Browsing by Subject "data collection"

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COVID-19 Texas College Student Experiences Survey: Data Collection
(2024-04-14) Latino Research Institute
This record includes the surveys distributed to respondents for data collection in the COVID-19 Texas College Student Experiences study. It includes wave 1 and wave 2 surveys (both in English).
Designing Across Distributed Agency: Values, participatory design and building socially responsible AI
(Participatory Design Conference, 2020-05-25) Slota, Stephen C
How Can Improving Data Collection and Reporting Advance the Civil Rights of LGBT Students?
(University of Texas at Austin Population Research Center, 2016-03) Russell, Stephen
Managing Data Collection for Real-Time Reference: Lessons from the AskERIC Live! Experience
(2003) Belanger, Yvonne; Lankes, R. David; Shostack, Pauline Lynch
Successful management of a real-time digital reference service requires effective and efficient data collection to provide accurate and useful information about service processes and outcomes. This article describes the data collection procedures developed by AskERIC for its real-time reference service; in particular, this article will describe how these procedures address limitations, gaps, and inaccuracies in the data as passively captured by software. Finally, particular issues and considerations for service managers about various statistical measures within the real-time environment are discussed.
Multi-Modal Data Collection for Measuring Health, Behavior, and Living Environment of Large-Scale Participant Cohorts: Conceptual Framework and Findings from Deployments
(2020-10-16) Wu, Congyu; Fritz, Hagen; Nagy, Zoltan; Maestre, Juan P.; Thomaz, Edison; Julien, Christine; Castelli, Darla M.; de Barbaro, Kaya; Harari, Gabriella M.; Craddock, R. Cameron; Kinney, Kerry A.; Gosling, Samuel D.
As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness, unobtrusiveness, and ecological validity. A number of human-subject studies have been conducted in the past decade to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes. While understanding health and behavior is the focus for most of these studies, we find that minimal attention has been placed on measuring personal environments, especially together with other human-centric data modalities. Moreover, the participant cohort size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes. To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with established mobile sensing and experience sampling techniques in a cohort study of up to 1584 student participants per data type for 3 weeks at a major research university in the United States. In this paper, we begin by proposing a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study design and procedure, technologies and methods deployed, descriptive statistics of the collected data, and results from our extensive exploratory analyses. Our novel data, conceptual development, and analytical findings provide important guidance for data collection and hypothesis generation in future human-centric sensing studies.
Well-Being and Mental Health of Health Professionals Providing Services During the COVID-19 Pandemic: Data Collection
(2024-04-14) Latino Research Institute
This record includes the surveys used for data collection in the Well-Being and Mental Health of Health Professionals Providing Services During the COVID-19 Pandemic study. Two PDF files are included: one that contains both wave 1 surveys in English and Spanish, and another that contains both wave 2 surveys in English and Spanish.