This study examined current social science qualitative and mixed methods research practices in the adoption and use of data management and analysis technology with three questions: 1) who uses technology for qualitative and mixed methods data analysis? 2) what can be learned by knowing who these researchers are? and, 3) how might current…

Public administration is struggling to contend with a substantial shift in practice fueled by the accelerating adoption of information technology. New skills, competencies and pedagogies are required by the field to help overcome the data-skills gap. As a means to address these deficiencies, we introduce the Data Science Literacy Framework, a…

Despite the relative youth of bibliometric web platforms (Google Scholar was released in 2004), they play an increasingly significant role in the assessment of the impact of scholars and the research they produce. This scholarly essay provides a thorough review of the literature on bibliometric platforms, the extent to which they make available…

Learning Management Systems (LMS) are software applications that facilitate the management and monitoring of online teaching courses and/or training programs, workshops, webinars, forums, and other similar learning activities. The LMS provides learning and teaching benefits and possibilities for synchronous, asynchronous, and hybrid training. For…

Instructors at postsecondary institutions have designed a myriad of data science classes to keep up with the rise of big data. Businesses and companies have become increasingly interested in hiring people with strong data acquisition, management, and communication skills. Since data science as a field of study is relatively new, though it has deep…

This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections. The paper introduces: (1) VLE, a novel dataset that consists of content and video based features extracted from publicly available scientific video lectures coupled with implicit and explicit signals related to…

We assessed whether an adaptation of value-added analysis (VAA) can provide evidence on the relative effectiveness of interventions implemented in a large school district. We analyzed two datasets, one documenting interventions received by underperforming students, and one documenting interventions received by students in schools benefiting from…

This article-format dissertation focuses on how scholars use social media to support their scholarship. The first article is a scoping literature review that outlines current research. While overviewing an emergent field of literature, the article highlights motivations for using social media use, discusses benefits and drawbacks of this use for…

We assessed whether an adaptation of value-added analysis (VAA) can provide evidence on the relative effectiveness of interventions implemented in a large school district. We analyzed two datasets, one documenting interventions received by underperforming students, and one documenting interventions received by students in schools benefiting from…

A growing literature uses value-added (VA) models to quantify principals' contributions to improving student outcomes. Principal VA is typically estimated using a connected networks model that includes both principal and school fixed effects (FE) to isolate principal effectiveness from fixed school factors that principals cannot control. While…

When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…

Large-scale analyses are a powerful and increasingly common tool for investigating a range of public health and social concerns (Pienta, O'Rourke, & Franks, 2011). This series will provide a primer on large-scale secondary analysis in school psychology, with this article focusing on considerations for researchers interested in applying and…

The purpose of this study was to compare 12 commonly-used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema-based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each…

Missing data result in less precise and possibly biased effect estimates in single studies. Bias arising from studies with incomplete outcome data is naturally propagated in a meta-analysis. Conventional analysis using only individuals with available data is adequate when the meta-analyst can be confident that the data are missing at random (MAR)…

As California invests in early learning and care, the state is also moving forward with a long-overdue plan to build a statewide longitudinal data system (SLDS) -- known as the Cradle-to-Career (C2C) Data System -- which will eventually connect data over time and across sectors like education, health, human services, and the workforce. This is a…