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Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
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Matthew J. Madison; Seungwon Chung; Junok Kim; Laine P. Bradshaw – Grantee Submission, 2023
Recent developments have enabled the modeling of longitudinal assessment data in a diagnostic classification model (DCM) framework. These longitudinal DCMs were developed to provide measures of student growth on a discrete scale in the form of attribute mastery transitions, thereby supporting categorical and criterion-referenced interpretations of…
Descriptors: Models, Cognitive Measurement, Diagnostic Tests, Classification
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Sebbaq, Hanane; El Faddouli, Nour-eddine – International Review of Research in Open and Distributed Learning, 2022
The quality assurance of MOOCs focuses on improving their pedagogical quality. However, the tools that allow reflection on and assistance regarding the pedagogical aspects of MOOCs are limited. The pedagogical classification of MOOCs is a difficult task, given the variability of MOOCs' content, structure, and designs. Pedagogical researchers have…
Descriptors: MOOCs, Classification, Educational Objectives, Models
Mo, Yuji – ProQuest LLC, 2022
The research in this dissertation consists of two parts: An active learning algorithm for hierarchical labels and an embedding-based retrieval algorithm. In the first part, we present a new approach for learning hierarchically decomposable concepts. The approach learns a high-level classifier (e.g., location vs. non-location) by separately…
Descriptors: Active Learning, Algorithms, Classification, Models
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Alexia Micallef; Philip M. Newton – Teaching of Psychology, 2024
Background: Prior research suggests that the teaching of abstract concepts can be enhanced by the use of concrete examples, but there are few controlled studies. Objective: To replicate key findings from experiment one from Rawson et al. (2015). Method: Experiment participants studied definitions of abstract concepts from psychology, either with…
Descriptors: Teaching Methods, Instructional Effectiveness, Psychology, Concept Formation
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Sijia Huang; Seungwon Chung; Carl F. Falk – Journal of Educational Measurement, 2024
In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…
Descriptors: Response Style (Tests), Classification, Data, Models
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Cai, Zhiqiang; Marquart, Cody; Shaffer, David W. – International Educational Data Mining Society, 2022
Regular expression (regex) coding has advantages for text analysis. Humans are often able to quickly construct intelligible coding rules with high precision. That is, researchers can identify words and word patterns that correctly classify examples of a particular concept. And, it is often easy to identify false positives and improve the regex…
Descriptors: Coding, Classification, Artificial Intelligence, Engineering Education
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Kwaku Adu-Gyamfi; Kayla Chandler; Anthony Thompson – School Science and Mathematics, 2025
The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…
Descriptors: Algebra, Mathematics Instruction, Barriers, Cognitive Processes
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Holmes Finch, W. – Educational and Psychological Measurement, 2021
Social scientists are frequently interested in identifying latent subgroups within the population, based on a set of observed variables. One of the more common tools for this purpose is latent class analysis (LCA), which models a scenario involving k finite and mutually exclusive classes within the population. An alternative approach to this…
Descriptors: Group Membership, Classification, Sample Size, Models
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Ceylan, Hasan Can; Hardalaç, Naciye; Kara, Ali Can; Hardalaç Firat – World Journal of Education, 2021
Because the classification saves time in the learning process and enables this process to take place more easily, its contribution to music learning cannot be denied. One of the most valid and effective methods in music classification is music genre classification. Given the rapid progress of music production in the world and the significant…
Descriptors: Music, Classification, Automation, Music Education
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Lientje Maas; Matthew J. Madison; Matthieu J. S. Brinkhuis – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due…
Descriptors: Clinical Diagnosis, Classification, Models, Psychometrics
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Madeline A. Schellman; Matthew J. Madison – Grantee Submission, 2024
Diagnostic classification models (DCMs) have grown in popularity as stakeholders increasingly desire actionable information related to students' skill competencies. Longitudinal DCMs offer a psychometric framework for providing estimates of students' proficiency status transitions over time. For both cross-sectional and longitudinal DCMs, it is…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
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Du, Hanxiang; Xing, Wanli – Distance Education, 2023
Online discussion forums are highly valued by instructors due to their affordance for understanding class activities and learning. However, a discussion forum with a great number of posts requires a large amount of time to view, and help requests are easily overlooked. Various machine-learning--based tools have been developed to help instructors…
Descriptors: Computer Mediated Communication, Discussion Groups, Classification, Identification
Huggins, Kristin A. – ProQuest LLC, 2023
Voice misclassification threatens the vocal longevity and long-term career success of voice students enrolled in higher education (HE) vocal programs. Not every singer possesses the musculature required to support the unique vocal fold density and subglottal pressure necessary to sing repertoire and roles associated with certain voice types…
Descriptors: Singing, Higher Education, Classification, Methods
Kye, Anna – ProQuest LLC, 2023
Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…
Descriptors: Comparative Analysis, Classification, College Enrollment, Prediction
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