data to inform decisions pays off for college success programs on multiple levels. Having data allows program staff to monitor the progress of individual students and tailor support to their particular needs. It enables staff to understand the effectiveness of program activities and make improvements as necessary. Most…

This paper describes a preliminary study of how computational methods allow us to know more about citizen science and its connection with education. Citizen science is a practice involving a general public in scientific tasks and generating knowledge and scientific results. Previous studies have shown that the education sector can take benefit of…

There is an increasing interest and growing practice in Citizen Science (CS) that goes along with the usage of websites for communication as well as for capturing and processing data and materials. From an educational perspective, it is expected that by integrating information about CS in a formal educational setting, it will inspire teachers to…

Child Trends and Start Early have partnered to better understand what early childhood systems builders need to build and support more equitable systems. The briefs in this series, called Conversation Starters, define a new framework for early childhood systems that center families' experiences and raise key considerations and next steps for…

Data is so deeply woven into the fabric of people's lives that it is next to impossible to imagine what a data-free life would be like. But despite the centrality of data in everyone's personal lives, when people talk about data in schools, their comments are often negative. The authors of this article believe "data" should not be a…

The purpose of this study is to develop a valid and reliable Likert-type scale that can be used to measure the data literacy skills of educators. In the development process of the scale, after reviewing the relevant literature, a pool of 130 items was designed and presented to the experts for their view. After the evaluation of experts, the…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…

There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…