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Rebecca Whittle; Joie Ensor; Miriam Hattle; Paula Dhiman; Gary S. Collins; Richard D. Riley – Research Synthesis Methods, 2024
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…
Descriptors: Data, Individual Characteristics, Participant Characteristics, Meta Analysis
Leher Singh; Mihaela D. Barokova; Heidi A. Baumgartner; Diana C. Lopera-Perez; Paul Okyere Omane; Mark Sheskin; Francis L. Yuen; Yang Wu; Katherine J. Alcock; Elena C. Altmann; Marina Bazhydai; Alexandra Carstensen; Kin Chung Jacky Chan; Hu Chuan-Peng; Rodrigo Dal Ben; Laura Franchin; Jessica E. Kosie; Casey Lew-Williams; Asana Okocha; Tilman Reinelt; Tobias Schuwerk; Melanie Soderstrom; Angeline S. M. Tsui; Michael C. Frank – Developmental Psychology, 2024
Culture is a key determinant of children's development both in its own right and as a measure of generalizability of developmental phenomena. Studying the role of culture in development requires information about participants' demographic backgrounds. However, both reporting and treatment of demographic data are limited and inconsistent in child…
Descriptors: Data Collection, Young Children, Demography, Cultural Traits
Brown, Neil C. C.; Weill-Tessier, Pierre; Sekula, Maksymilian; Costache, Alexandra-Lucia; Kölling, Michael – ACM Transactions on Computing Education, 2023
Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…
Descriptors: Novices, Programming, Programming Languages, Data
Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Wentao Li; Jannik Aagerup; Ben W. Mol; Rui Wang; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing integrity concerns in medical research have prompted the development of tools to detect untrustworthy studies. Existing tools primarily assess published aggregate data (AD), though scrutiny of individual participant data (IPD) is often required to detect trustworthiness issues. Thus, we developed the IPD Integrity Tool for detecting…
Descriptors: Integrity, Randomized Controlled Trials, Data Use, Individual Characteristics
Kwon, Ji Hye; Cha, Hyun-Jung; Na, Seo-Ha; Um, Hyejin; Lim, Sung-Eun; Park, Changmi; Ga, Seok-Hyun; Kim, Chan-Jong – Asia-Pacific Science Education, 2022
Citizen science is expected to play an important role in relation to scientific literacy Vision III for students living in the future society. This study aims to identify the characteristics of extreme citizen science (ECS) and extreme citizen scientists (ECSs) and to derive key competencies of ECS?s using literature analysis from Korean and…
Descriptors: Citizen Participation, Scientific Research, Scientists, Scientific Literacy
Blasko, Alyssa M.; Morin, Kristi L.; Bauer, Kathleen; Johnson, Kelsey M.; Enriquez, Grace B.; Hunsicker, Lindsey E.; Tasik, Emily J.; Renz, Theodore E., III – Journal of Special Education, 2023
Most disability research is conducted in high-income countries, despite much of the world's population living in low- and middle-income countries. Given the flexible nature of qualitative research, studies using this methodology have the potential to provide important insights into how disability is perceived across the globe. The aim of the…
Descriptors: Foreign Countries, Disabilities, Research, Research Methodology
Mo Zhang; Paul Deane; Andrew Hoang; Hongwen Guo; Chen Li – Educational Measurement: Issues and Practice, 2025
In this paper, we describe two empirical studies that demonstrate the application and modeling of keystroke logs in writing assessments. We illustrate two different approaches of modeling differences in writing processes: analysis of mean differences in handcrafted theory-driven features and use of large language models to identify stable personal…
Descriptors: Writing Tests, Computer Assisted Testing, Keyboarding (Data Entry), Writing Processes
Sören Rüttgers; Ulrike Kuhl; Benjamin Paaßen – International Educational Data Mining Society, 2024
To train two-versus-two sports, it is beneficial to play regularly with varying teammates and opponents of similar skill level. However, even in small classes, it is almost impossible for a human instructor to maintain an accurate overview of each student's skill development to optimize teams and pairings accordingly. Therefore, we propose an…
Descriptors: Team Sports, Athletics, Training, Skill Development
Emily R. Koren; John W. Curtis; Adrianna Kezar; K. C. Culver – Pullias Center for Higher Education, 2024
The purpose of the Faculty, Academic Careers and Environments (FACE) project is to understand who faculty are, what their academic careers look like, and how the environments in which they work shape their ability to thrive as instructors, researchers and public scholars in the community. The goal of the project is to examine and pilot test how…
Descriptors: Higher Education, Pilot Projects, Diversity (Faculty), Individual Characteristics
Eric Richardson; Jean Gordon; Richard Ginnetti; Rachel Carroll; Randyl Cochran; Laura Morris; Valerena Candy; Margaret Brown – Journal of Education Human Resources, 2025
Beyond informing human resources (HR) policies and practices, information gleaned from predictive analytics, visualized via dashboards, can increase awareness and prompt employee and management actions based on identified variables often related to intent to leave and employee wellness. While considerable research, relevant measurements, and tools…
Descriptors: Higher Education, Employee Attitudes, Labor Turnover, Occupational Mobility
Marijn Martens; Ralf De Wolf; Lieven De Marez – Education and Information Technologies, 2024
Algorithmic systems such as Learning Analytics (LA) are driving the datafication and algorithmization of education. In this research, we focus on the appropriateness of LA systems from the perspective of parents and students in secondary education. Anchored in the contextual integrity framework (Nissenbaum, "Washington Law Review, 79,"…
Descriptors: Parent Attitudes, Student Attitudes, Learning Analytics, Algorithms
Krista M. Soria; Stacey E. Vakanski; Trevor White; Ryan Arp – Community College Review, 2024
Objective: The purpose of this paper was to examine variables associated with food insecurity among community college caregivers during the COVID-19 pandemic. Methods: We used data from a multi-institutional survey of 15,051 caregivers enrolled at 130 community colleges in 42 states in fall 2020. We used a logistic regression to examine whether…
Descriptors: Food, Hunger, Community Colleges, Caregivers
Joanna E. Bettmann; Naomi Martinez-Gutierrez; Rachel Esrig; Ellison Blumenthal; Laura Mills – Child & Youth Care Forum, 2024
Extensive research into wilderness therapy has not explored who benefits the most and who does not thrive in these programs. The present study examined demographic, clinical, and familial characteristics that distinguished adolescents who improve most in wilderness therapy programs from those who deteriorate. Using data collected by the National…
Descriptors: Adolescents, Data Analysis, Physical Environment, Therapy
Anthony L. Abell – ProQuest LLC, 2023
Small Bible colleges have limited resources to recruit students. They must find strategies to recruit and retain college-ready students who fit with their mission. With limited or no endowments or reserves, these colleges rely primarily on enrollment tuition revenue. The purpose of this study, conducted at a small Bible college in the southeastern…
Descriptors: College Admission, Predictor Variables, School Holding Power, Religious Colleges
Kyle T. Turner; George Engelhard Jr. – Journal of Experimental Education, 2024
The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…
Descriptors: Data Analysis, Multivariate Analysis, Individual Characteristics, Behavior
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