We present a model for sharing quantitative data in the field of physics education research and use it to present a newly available dataset as an example. This model is in line with calls from across physics and science more generally to democratize data and results through open access. The model includes suggestions for data collection, creation…

This manuscript provides information on datasets pertaining to Project KIDS. Datasets include behavioral and achievement data for over 4,000 students between five and twelve years old participating in nine randomized control trials of reading instruction and intervention between 2005-2011, and information on home environments of a subset of 442…

Purpose: Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches -- in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and…

Purpose: This paper aims to provides a brief review of the dashboard literature, an account of the development of performance dashboards for field data collection at Westat, and more specifically for the first cycle of the Programme for the International Assessment of Adult Competencies (PIAAC). A brief concluding section offers suggestions for…

Observers have expressed concern about growing inequality in resources across universities. But are universities really becoming more unequal? We argue that the typical approach of examining endowment growth alone is not sensible. In line with the literature on household inequality, we focus instead on a comprehensive income measure. We find that…

This article examines two methodological issues regarding ways of obtaining and analyzing outcome data for people with intellectual disabilities: (a) self-report and proxy-report data and (b) analysis of population-based data sets. Some people with intellectual disabilities have difficulties with self-reporting due to problems of understanding and…

Increasingly US jobs require data science and analytics skills. Can we meet the demand? The current shortage of skills in the national job pool demonstrates that business-as-usual strategies won't satisfy the growing need. If we are to unlock the promise and potential of data and all the technologies that depend on it, employers and educators will…

As part of our NSF funded collaborative project on Data Sharing within Engineering Education Community, we conducted an empirical study to better understand the current climate of data sharing and participants' future expectations of the field. We present findings of this mixed method study and discuss implications. Overall, we found strong…

This manual provides guidance and documentation for users of the kindergarten (or base year) data of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It begins with an overview of the ECLS-K:2011. Subsequent chapters provide details on the study data collection instruments and methods; the direct and indirect…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

This manual provides guidance and documentation for users of the longitudinal kindergarten-first grade (K-1) data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It mainly provides information specific to the first-grade rounds of data collection. Data for the ECLS-K:2011 are released in both a…

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

The article addresses the question of how the assessment process with large-scale data derived from online learning environments will be different from the assessment process without it. Following an explanation of big data and how it is different from previously available learner data, we describe three notable features that characterize…

The true power of comparative research around the impact and use of open educational resources is only just being realised, largely through the work done by the Hewlett-funded OER Research Hub, based at The Open University (UK). Since late 2012, the project has used a combination of surveys, interviews and focus groups to gather data about the use…

The purpose of this study was to determine if there was a difference in how high and low performing elementary school districts use and analyze data to differentiate instruction, make changes to district/grade level curriculum, determine professional development needs, determine teacher effectiveness, and determine the use of school district…