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Prathiba Natesan Batley; Erica B. McClure; Brandy Brewer; Ateka A. Contractor; Nicholas John Batley; Larry Vernon Hedges; Stephanie Chin – Grantee Submission, 2023
N-of-1 trials, a special case of Single Case Experimental Designs (SCEDs), are prominent in clinical medical research and specifically psychiatry due to the growing significance of precision/personalized medicine. It is imperative that these clinical trials be conducted, and their data analyzed, using the highest standards to guard against threats…
Descriptors: Medical Research, Research Design, Data Analysis, Effect Size
Robert B. Olsen; Larry L. Orr; Stephen H. Bell; Elizabeth Petraglia; Elena Badillo-Goicoechea; Atsushi Miyaoka; Elizabeth A. Stuart – Journal of Research on Educational Effectiveness, 2024
Multi-site randomized controlled trials (RCTs) provide unbiased estimates of the average impact in the study sample. However, their ability to accurately predict the impact for individual sites outside the study sample, to inform local policy decisions, is largely unknown. To extend prior research on this question, we analyzed six multi-site RCTs…
Descriptors: Accuracy, Predictor Variables, Randomized Controlled Trials, Regression (Statistics)
Sandy P. Hinkley – Update: Applications of Research in Music Education, 2024
Music educators typically use a variety of strategies to teach their subject matter, one core practice of which is modeling. Vocal modeling is a type of aural demonstration, with uses ranging from pitch matching and song instruction to vocal tone building and musicianship development. In early studies, researchers primarily studied the effects of…
Descriptors: Music Education, Singing, Teaching Methods, Modeling (Psychology)
Yasar C. Kakdas; Sinan Kockara; Tansel Halic; Doga Demirel – IEEE Transactions on Learning Technologies, 2024
This article presents a 3-D medical simulation that employs reinforcement learning (RL) and interactive RL (IRL) to teach and assess the procedure of donning and doffing personal protective equipment (PPE). The simulation is motivated by the need for effective, safe, and remote training techniques in medicine, particularly in light of the COVID-19…
Descriptors: Medical Education, Error Patterns, Error Correction, Reinforcement
Emily R. Forcht; Ethan R. Van Norman – Psychology in the Schools, 2024
The present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end-of-year proficiency in reading and math. Participants included 13,009 students in Grades 3-8 who had at least one fall screening score and end-of-year…
Descriptors: Computer Assisted Testing, Adaptive Testing, Diagnostic Tests, Screening Tests
Janneke van de Pol; Sophie Oudman – Metacognition and Learning, 2024
Teachers' ability to accurately judge students' monitoring skills is important as it enables teachers to help students becoming better self-regulated learners. Yet, there is hardly any research on this crucial teacher skill and a framework is missing. We present a novel conceptual and methodological framework integrating teachers' judgments of…
Descriptors: Secondary School Teachers, Self Evaluation (Individuals), Student Evaluation, Cues
Saeid Sarabi Asl; Mojgan Rashtchi; Ghafour Rezaie – Asian-Pacific Journal of Second and Foreign Language Education, 2024
Dynamic assessment has been proven to effectively promote EFL learners' speaking proficiency, but its implementation in teaching speaking skills has been limited. One of the main reasons is that, thus far, very few studies have scrutinized the impacts of its two main models, interactionist and interventionist, on the speaking sub-skills of EFL…
Descriptors: Intervention, Evaluation Methods, Models, English (Second Language)
Lin Zhong – Interactive Learning Environments, 2024
Being efficient learners is important in the modern workforce, but improved performance and cognitive load do not imply that students are efficient learners. This study investigated the effectiveness of a personalized role-playing game in students' learning efficiency (LE) and mental efficiency. Results showed that students in the personalized…
Descriptors: Role Playing, Game Based Learning, Program Effectiveness, Learning Processes
Ana Lidia Franzoni Velázquez; Esperanza Huerta; Scott Jensen – Discover Education, 2024
This two-part study describes a learning exercise including a video and a worksheet designed to raise students' awareness of the need to evaluate the completeness of references generated by ChatGPT. The first part of the study assesses the completeness and relevance of academic references generated by ChatGPT using four prompts and three versions…
Descriptors: Artificial Intelligence, Students, Instructional Material Evaluation, Computer Assisted Instruction
James Mahshie; Cynthia Core; Michael D. Larsen – International Journal of Language & Communication Disorders, 2024
Background: Despite the ability of cochlear implants (CIs) to provide children with access to speech, there is considerable variability in spoken language outcomes. Research aimed at identifying factors influencing speech production accuracy is needed. Aims: To characterize the consonant production accuracy of children with cochlear implants…
Descriptors: Influences, Phonemes, Accuracy, Children
Teymoor Khosravi; Zainab M. Al Sudani; Morteza Oladnabi – Innovations in Education and Teaching International, 2024
OpenAI's ChatGPT, is a conversational chatbot that uses Generative Pre-trained Transformer or GPT language model to mimic human-like responses. Here we evaluated its performance in providing responses to genetics questions across five different tasks including solid genetic basics, identifying inheritance pattern based on described pedigrees,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Genetics
Andrea Zanellati; Stefano Pio Zingaro; Maurizio Gabbrielli – IEEE Transactions on Learning Technologies, 2024
Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…
Descriptors: Dropouts, Dropout Characteristics, Potential Dropouts, Artificial Intelligence
Donna Chu; Frankie Ho Chun Wong – Journal of Education, 2024
This paper discusses the factors affecting the behaviours for coping with fake news among young people. The data were collected from a survey conducted in late 2019, which sampled 2112 secondary school students from 21 partnering schools. This study aims to understand the opinions and behaviours of teenagers towards disinformation when fake news…
Descriptors: Foreign Countries, Secondary School Students, Student Behavior, News Media
Marsela Thanasi-Boçe; Julian Hoxha – Education and Information Technologies, 2024
Entrepreneurship education has evolved to meet the demands of a dynamic business environment, necessitating innovative teaching methods to prepare entrepreneurs for market uncertainties. Large Language Models (LLMs) like the Generative Pre-trained Transformer 4 (GPT-4), recognized for their exceptional performance on public datasets, are examined…
Descriptors: Entrepreneurship, Business Administration Education, Technology Integration, Artificial Intelligence
Shaojie Wang; Won-Chan Lee; Minqiang Zhang; Lixin Yuan – Applied Measurement in Education, 2024
To reduce the impact of parameter estimation errors on IRT linking results, recent work introduced two information-weighted characteristic curve methods for dichotomous items. These two methods showed outstanding performance in both simulation and pseudo-form pseudo-group analysis. The current study expands upon the concept of information…
Descriptors: Item Response Theory, Test Format, Test Length, Error of Measurement

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