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Direct linkSujin Oh – ProQuest LLC, 2024
The revised Speech Learning Model (SLM-r) postulates that learners with more precisely defined categories in their native language (L1) exhibit greater proficiency in acquiring sounds in a second language (L2). Despite its recent emergence, empirical studies validating this hypothesis remain scarce. This study aims to investigate the predictive…
Descriptors: Native Language, Second Language Learning, Speech Communication, Individual Differences
Peer reviewedLeah Ward; Kamila Polišenská; Colin Bannard – Journal of Speech, Language, and Hearing Research, 2024
Purpose: This systematic review and multilevel meta-analysis examines the accuracy of sentence repetition (SR) tasks in distinguishing between typically developing (TD) children and children with developmental language disorder (DLD). It explores variation in the way that SR tasks are administered and/or evaluated and examines whether variability…
Descriptors: Children, Language Impairments, Repetition, Sentences
McCluskey, Sydne – ProQuest LLC, 2023
Rater comparison analysis is commonly necessary in the social sciences. Conventional approaches to the problem generally focus on calculation of agreement statistics, which provide useful but incomplete information about rater agreement. Importantly, one-number agreement statistics give no indication regarding the nature of disagreements, nor do…
Descriptors: Bayesian Statistics, Structural Equation Models, Interrater Reliability, Beliefs
Burton, Olivia R.; Bodner, Glen E.; Williamson, Paul; Arnold, Michelle M. – Metacognition and Learning, 2023
Meta-reasoning requires monitoring and controlling one's reasoning processes, and it often begins with an assessment of problem solvability. We explored whether "Judgments of Solvability (JOS)" for solvable and unsolvable anagrams discriminate and predict later problem-solving outcomes once anagrams solved during the JOS task are…
Descriptors: Accuracy, Prediction, Problem Solving, Thinking Skills
Kim, Rae Yeong; Yoo, Yun Joo – Journal of Educational Measurement, 2023
In cognitive diagnostic models (CDMs), a set of fine-grained attributes is required to characterize complex problem solving and provide detailed diagnostic information about an examinee. However, it is challenging to ensure reliable estimation and control computational complexity when The test aims to identify the examinee's attribute profile in a…
Descriptors: Models, Diagnostic Tests, Adaptive Testing, Accuracy
Kataoka, Yuki; Taito, Shunsuke; Yamamoto, Norio; So, Ryuhei; Tsutsumi, Yusuke; Anan, Keisuke; Banno, Masahiro; Tsujimoto, Yasushi; Wada, Yoshitaka; Sagami, Shintaro; Tsujimoto, Hiraku; Nihashi, Takashi; Takeuchi, Motoki; Terasawa, Teruhiko; Iguchi, Masahiro; Kumasawa, Junji; Ichikawa, Takumi; Furukawa, Ryuki; Yamabe, Jun; Furukawa, Toshi A. – Research Synthesis Methods, 2023
There are currently no abstract classifiers, which can be used for new diagnostic test accuracy (DTA) systematic reviews to select primary DTA study abstracts from database searches. Our goal was to develop machine-learning-based abstract classifiers for new DTA systematic reviews through an open competition. We prepared a dataset of abstracts…
Descriptors: Competition, Classification, Diagnostic Tests, Accuracy
Victoria L. Lowell; Lucía Ureña-Rodríguez – SAGE Open, 2023
Globally, educators and researchers use different terms to describe instructors' approaches when presenting instructional material in formal and informal settings. Terms commonly used to describe instructional approaches include teaching/instructional strategy, teaching/instructional method, and teaching/instructional technique. Although…
Descriptors: Taxonomy, Teaching Methods, Educational Strategies, Standards
Senthil Kumaran, V.; Malar, B. – Interactive Learning Environments, 2023
Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…
Descriptors: Electronic Learning, Dropouts, Accuracy, Classification
Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Download full textKristy Plander; Renee Hathaway; Deb Maeder – Online Learning, 2025
The purpose of this explanatory sequential mixed methods study was to examine faculty perceptions of distance course quality review feedback at a small healthcare-focused college in the United States. The Examining the Evaluator Feedback Survey tool was adapted and used to determine faculty perceptions (N=16) of five key aspects of reviewer…
Descriptors: Teacher Attitudes, Distance Education, College Faculty, Value Judgment
Wu Xu; Zhang Wei; Peng Yan – European Journal of Education, 2025
This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…
Descriptors: Artificial Intelligence, Natural Language Processing, Engineering Education, Majors (Students)
Sheng Bi; Zeyi Miao; Qizhi Min – IEEE Transactions on Learning Technologies, 2025
The objective of question generation from knowledge graphs (KGQG) is to create coherent and answerable questions from a given subgraph and a specified answer entity. KGQG has garnered significant attention due to its pivotal role in enhancing online education. Encoder-decoder architectures have advanced traditional KGQG approaches. However, these…
Descriptors: Grammar, Models, Questioning Techniques, Graphs
Anna Dailey; Meghan Riling – Mathematics Teacher: Learning and Teaching PK-12, 2025
Mathematics teachers have been documented as thinking of precision as a black-and-white issue that should be judged based on external expectations (Otten et al., 2019), suggesting that matters of precision align primarily with approaches to mathematics instruction that prioritize accuracy and speed. How can teachers who also value creativity and…
Descriptors: Aesthetics, Art, Islamic Culture, Geometry
Aiman Mohammad Freihat; Omar Saleh Bani Yassin – Educational Process: International Journal, 2025
Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…
Descriptors: Accuracy, Computation, Multiple Choice Tests, Test Items
Hanshu Zhang; Ran Zhou; Cheng-You Cheng; Sheng-Hsu Huang; Ming-Hui Cheng; Cheng-Ta Yang – Cognitive Research: Principles and Implications, 2025
Although it is commonly believed that automation aids human decision-making, conflicting evidence raises questions about whether individuals would gain greater advantages from automation in difficult tasks. Our study examines the combined influence of task difficulty and automation reliability on aided decision-making. We assessed decision…
Descriptors: Task Analysis, Difficulty Level, Decision Making, Automation
