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Laura E. Matzen; Zoe N. Gastelum; Breannan C. Howell; Kristin M. Divis; Mallory C. Stites – Cognitive Research: Principles and Implications, 2024
This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and…
Descriptors: Artificial Intelligence, Error Patterns, Decision Making, Models
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Lauren A. Mason; Abigail Miller; Gregory Hughes; Holly A. Taylor – Cognitive Research: Principles and Implications, 2025
False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error…
Descriptors: Error Correction, Error Patterns, Evaluation Methods, Visual Aids
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Julie Y. L. Chow; Jessica C. Lee; Peter F. Lovibond – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
People often rely on the covariation between events to infer causality. However, covariation between cues and outcomes may change over time. In the associative learning literature, extinction provides a model to study updating of causal beliefs when a previously established relationship no longer holds. Prediction error theories can explain both…
Descriptors: Beliefs, Learning Processes, Foreign Countries, Attribution Theory
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Alrik Thiem; Lusine Mkrtchyan – Field Methods, 2024
Qualitative comparative analysis (QCA) is an empirical research method that has gained some popularity in the social sciences. At the same time, the literature has long been convinced that QCA is prone to committing causal fallacies when confronted with non-causal data. More specifically, beyond a certain case-to-factor ratio, the method is…
Descriptors: Qualitative Research, Comparative Analysis, Research Methodology, Benchmarking
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Tsubasa Minematsu; Atsushi Shimada – International Association for Development of the Information Society, 2024
In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…
Descriptors: Educational Technology, Technology Uses in Education, Error Patterns, Sentences
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Cai, Zhiqiang; Marquart, Cody; Shaffer, David W. – International Educational Data Mining Society, 2022
Regular expression (regex) coding has advantages for text analysis. Humans are often able to quickly construct intelligible coding rules with high precision. That is, researchers can identify words and word patterns that correctly classify examples of a particular concept. And, it is often easy to identify false positives and improve the regex…
Descriptors: Coding, Classification, Artificial Intelligence, Engineering Education
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Kwaku Adu-Gyamfi; Kayla Chandler; Anthony Thompson – School Science and Mathematics, 2025
The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…
Descriptors: Algebra, Mathematics Instruction, Barriers, Cognitive Processes
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Ronit Shmallo; Adi Katz – Computer Science Education, 2024
Background and Context: Gender research shows that women are better at reading comprehension. Other studies indicate a lower tendency in women to choose STEM professions. Since data modeling requires reading skills and also belongs in the areas of information systems and computer science (STEM professions), these findings provoked our curiosity.…
Descriptors: Gender Differences, Transfer of Training, Databases, Models
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Morali, Hasibe Sevgi; Filiz, Ahsen – Journal of Pedagogical Research, 2023
Proof facilitates conceptual and meaningful learning in mathematics education rather than rote memorization. In this study, incorrect theorems and proofs are used to assess secondary school pre-service mathematics teachers' proof assessing skills. Using the case study method, the study is conducted on preservice mathematics teachers studying at…
Descriptors: Mathematical Models, Preservice Teachers, Mathematics Teachers, Mathematics Skills
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Julian M. Pine; Daniel Freudenthal; Fernand Gobet – Journal of Child Language, 2023
Verb-marking errors are a characteristic feature of the speech of typically-developing (TD) children and are particularly prevalent in the speech of children with Developmental Language Disorder (DLD). However, both the pattern of verb-marking error in TD children and the pattern of verb-marking deficit in DLD vary across languages and interact…
Descriptors: Developmental Disabilities, Language Impairments, Verbs, Error Patterns
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Puleng Motseki; Kakoma Luneta – African Journal of Research in Mathematics, Science and Technology Education, 2024
Among the problems identified at Technical and Vocational Education and Training (TVET) colleges, low achievement in mathematical subjects is the most prominent one. This paper documents a qualitative case study undertaken at TVET College in Gauteng with the purpose of exploring the National Certificate Vocational (NC(V)) Level 4 students' errors…
Descriptors: Vocational Education, Student Reaction, Low Achievement, Mathematics Achievement
Jennifer Kuo – ProQuest LLC, 2023
Paradigms with conflicting data patterns can be difficult to learn, resulting in acquisition error. In this dissertation, I look at how paradigms are reanalyzed over time to gain insight into the factors that influence morphophonological learning. Existing models of morphophonology (e.g. Hare & Elman 1995; Albright 2002b,a, 2010) predict…
Descriptors: Phonology, Malayo Polynesian Languages, Language Research, Grammar
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Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
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Lee, Sooyong; Han, Suhwa; Choi, Seung W. – Educational and Psychological Measurement, 2022
Response data containing an excessive number of zeros are referred to as zero-inflated data. When differential item functioning (DIF) detection is of interest, zero-inflation can attenuate DIF effects in the total sample and lead to underdetection of DIF items. The current study presents a DIF detection procedure for response data with excess…
Descriptors: Test Bias, Monte Carlo Methods, Simulation, Models
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Sideridis, Georgios D.; Jaffari, Fathima – Measurement and Evaluation in Counseling and Development, 2022
The present study describes an R function that implements six corrective procedures developed by Bartlett, Swain, and Yuan in the correction of 21 statistics associated with the omnibus Chi-square test, the residuals, or fit indices in confirmatory factor analysis (CFA) and structural equation modeling (SEM).
Descriptors: Statistical Analysis, Goodness of Fit, Factor Analysis, Structural Equation Models
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