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Aoqi Li; Johan Hulleman; Jeremy M. Wolfe – Cognitive Research: Principles and Implications, 2024
In any visual search task in the lab or in the world, observers will make errors. Those errors can be categorized as "deterministic": If you miss this target in this display once, you will definitely miss it again. Alternatively, errors can be "stochastic", occurring randomly with some probability from trial to trial.…
Descriptors: Visual Perception, Visual Stimuli, Error Patterns, Probability
Ryan S. Baker; Stephen Hutt; Nigel Bosch; Jaclyn Ocumpaugh; Gautam Biswas; Luc Paquette; J. M. Alexandra Andres; Nidhi Nasiar; Anabil Munshi – Educational Technology Research and Development, 2024
In this paper, we propose a new method for selecting cases for in situ, immediate interview research: detector-driven classroom interviewing (DDCI). Published work in educational data mining and learning analytics has yielded highly scalable measures that can detect key aspects of student interaction with computer-based learning in close to…
Descriptors: Electronic Learning, Anxiety, Metacognition, Data Collection
Francesca Patterson; Melina A. Kunar – Cognitive Research: Principles and Implications, 2024
Computer Aided Detection (CAD) has been used to help readers find cancers in mammograms. Although these automated systems have been shown to help cancer detection when accurate, the presence of CAD also leads to an over-reliance effect where miss errors and false alarms increase when the CAD system fails. Previous research investigated CAD systems…
Descriptors: Cancer, Computer Use, Identification, Screening Tests
Po-Chun Huang; Ying-Hong Chan; Ching-Yu Yang; Hung-Yuan Chen; Yao-Chung Fan – IEEE Transactions on Learning Technologies, 2024
Question generation (QG) task plays a crucial role in adaptive learning. While significant QG performance advancements are reported, the existing QG studies are still far from practical usage. One point that needs strengthening is to consider the generation of question group, which remains untouched. For forming a question group, intrafactors…
Descriptors: Automation, Test Items, Computer Assisted Testing, Test Construction
Ebru Balta; Celal Deha Dogan – SAGE Open, 2024
As computer-based testing becomes more prevalent, the attention paid to response time (RT) in assessment practice and psychometric research correspondingly increases. This study explores the rate of Type I error in detecting preknowledge cheating behaviors, the power of the Kullback-Leibler (KL) divergence measure, and the L person fit statistic…
Descriptors: Cheating, Accuracy, Reaction Time, Computer Assisted Testing
Carlos Cinelli; Andrew Forney; Judea Pearl – Sociological Methods & Research, 2024
Many students of statistics and econometrics express frustration with the way a problem known as "bad control" is treated in the traditional literature. The issue arises when the addition of a variable to a regression equation produces an unintended discrepancy between the regression coefficient and the effect that the coefficient is…
Descriptors: Regression (Statistics), Robustness (Statistics), Error of Measurement, Testing Problems
Gagan Shergill – Communique, 2025
Although school psychologists often comment on examinee motivation in their reports, systematic evaluation of effort is not common practice. Empirical assessment of performance effort provides critical evidence for the validity of evaluations and will likely lead to more valid assessments, recommendations, and placements. This article focuses on…
Descriptors: Testing, Student Behavior, Student Motivation, Student Evaluation
Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
Stephanie S. Sheron; Kecia L. Addison – Montgomery County Public Schools, 2025
This memorandum provides information on Advanced Placement (AP) and International Baccalaureate (IB) course enrollment, exam participation, and exam performance during the 2023-2024 school year. During the 2023-2024 school year, 136 AP or IB courses were offered across high schools. Among the 25 comprehensive high schools, all offered AP courses,…
Descriptors: High School Students, Advanced Placement Programs, Course Selection (Students), Enrollment
Ken O'Connor; Matt Townsley – Phi Delta Kappan, 2025
Decisions about assessment are often built on myths about teacher professional judgment and subjectivity that prioritize standardized assessment over classroom assessment. Ken O'Connor and Matt Townsley discuss some of the most common myths and explain how to dispel them by developing clear guidelines in which teachers can exercise their judgment,…
Descriptors: Decision Making, Student Evaluation, Standardized Tests, Testing Problems
Glory Tobiason; Adrienne Lavine – Change: The Magazine of Higher Learning, 2025
Current methods for evaluating faculty teaching fall short, and one way to address this is through campus-wide initiatives that focus on change at the level of academic units. The complex context of higher education makes meaningful teaching evaluation difficult; in particular, four sobering realities of this context must be taken into account in…
Descriptors: Teacher Evaluation, Evaluation Methods, Testing Problems, Educational Change
Hample, Rachel – ProQuest LLC, 2022
Many institutions use placement tests as a method to assess students' readiness for college-level coursework. With the increased use of technology in testing, many institutions have transitioned placement test administration to an online format in an unproctored setting. While unproctored placement tests may provide financial and logistical…
Descriptors: Supervision, Mathematics Tests, Placement Tests, Computer Assisted Testing
Carol Eckerly; Yue Jia; Paul Jewsbury – ETS Research Report Series, 2022
Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Scoring
Kim, Ahyoung Alicia; Yumsek, Meltem; Kemp, Jason A.; Chapman, Mark; Cook, H. Gary – Language Testing, 2023
English learners (ELs) comprise approximately 10% of kindergarten to Grade 12 students in US public schools, with about 15% of ELs identified as having disabilities. English language proficiency (ELP) assessments must adhere to universal design principles and incorporate universal tools, designed to increase accessibility for all ELs, including…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Students with Disabilities
Xu, Lingling; Wang, Shiyu; Cai, Yan; Tu, Dongbo – Journal of Educational Measurement, 2021
Designing a multidimensional adaptive test (M-MST) based on a multidimensional item response theory (MIRT) model is critical to make full use of the advantages of both MST and MIRT in implementing multidimensional assessments. This study proposed two types of automated test assembly (ATA) algorithms and one set of routing rules that can facilitate…
Descriptors: Item Response Theory, Adaptive Testing, Automation, Test Construction