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Stacey von Winckelmann – ProQuest LLC, 2023
The research problem addressed in this study is that racial bias programmed into predictive algorithm recommendations negatively impacts students in historically underrepresented groups. The purpose of this qualitative descriptive study was to explore the perception of algorithm accuracy among data professionals in higher education and explore the…
Descriptors: Prediction, Algorithms, Racism, Accuracy
Stacey Lynn von Winckelmann – Information and Learning Sciences, 2023
Purpose: This study aims to explore the perception of algorithm accuracy among data professionals in higher education. Design/methodology/approach: Social justice theory guided the qualitative descriptive study and emphasized four principles: access, participation, equity and human rights. Data collection included eight online open-ended…
Descriptors: Prediction, Algorithms, Racism, Accuracy
Debora Weber-Wulff; Alla Anohina-Naumeca; Sonja Bjelobaba; Tomáš Foltýnek; Jean Guerrero-Dib; Olumide Popoola; Petr Šigut; Lorna Waddington – International Journal for Educational Integrity, 2023
Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching for solutions to detect such content. The paper examines the general functionality of detection tools for…
Descriptors: Artificial Intelligence, Identification, Man Machine Systems, Accuracy
Porter, Cody Normitta; Taylor, Rachel; Harvey, Adam Charles – Applied Cognitive Psychology, 2022
This study investigates the Asymmetric Information Management (AIM) technique's ability to detect fraudulent insurance claims submitted online. The AIM instructions inform claimants that, inter alia, more detailed statements are easier to accurately classify as genuine or fabricated. To test this, truth tellers (n = 55) provided an honest…
Descriptors: Information Management, Identification, Deception, Insurance
Thorley, Craig; Acton, Benjamin; Armstrong, Jesse; Ford, Shanade; Gundry, Margaret – Cognitive Research: Principles and Implications, 2022
This study examined whether our ability to accurately estimate unfamiliar faces' ages declines when they are wearing sunglasses or surgical-style face masks and whether these disguises make it harder to later recognise those faces when undisguised. In theory, both disguises should harm age estimation accuracy and later face recognition as they…
Descriptors: Age, Accuracy, Recognition (Psychology), Human Body
Gorney, Kylie; Wollack, James A. – Journal of Educational Measurement, 2022
Detection methods for item preknowledge are often evaluated in simulation studies where models are used to generate the data. To ensure the reliability of such methods, it is crucial that these models are able to accurately represent situations that are encountered in practice. The purpose of this article is to provide a critical analysis of…
Descriptors: Prior Learning, Simulation, Models, Reaction Time
Atcha, Haroon – Community College Journal of Research and Practice, 2022
Proper institutional planning requires accurate enrollment forecasts. This is especially true in the community college context given open enrollment policies and reliance on public funds. Despite the importance of this task, enrollment forecasts are relatively disconnected from theoretical advances in the study of retention and enrollment. In this…
Descriptors: Enrollment Projections, Models, Community Colleges, Educational Theories
Sarah C. Creel – Child Development, 2025
How does one assess developmental change when the measures themselves change with development? Most developmental studies of word learning use either looking (infants) or pointing (preschoolers and older). With little empirical evidence of the relationship between the two measures, developmental change is difficult to assess. This paper analyzes…
Descriptors: Preschool Children, Vocabulary Development, Language Acquisition, Accuracy
Harikesh Singh; Li-Minn Ang; Dipak Paudyal; Mauricio Acuna; Prashant Kumar Srivastava; Sanjeev Kumar Srivastava – Technology, Knowledge and Learning, 2025
Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…
Descriptors: Artificial Intelligence, Computer Software, Computer Simulation, Prediction
Adam J. Lekwa; Joseph Deegan; Christian Mathews – Assessment for Effective Intervention, 2025
Drawing on cognitive theory in reading comprehension, Sentence Order Fluency (SOF) is proposed as a method for monitoring progress in reading comprehension. In this article, we present results of a pilot study on SOF conducted between April and June 2023, with a group of 119 students in Grades 4, 5, and 6 in a charter school in the mid-Atlantic…
Descriptors: Progress Monitoring, Reading Comprehension, Elementary School Students, Grade 4
Misun Yi – Journal of Applied Research in Intellectual Disabilities, 2025
Background: Individuals with intellectual disabilities are amongst the groups most vulnerable to sexual crimes. However, their limited cognitive abilities can make it challenging to obtain detailed statements from victims during investigative interviews. This study examined whether practising answering open-ended questions early in the interview…
Descriptors: Adults, Intellectual Disability, Children, Sexual Abuse
Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
Bassil M. Mashaqba; Khalid Al-Shdifat; Anas I. Al huneety; Mohammad Nour Abu Guba; Hadeel Abdelhadi – International Journal of Bilingual Education and Bilingualism, 2025
This study investigated phonological whole-word measures in bilingual Arabic-English speakers to explore how the target approximations influence children's phonological development. To this end, fifteen bilingual Arabic-English speakers and nine monolingual Arabic-speaking children aged 36-48 months (mean = 42) participated in a parent-child…
Descriptors: Phonology, Child Language, Bilingualism, Arabic
Sean Guo; Briony Swire-Thompson; Xiaoqing Hu – Cognitive Research: Principles and Implications, 2025
Images generated using artificial intelligence (AI) have become increasingly realistic, sparking discussions and fears about an impending "infodemic" where we can no longer trust what we see on the internet. In this preregistered study, we examine whether providing specific media literacy tips about how to spot AI-generated images can…
Descriptors: Media Literacy, Artificial Intelligence, Technology Uses in Education, Visual Stimuli
Munish Saini; Eshan Sengupta; Naman Sharma – Education and Information Technologies, 2025
To be an effective teacher, one must possess strong learning abilities. Developing lesson planning, pursuing learning objectives, and assessing post-lesson accomplishments all these depend on reflection and ongoing learning. As education is context-specific, the iterative process of preparing, reflecting, and improving is what makes teaching…
Descriptors: Artificial Intelligence, Technology Uses in Education, Nonverbal Communication, Feedback (Response)

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