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Daniel Katz; Anne Corinne Huggins-Manley; Walter Leite – Applied Measurement in Education, 2022
According to the "Standards for Educational and Psychological Testing" (2014), one aspect of test fairness concerns examinees having comparable opportunities to learn prior to taking tests. Meanwhile, many researchers are developing platforms enhanced by artificial intelligence (AI) that can personalize curriculum to individual student…
Descriptors: High Stakes Tests, Test Bias, Testing Problems, Prior Learning
Evan Rosenman; Rina Friedberg; Michael Baiocchi – Society for Research on Educational Effectiveness, 2022
Background and Context: In 2016, our team designed and implemented a cluster-randomized trial of a school-based empowerment training program, targeting adolescent girls in Nairobi, Kenya (Baiocchi et al., 2019; Rosenman et al., 2020). In that study, the primary outcome was the experience of sexual violence in the prior year. Participants disclosed…
Descriptors: Foreign Countries, Adolescents, Females, Sexual Abuse
Benjamin W. Y. Hornsby; Stephen Camarata; Sun-Joo Cho; Hilary Davis; Ronan McGarrigle; Fred H. Bess – Journal of Speech, Language, and Hearing Research, 2022
Purpose: Growing evidence suggests that fatigue associated with listening difficulties is particularly problematic for children with hearing loss (CHL). However, sensitive, reliable, and valid measures of listening-related fatigue do not exist. To address this gap, this article describes the development, psychometric evaluation, and preliminary…
Descriptors: Test Construction, Fatigue (Biology), Hearing Impairments, Listening
Rustam, Ahmad; Naga, Dali Santun; Supriyati, Yetti – International Journal of Education and Literacy Studies, 2019
Detection of differential item functioning (DIF) is needed in the development of tests to obtain useful items. The Mantel-Haenszel method and standardization are tools for DIF detection based on classical theory assumptions. The study was conducted to highlight the sensitivity and accuracy between the Mantel-Haenszel method and the standardization…
Descriptors: Statistical Analysis, Test Bias, Accuracy, Multiple Choice Tests
Wolkowitz, Amanda A.; Wright, Keith D. – Journal of Educational Measurement, 2019
This article explores the amount of equating error at a passing score when equating scores from exams with small samples sizes. This article focuses on equating using classical test theory methods of Tucker linear, Levine linear, frequency estimation, and chained equipercentile equating. Both simulation and real data studies were used in the…
Descriptors: Error Patterns, Sample Size, Test Theory, Test Bias
Zhong Jian Chee; Anke M. Scheeren; Marieke de Vries – Autism: The International Journal of Research and Practice, 2024
Despite several psychometric advantages over the 50-item Autism Spectrum Quotient, an instrument used to measure autistic traits, the abridged AQ-28 and its cross-cultural validity have not been examined as extensively. Therefore, this study aimed to examine the factor structure and measurement invariance of the AQ-28 in 818 Dutch (M[subscript…
Descriptors: Autism Spectrum Disorders, Questionnaires, Factor Structure, Factor Analysis
Katherine T. Rhodes; Julie A. Washington; Sibylla Leon Guerrero – Educational Assessment, 2024
Little is known about mismatches between the language of mathematics testing instruments and the rich linguistic repertoires that African American children develop at home and in the community. The current study aims to provide a proof of concept and novel explanatory item response design that uses error analysis to investigate the relationship…
Descriptors: Black Dialects, African American Students, Language Usage, Mathematics Tests
A. Corinne Huggins-Manley; Jing Huang; Jerri-ann Danso; Wei Li; Walter L. Leite – Journal of Experimental Education, 2024
The global COVID-19 health pandemic caused major interruptions to educational assessment systems, partially due to shifts to remote learning environments, entering the post-COVID educational world into one that is more open to heterogeneity in instructional and assessment modes for secondary students. In addition, in 2020, educational inequities…
Descriptors: Student Evaluation, Educational Environment, Educational Change, COVID-19
Jonathan Schmidgall; Yan Huo; Jaime Cid; Youhua Wei – ETS Research Report Series, 2024
The principle of fairness in testing traditionally involves an assertion about the absence of bias, or that measurement should be impartial (i.e., not provide an unfair advantage or disadvantage), across groups of test takers. In more general-purposes language testing, a test taker's background knowledge is not typically considered relevant to the…
Descriptors: Testing, Language Tests, Test Bias, English for Special Purposes
Blaženka Divjak; Petra Žugec; Katarina Pažur Anicic – International Journal of Mathematical Education in Science and Technology, 2024
Assessment is among the inevitable components of a curriculum and directs students' learning. E-assessment, as prepared and administered with the use of ICT, provides opportunities to make the process easier in some aspects, but also brings certain challenges. This paper presents an e-assessment framework from a student perspective. Our study…
Descriptors: Student Evaluation, Computer Assisted Testing, Evaluation Methods, Student Attitudes
Carly Steele; Graeme Gower; Tetiana Bogachenko – Australian Journal of Education, 2024
In this article, we argue that current assessment practices in higher education require urgent examination and should be re-imagined in culturally responsive ways to ensure fairness for all. From sociocultural and social justice perspectives, we highlight examples of cultural and linguistic bias in assessment that disadvantages many First Nations…
Descriptors: Culturally Relevant Education, Indigenous Populations, College Students, Student Evaluation
Wuttke, Eveline; Siegfried, Christin; Aprea, Carmela – Empirical Research in Vocational Education and Training, 2020
Due to current trends in society and economy, financial literacy is often considered as an important twenty-first century skill. However, regardless of the postulated relevance, studies suggest that financial illiteracy seems to be a widespread phenomenon in the population of many nations. Some studies also show that some groups perform…
Descriptors: Money Management, Multiple Literacies, Situational Tests, Test Bias
Amrein-Beardsley, Audrey; Geiger, Tray – SAGE Open, 2020
The Education Value-Added Assessment System (EVAAS), the value-added model (VAM) sold by the international business analytics software company SAS Institute Inc., is advertised as offering "precise, reliable and unbiased results that go far beyond what other simplistic [value-added] models found in the market today can provide." In this…
Descriptors: Value Added Models, Test Validity, Test Reliability, Test Bias
Leighton, Jacqueline P.; Lehman, Blair – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Jacqueline Leighton and Dr. Blair Lehman review differences between think-aloud interviews to measure problem-solving processes and cognitive labs to measure comprehension processes. Learners are introduced to historical, theoretical, and procedural differences between these methods and how to use and analyze…
Descriptors: Protocol Analysis, Interviews, Problem Solving, Cognitive Processes
Cuellar, Edwin; Partchev, Ivailo; Zwitser, Robert; Bechger, Timo – Educational Assessment, Evaluation and Accountability, 2021
International large-scale assessment in education aims to compare educational achievement across many countries. Differences between countries in language, culture, and education give rise to differential item functioning (DIF). For many decades, DIF has been regarded as a nuisance and a threat to validity. In this paper, we take a different…
Descriptors: International Assessment, Academic Achievement, Test Bias, Achievement Tests

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