We note two possibilities for how our science might capitalize on advances in computing that harness and weave "big data" into the rich tapestry of how human development unfolds. First, we propose that the classic theoretical models that have guided developmental research since the 1970s and the hierarchical analytical models used to…

The use of social media platforms as a means of data collection for researchers is increasing. With the number of active users of Facebook across the globe exceeding two billion, the platform offers a means to reach and hear from diverse populations and gather information-rich data. Despite an increase of researchers utilising Facebook and…

Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…

Autism is heterogeneous at many levels, including clinical symptoms and etiology. A key strategy in studying heterogeneous conditions is having large enough sample sizes to stratify into smaller groups that are more homogeneous. SPARK and Simons Searchlight are large and growing research cohorts of individuals with autism in the United States and…

Purpose: End-user participation is often encouraged to promote the uptake of Digital Livestock Technologies (DLTs). However, managing participation during DLT development can be challenging. We explore how participation decisions can impact end-users' engagement and attitudes towards the process, before suggesting strategies for improved…

The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…

Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…

This paper describes, and lays out an argument for, the use of a procedure to help groups of reviewers to judge the quality of prior research reports. It argues why such a procedure is needed, and how other existing approaches are only relevant to some kinds of research, meaning that a review or synthesis cannot successfully combine quality…

Program evaluation is an essential practice for providers of behavior analytic services, as it helps providers understand the extent to which they are achieving their intended mission to the community they serve. A proposed method for conducting such evaluations, is through the use of a consecutive case series design, for which cases are…

This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator's research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic…

In the 2023 report "Colorado's Longitudinal Data Landscape. Report to the Education Committees of the Colorado House of Representatives and the Colorado Senate. Statute: 23-1-141," the Colorado Department of Higher Education (CDHE) provided a detailed overview of Colorado's long history of efforts to support more connected, longitudinal…

As organizations' reliance on data increases, the prevalence of data analytics programs in universities likewise increases. However, despite this specialized education, scholars still report a gap between the knowledge and skills students graduate with and those required by industry upon beginning work as an entry-level data analyst. We draw on…

The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

Internet-of-Things (IoT) research has primarily focused on identifying IoT devices' organizational risks with little attention to consumer perceptions about IoT device risks. The purpose of this study is to understand consumer risk perceptions for personal IoT devices and translate these perceptions into guidance for future research directions. We…

Historic data in analog (or print) format is a valuable resource that is utilized by scientists in many fields. This type of data may be found in various locations on university campuses including offices, labs, storage facilities, and archives. This study investigates whether biological data held in one institutional university archives could be…