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Corey Schimpf; Brian Castellani – International Journal of Social Research Methodology, 2024
Advances in the integration of smart technology with interdisciplinary methods has created a new genre, approachable modeling and smart methods -- AM-Smart for short. AM-Smart platforms address a major challenge for applied and public sector analysts, educators and those trained in traditional methods: accessing the latest advances in…
Descriptors: Technology Integration, Technology Uses in Education, Computer Oriented Programs, Artificial Intelligence
Aslina Saad; Suhaila Zainudin – Interactive Learning Environments, 2024
This study delves into the integration of Project-Based Learning (PBL) and Computational Thinking (CT) to enhance 21st century learning. Through a Narrative Literature Review (NLR), pivotal strategies for effective implementation are identified. These include fostering collaborative pedagogy, employing visualization tools, embracing diverse…
Descriptors: Active Learning, Student Projects, Teaching Methods, Computation
Camille Lund – Mathematics Teacher: Learning and Teaching PK-12, 2024
Every educator knows the sinking feeling of a lesson gone wrong. As teachers look around the room and realize that many of their students are just not getting it, they often feel like failures. However, the struggle students experience as they persevere through high-quality challenging tasks is not a sign of failure, but rather a key aspect of…
Descriptors: Mathematics Instruction, Difficulty Level, Mathematics Skills, Teaching Methods
Korchi, Adil; Dardor, Mohamed; Mabrouk, El Houssine – Education and Information Technologies, 2020
Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…
Descriptors: Learning Analytics, Data, Computation, Mathematics
The Reliability of the Posterior Probability of Skill Attainment in Diagnostic Classification Models
Johnson, Matthew S.; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2020
One common score reported from diagnostic classification assessments is the vector of posterior means of the skill mastery indicators. As with any assessment, it is important to derive and report estimates of the reliability of the reported scores. After reviewing a reliability measure suggested by Templin and Bradshaw, this article suggests three…
Descriptors: Reliability, Probability, Skill Development, Classification
Hu, Mingjia; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…
Descriptors: Classification, Recognition (Psychology), Computation, Models
Li, Jianzhu; Krenzke, Tom; Ren, Weijia; Mohadjer, Leyla; Fay, Robert; Erciulescu, Andreea – National Center for Education Statistics, 2022
The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle international survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across…
Descriptors: Adults, International Assessment, Adult Literacy, Numeracy
Saetnan, Ann Rudinow; Tøndel, Gunhild; Rasmussen, Bente – Research Evaluation, 2019
This qualitative case study of emergent practices in a multi-paradigmatic field at one department in Norway explores how performance metrics in science intra-act with staff composition and resource allocation, potentially affecting paradigm trends. Inspired by agential realism, we discuss four key metrics as the material core of an assemblage…
Descriptors: Computation, Models, Number Concepts, Foreign Countries
Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners
Vong, Wai Keen; Hendrickson, Andrew T.; Navarro, Danielle J.; Perfors, Amy – Cognitive Science, 2019
The curse of dimensionality, which has been widely studied in statistics and machine learning, occurs when additional features cause the size of the feature space to grow so quickly that learning classification rules becomes increasingly difficult. How do people overcome the curse of dimensionality when acquiring real-world categories that have…
Descriptors: Learning Processes, Classification, Models, Performance
Ahirwal, Mitul Kumar; Kumar, Prabhat – Interchange: A Quarterly Review of Education, 2023
Nowadays, with increasing competitiveness in every field, securing a good job may be difficult. In this connection, students aiming to get into the best educational institution (EI) would give them their best chance of quality education and good job opportunities. Institutional evaluation and selection are complex tasks that must simultaneously…
Descriptors: Foreign Countries, College Choice, Selection Criteria, Decision Making
Emily A. Brown – ProQuest LLC, 2024
Previous research has been limited regarding the measurement of computational thinking, particularly as a learning progression in K-12. This study proposes to apply a multidimensional item response theory (IRT) model to a newly developed measure of computational thinking utilizing both selected response and open-ended polytomous items to establish…
Descriptors: Models, Computation, Thinking Skills, Item Response Theory
Seyedahmad Rahimi; Russell Almond; Andrea Ramírez-Salgado; Christine Wusylko; Lauren Weisberg; Yukyeong Song; Jie Lu; Ted Myers; Bowen Wang; Xiaomaon Wang; Marc Francois; Jennifer Moses; Eric Wright – Journal of Computer Assisted Learning, 2024
Background: Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the…
Descriptors: Competence, Models, Research Methodology, Research Design
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Omar, Abdulfattah – Journal of Language and Linguistic Studies, 2021
In recent years, numerous computational methods have been developed that have been widely used in humanities and literary studies. In spite of the potential of such methods in providing workable solutions to various inherent problems in research within these domains, including selectivity, objectivity, and replicability, very little empirical work…
Descriptors: Fiction, Novels, Classics (Literature), Literary Devices