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Matthew C. Lambert; Michael H. Epstein; Douglas Cullinan – Journal of Psychoeducational Assessment, 2025
Research and policy reports estimate that 10%-40% of U.S. children and adolescents currently have or very recently have had at least one significant mental health condition. Students who exhibit substantial behavior and emotional problems in school often show less severe problems when younger. Screening for less severe problems at younger ages can…
Descriptors: Elementary School Students, Screening Tests, Emotional Disturbances, Test Validity
Schindler, Simon; Wagner, Laura K.; Reinhard, Marc-André; Ruhara, Nico; Pfattheicher, Stefan; Nitschke, Joachim – Applied Cognitive Psychology, 2021
The present research examined lie detection abilities of a rarely investigated group, namely offenders. Results of the studies conducted thus far indicated a better performance of offenders compared to non-offenders when discriminating between true and false messages. With two new studies, we aimed at replicating offenders' superior abilities in…
Descriptors: Deception, Identification, Criminals, Males
Ilagan, Michael John; Falk, Carl F. – Educational and Psychological Measurement, 2023
Administering Likert-type questionnaires to online samples risks contamination of the data by malicious computer-generated random responses, also known as bots. Although nonresponsivity indices (NRIs) such as person-total correlations or Mahalanobis distance have shown great promise to detect bots, universal cutoff values are elusive. An initial…
Descriptors: Likert Scales, Questionnaires, Artificial Intelligence, Identification
Balqis Albreiki; Tetiana Habuza; Nishi Palakkal; Nazar Zaki – Education and Information Technologies, 2024
The nature of education has been transformed by technological advances and online learning platforms, providing educational institutions with more options than ever to thrive in a complex and competitive environment. However, they still face challenges such as academic underachievement, graduation delays, and student dropouts. Fortunately, by…
Descriptors: Multivariate Analysis, Graphs, Identification, At Risk Students
Xuandong Zhao – ProQuest LLC, 2024
The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…
Descriptors: Computational Linguistics, Intellectual Property, Artificial Intelligence, Productivity
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Sedat Sen; Allan S. Cohen – Educational and Psychological Measurement, 2024
A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…
Descriptors: Goodness of Fit, Item Response Theory, Sample Size, Classification
Das, Syaamantak; Mandal, Shyamal Kumar Das; Basu, Anupam – Contemporary Educational Technology, 2020
Cognitive learning complexity identification of assessment questions is an essential task in the domain of education, as it helps both the teacher and the learner to discover the thinking process required to answer a given question. Bloom's Taxonomy cognitive levels are considered as a benchmark standard for the classification of cognitive…
Descriptors: Classification, Difficulty Level, Test Items, Identification
Zeyu Xu – AERA Online Paper Repository, 2024
Children's math performance is strongly correlated with later life outcomes, but early gaps in math skills are stubbornly difficult to close. It is therefore important to identify student math needs early. Using Grade 1-3 student records from Kentucky public schools, the study finds that typically recommended cut scores for widely used early grade…
Descriptors: Mathematics Skills, Mathematics Achievement, Mathematics Education, Elementary School Mathematics
Shahzad, Areeba; Wali, Aamir – Education and Information Technologies, 2022
Checking essays written by students is a very time consuming task. Besides spellings and grammar, they also need to be evaluated on their semantic content such as cohesion, coherence, etc. In this study we focus on one such aspect of semantic content which is the topic of the essay. Putting it formally, given a prompt or essay-statement and an…
Descriptors: Computer Uses in Education, Essays, Writing Evaluation, Semantics
Stanley, C.; Petscher, Y.; Pentimonti, J. – National Center on Improving Literacy, 2019
Classification accuracy is a key characteristic of screening tools. A goal in classification accuracy is to correctly identify issues that result in a later problem and situations in which the scores identify issues that do not result in a later problem.
Descriptors: Screening Tests, Identification, Classification, Accuracy
Cantin-Garside, Kristine D.; Kong, Zhenyu; White, Susan W.; Antezana, Ligia; Kim, Sunwook; Nussbaum, Maury A. – Journal of Autism and Developmental Disorders, 2020
Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning methods for detecting and distinguishing diverse SIB types. SIB episodes were captured with body-worn…
Descriptors: Self Destructive Behavior, Autism, Pervasive Developmental Disorders, Identification
Carioti, Desiré; Stucchi, Natale Adolfo; Toneatto, Carlo; Masia, Marta Franca; Del Monte, Milena; Stefanelli, Silvia; Travellini, Simona; Marcelli, Antonella; Tettamanti, Marco; Vernice, Mirta; Guasti, Maria Teresa; Berlingeri, Manuela – Annals of Dyslexia, 2023
In this study, we validated the "ReadFree tool", a computerised battery of 12 visual and auditory tasks developed to identify poor readers also in minority-language children (MLC). We tested the task-specific discriminant power on 142 Italian-monolingual participants (8-13 years old) divided into monolingual poor readers (N = 37) and…
Descriptors: Language Minorities, Task Analysis, Italian, Monolingualism
Stanley, Lauren H. K. – ProQuest LLC, 2022
Early childhood traumatic experiences place children at-risk for social, emotional, and behavioral impairments that contribute to poor educational outcomes. There is an increasing awareness that children with early traumatic exposure may need supplemental supports for academic success. These supports may be presented in the form of…
Descriptors: Young Children, Kindergarten, Trauma, Early Experience
Christopher E. Gomez; Marcelo O. Sztainberg; Rachel E. Trana – International Journal of Bullying Prevention, 2022
Cyberbullying is the use of digital communication tools and spaces to inflict physical, mental, or emotional distress. This serious form of aggression is frequently targeted at, but not limited to, vulnerable populations. A common problem when creating machine learning models to identify cyberbullying is the availability of accurately annotated,…
Descriptors: Video Technology, Computer Software, Computer Mediated Communication, Bullying

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