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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
Bahaa Madi Tarabya; Samer Andria; Asaid Khateb – Annals of Dyslexia, 2025
The current study sought to examine the existence of reading subtypes based on specific accuracy and rate criteria in dyslexia among a non-clinical sample of 120 Arabic-speaking University students and to characterize their reading-related and linguistic skills. For this aim, we relied on a conventional practice in reading disability literature…
Descriptors: Arabic, College Students, Accuracy, Dyslexia
Senay Kocakoyun Aydogan; Turgut Pura; Fatih Bingül – Malaysian Online Journal of Educational Technology, 2024
In every culture and era, education is considered the most fundamental reality and rule that societies prioritize and deem essential. Throughout the process spanning thousands of years, from the emergence of writing to the present day, education has undergone various forms and formats of change. Education has been a continuous guide for shaping,…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
Huan Liu – ProQuest LLC, 2024
In many large-scale testing programs, examinees are frequently categorized into different performance levels. These classifications are then used to make high-stakes decisions about examinees in contexts such as in licensure, certification, and educational assessments. Numerous approaches to estimating the consistency and accuracy of this…
Descriptors: Classification, Accuracy, Item Response Theory, Decision Making
Abdullah Mana Alfarwan – ProQuest LLC, 2024
This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…
Descriptors: Regression (Statistics), Decision Making, Prediction, Sample Size
Setzer, J. Carl; Cheng, Ying; Liu, Cheng – Journal of Educational Measurement, 2023
Test scores are often used to make decisions about examinees, such as in licensure and certification testing, as well as in many educational contexts. In some cases, these decisions are based upon compensatory scores, such as those from multiple sections or components of an exam. Classification accuracy and classification consistency are two…
Descriptors: Classification, Accuracy, Psychometrics, Scores
Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval
Rumeysa Demir; Metin Demir – Educational Process: International Journal, 2025
Background/purpose: This study aims to reveal in detail the extent to which the variables in The Primary and Secondary Education Institutions Scholarship Examination (PSEISE) predict the success of students on the scholarship exam with the help of artificial neural networks (ANN). In addition, in light of the findings obtained as a result of the…
Descriptors: Elementary Secondary Education, Foreign Countries, Artificial Intelligence, Computer Software
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
Rios, Joseph A. – Applied Measurement in Education, 2022
Testing programs are confronted with the decision of whether to report individual scores for examinees that have engaged in rapid guessing (RG). As noted by the "Standards for Educational and Psychological Testing," this decision should be based on a documented criterion that determines score exclusion. To this end, a number of heuristic…
Descriptors: Testing, Guessing (Tests), Academic Ability, Scores
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
Newell, Kirsten W.; Kember, Jessie; Zinn, Gesa – Assessment for Effective Intervention, 2022
This brief report summarizes the development and psychometric properties of German reading fluency passages as compared to English reading fluency passages for immersion language learners. Results indicated that scores from German language reading fluency passages alone were (a) somewhat less reliable than scores from English publisher-developed…
Descriptors: German, Reading Fluency, Oral Reading, Immersion Programs
Marzieh Haghayeghi; Ali Moghadamzadeh; Hamdollah Ravand; Mohamad Javadipour; Hossein Kareshki – Journal of Psychoeducational Assessment, 2025
This study aimed to address the need for a comprehensive assessment tool to evaluate the mathematical abilities of first-grade students through cognitive diagnostic assessment (CDA). The primary challenge involved in this endeavor was to delineate the specific cognitive skills and sub-skills pertinent to first-grade mathematics (FG-M) and to…
Descriptors: Test Construction, Cognitive Measurement, Check Lists, Mathematics Tests
Kim, Stella Y.; Lee, Won-Chan – Journal of Educational Measurement, 2020
The current study aims to evaluate the performance of three non-IRT procedures (i.e., normal approximation, Livingston-Lewis, and compound multinomial) for estimating classification indices when the observed score distribution shows atypical patterns: (a) bimodality, (b) structural (i.e., systematic) bumpiness, or (c) structural zeros (i.e., no…
Descriptors: Classification, Accuracy, Scores, Cutting Scores
Kayla V. Campaña; Benjamin G. Solomon – Assessment for Effective Intervention, 2025
The purpose of this study was to compare the classification accuracy of data produced by the previous year's end-of-year New York state assessment, a computer-adaptive diagnostic assessment ("i-Ready"), and the gating combination of both assessments to predict the rate of students passing the following year's end-of-year state assessment…
Descriptors: Accuracy, Classification, Diagnostic Tests, Adaptive Testing