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Jessica R. Toste; Sally K. Fluhler; Emily A. Farris; Brennan W. Chandler – Intervention in School and Clinic, 2025
Students with reading disabilities require instruction and intensive intervention targeted to their current learning needs. Through data-based instruction, educators can monitor student's performance and make adjustments to instruction to better address student needs using both progress monitoring and diagnostic assessment. This article provides…
Descriptors: Reading Fluency, Reading Difficulties, Students with Disabilities, Intervention
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
Chi Hong Leung; Winslet Ting Yan Chan – Asian Journal of Contemporary Education, 2025
This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Error Patterns
Han, Suhwa; Kang, Hyeon-Ah – Journal of Educational Measurement, 2023
The study presents multivariate sequential monitoring procedures for examining test-taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test-taking behavior. The study in particular proposes three schemes to track different…
Descriptors: Test Wiseness, Student Behavior, Item Response Theory, Computer Assisted Testing
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
Gilhooly, Ken J.; Sleeman, Derek H. – Applied Cognitive Psychology, 2022
Inconsistency in real-world judgments can cause random unfairness, injustice and misallocation of resources. In their recent monograph Kahneman, Sibony, and Sunstein (2021) analyse judgment inconsistency or "Noise," examine its sources and propose remedies. In this commentary on Kahneman et al., we reflect on the major concepts (such as…
Descriptors: Decision Making, Bias, Error Patterns, Thinking Skills
Guzzo, Natália Brambatti – Journal of Child Language, 2022
I investigate the acquisition of affrication in Québec French (QF), where affricates are in complementary distribution with coronal stops, being realized before high front vowels and glides. Previous research on other languages shows that affricates are acquired before branching onsets, which supports the idea that complexity at the level of the…
Descriptors: Articulation (Speech), French, Foreign Countries, Language Research
Babcock, Ben; Marks, Peter E. L.; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N. – International Journal of Behavioral Development, 2022
A wide variety of methodological choices and situations can affect the quality of peer nomination measurements but have not received adequate study. This article begins by focusing on systematic nominator missingness as an example of one such situation. We reanalyzed findings from a recent study by Bukowski, Dirks, Commisso, Velàsquez, and Lopez…
Descriptors: Research Methodology, Peer Relationship, Statistical Analysis, Error Patterns
Biggs, Adam T. – Applied Cognitive Psychology, 2022
Inhibitory control has been identified as a prominent factor in shoot/don't-shoot errors. Although emerging evidence continues to support this relationship, there is critical nuance and depth that can significantly alter this connection between a cognitive capability and a critical real-world application. For example, presenting shoot/don't-shoot…
Descriptors: Inhibition, Self Control, Decision Making, Cognitive Processes
Shari Cavicchi; Abdulaziz Abubshait; Giulia Siri; Magda Mustile; Francesca Ciardo – Cognitive Research: Principles and Implications, 2025
Cognitive load occurs when the demands of a task surpass the available processing capacity, straining mental resources and potentially impairing performance efficiency, such as increasing the number of errors in a task. Owing to its ubiquity in real-world scenarios, the existence of offloading strategies to reduce cognitive load is not new to…
Descriptors: Robotics, Psychological Patterns, Cognitive Processes, Computer Software
Pham Sy Nam; Ngoc-Giang Nguyen; Hoa Anh Tuong; Ben Haas; Zsolt Lavicza; Yves Kreis – International Journal for Technology in Mathematics Education, 2023
Problem-based learning puts students in situations that suggest problems without providing instructions and available knowledge. Therefore, when using problem-based learning, students need to be flexible, self-disciplined, active and self-occupied with knowledge and turn the knowledge the teacher intends to impart into their knowledge. For locus…
Descriptors: Computer Software, Mathematics Instruction, Teaching Methods, Problem Based Learning
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
Lim, Hwanggyu; Choe, Edison M. – Journal of Educational Measurement, 2023
The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIF[subscript R] statistic both as an index for detecting uniform DIF of…
Descriptors: Test Items, Computer Assisted Testing, Item Response Theory, Adaptive Testing
Marie Alina Yeo; Benjamin Luke Moorhouse; Yuwei Wan – TESL-EJ, 2025
This paper looks at Google's NotebookLM, an AI-powered research assistant tool that can represent dense academic content in a range of output modes, like FAQs, timelines, study guides, and, most uniquely, as "Deep Dive" discussions. The discussions mimic a talk-show, where two AI-hosts unpack complex ideas from reading or audio texts,…
Descriptors: Artificial Intelligence, Research Tools, Technology Uses in Education, Computer Mediated Communication
Eglington, Luke G.; Pavlik, Philip I., Jr. – International Journal of Artificial Intelligence in Education, 2023
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences