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Direct linkMatthew J. Salganik; Ian Lundberg; Alexander T. Kindel; Caitlin E. Ahearn; Khaled Al-Ghoneim; Abdullah Almaatouq; Drew M. Altschul; Jennie E. Brand; Nicole Bohme Carnegie; Ryan James Compton; Debanjan Datta; Thomas Davidson; Anna Filippova; Connor Gilroy; Brian J. Goode; Eaman Jahani; Ridhi Kashyap; Antje Kirchner; Stephen McKay; Allison C. Morgan; Alex Pentland; Kivan Polimis; Louis Raes; Daniel E. Rigobon; Claudia V. Roberts; Diana M. Stanescu; Yoshihiko Suhara; Adaner Usmani; Erik H. Wang; Muna Adem; Abdulla Alhajri; Bedoor AlShebli; Redwane Amin; Ryan B. Amos; Lisa P. Argyle; Livia Baer-Bositis; Moritz Büchi; Bo-Ryehn Chung; William Eggert; Gregory Faletto; Zhilin Fan; Jeremy Freese; Tejomay Gadgil; Josh Gagné; Yue Gao; Andrew Halpern-Manners; Sonia P. Hashim; Sonia Hausen; Guanhua He; Kimberly Higuera; Bernie Hogan; Ilana M. Horwitz; Lisa M. Hummel; Naman Jain; Kun Jin; David Jurgens; Patrick Kaminski; Areg Karapetyan; E. H. Kim; Ben Leizman; Naijia Liu; Malte Möser; Andrew E. Mack; Mayank Mahajan; Noah Mandell; Helge Marahrens; Diana Mercado-Garcia; Viola Mocz; Katariina Mueller-Gastell; Ahmed Musse; Qiankun Niu; William Nowak; Hamidreza Omidvar; Andrew Or; Karen Ouyang; Katy M. Pinto; Ethan Porter; Kristin E. Porter; Crystal Qian; Tamkinat Rauf; Anahit Sargsyan; Thomas Schaffner; Landon Schnabel; Bryan Schonfeld; Ben Sender; Jonathan D. Tang; Emma Tsurkov; Austin van Loon; Onur Varol; Xiafei Wang; Zhi Wang; Julia Wang; Flora Wang; Samantha Weissman; Kirstie Whitaker; Maria K. Wolters; Wei Lee Woon; James Wu; Catherine Wu; Kengran Yang; Jingwen Yin; Bingyu Zhao; Chenyun Zhu; Jeanne Brooks-Gunn; Barbara E. Engelhardt; Moritz Hardt; Dean Knox; Karen Levy; Arvind Narayanan; Brandon M. Stewart; Duncan J. Watts; Sara McLanahan – Grantee Submission, 2020
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning…
Descriptors: Life Satisfaction, Family Life, Quality of Life, Disadvantaged
Kim, Jerin – ProQuest LLC, 2019
This study evaluated the predictive and concurrent validity of the Tiered Fidelity Inventory (TFI). Structural equation modeling was applied to test the associations between the TFI and student outcomes. First, a total of 1,691 schools with TFI Tier 1 in 2016-17 and school-wide discipline outcomes in 2015-16 and 2016-17 were targeted, finding a…
Descriptors: Fidelity, Response to Intervention, Measures (Individuals), Predictive Validity
Helen J. Nelson; Garth E. Kendall; Sharyn K. Burns; Kimberly A. Schonert-Reichl; Robert T. Kane – International Journal of Bullying Prevention, 2019
Social isolation of school children is increased when teachers feel unable to respond to children's report of witnessing or experiencing aggression at school. Teachers can find it difficult to respond adequately to children who report aggression when the aggression is deliberately hidden from the teacher by the perpetrator. This study aimed to…
Descriptors: Aggression, Peer Relationship, Bullying, Test Construction
Anne H. Davidson – National Assessment Governing Board, 2025
The purpose of this National Assessment of Educational Progress (NAEP) Achievement Levels Validity Argument Report is to synthesize evidence currently available to address the validity of the interpretations and uses of the NAEP Achievement Levels. Validity is the extent to which theory and evidence supports or refutes proposed and enacted test…
Descriptors: National Competency Tests, Academic Achievement, Test Validity, College Entrance Examinations
Ursula Holzmann; Sulekha Anand; Alexander Y. Payumo – Advances in Physiology Education, 2025
Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenges for using such tools in college classrooms. To address this, an adaptable assignment called the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Thinking Skills
Marzieh Haghayeghi; Ali Moghadamzadeh; Hamdollah Ravand; Mohamad Javadipour; Hossein Kareshki – Journal of Psychoeducational Assessment, 2025
This study aimed to address the need for a comprehensive assessment tool to evaluate the mathematical abilities of first-grade students through cognitive diagnostic assessment (CDA). The primary challenge involved in this endeavor was to delineate the specific cognitive skills and sub-skills pertinent to first-grade mathematics (FG-M) and to…
Descriptors: Test Construction, Cognitive Measurement, Check Lists, Mathematics Tests
Joshua Angrist; Peter Hull; Russell Legate-Yang; Parag A. Pathak; Christopher R. Walters – Blueprint Labs, 2025
School districts increasingly gauge school quality with surveys that ask about school climate and student engagement. We use data from New York City's middle and high schools to compare the long-run predictive validity of surveys with that of conventional test score value-added models (VAMs). Our analysis leverages the New York school match, which…
Descriptors: School Districts, School Surveys, Learner Engagement, School Effectiveness
Wani N. M. Sapuan; Nur A. Sulaiman – Teaching English with Technology, 2025
The COVID-19 pandemic has transformed teaching and learning in ESL education, particularly through the integration of artificial intelligence (AI) technologies into current English Language Teaching (ELT) practices. However, to ensure the seamless integration of these technologies into ELT practices, a proper framework needs to be developed and…
Descriptors: Technology Integration, English (Second Language), Second Language Learning, Second Language Instruction
Amber E. DeBono; Kathy B. Ewoldt; Michele Heimbauer; Elizabeth A. Mendelsohn; Jonathan Cohen – Learning Disability Quarterly, 2025
Although many social-emotional learning (SEL) surveys exist for the general student population, students with learning disabilities (SwLD) are often excluded during the survey development process, and the current SEL surveys often overlook critical SEL competencies for SwLD (e.g., self-advocacy), necessitating an SEL survey for SwLD. To address…
Descriptors: Social Emotional Learning, Surveys, Students with Disabilities, Learning Disabilities
Karin A. Pfeiffer; Kimberly A. Clevenger; Aaron P. Wood; Jennifer Zink; Amanda Sharfman; Meher Din – Measurement in Physical Education and Exercise Science, 2025
In 2011, the National Collaborative on Childhood Obesity Research established a Measures Registry (updated in 2020) for four key variables associated with childhood obesity. We analyzed the individual physical activity behaviors portion of the Measures Registry to highlight strengths and gaps in the reliability and validity literature for…
Descriptors: Physical Activity Level, Test Validity, Test Reliability, Children
Monika Szczygiel; Marzena Kutt – Journal of Numerical Cognition, 2025
This study aims to present the psychometric properties of the Polish language version of the Mathematical Resilience Scale (MRS; Kooken et al., 2016), established in a sample of 443 adults. We confirmed the first-order three-factor structure (Value, Struggle, Growth) with the second-order factor (Total Mathematical Resilience) of the MRS and its…
Descriptors: Mathematics Education, Mathematics Achievement, Mathematics Anxiety, Factor Structure
Mark Feng Teng – JALT CALL Journal, 2025
The present study aims to bridge the gap of validating the Vocabulary Learning Strategies in Watching Audiovisual Materials (VLSWAM) questionnaire, a tool designed to assess strategies learners use to acquire vocabulary through audiovisual content. Grounded in multimedia learning theory, the study employed exploratory factor analysis (EFA) and…
Descriptors: Test Validity, Questionnaires, Vocabulary Development, Learning Strategies
Shiau Huai Choong; Esther Gnanamalar Sarojini Daniel; Dorothy Dewitt – Journal of International and Comparative Education, 2025
This article describes the development of a Confucian heritage culture (CHC) scale, where a conceptual definition of CHC emerged from interdisciplinary perspectives. The scale dimensions adopted interdisciplinary perspectives from history, psychology, political science, and science education. The validity and reliability of the scale were…
Descriptors: Foreign Countries, Confucianism, Cultural Background, Heritage Education
Chih-Chan Cheng; Jeen-Shing Wang; Xiaoming Zhai; Ya-Ting Carolyn Yang – International Journal of STEM Education, 2025
Background: UNESCO reports that around 70 countries have adopted AI-related strategies, recognizing AI literacy as essential for preparing citizens in an AI-driven world. Yet, two key challenges remain: limited AI literacy development at the foundational level and persistent gender gaps in AI fields. Without early, inclusive education,…
Descriptors: Technological Literacy, Artificial Intelligence, Barriers, Gender Differences
Benton, Tom – Research Matters, 2019
For many practical purposes, it is often assumed that the quality of a marker is directly related to their seniority. At its extreme, the assumption is that the most senior marker (the Principal Examiner) is always right even in cases where large numbers of junior markers have a collectively different opinion regarding the mark that should be…
Descriptors: Examiners, Scoring, Predictive Validity, Scores
