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Marianthi Grizioti; Chronis Kynigos – Informatics in Education, 2024
Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…
Descriptors: Computation, Thinking Skills, Data Science, Classification
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Melissa Braaten – American Journal of Education, 2024
Purpose: This study investigates how the practice of dividing students and coursework into leveled categories persists in science education despite decades of efforts aimed at reducing inequities. This study makes underlying logics visible through an empirical analysis of how science educators attempt to reconcile an egalitarian vision of science…
Descriptors: Science Instruction, Ethnography, Honors Curriculum, High School Students
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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
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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
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Lange, Jochen – Critical Studies in Education, 2021
The paper considers digital tutoring platforms as commercial products in the shadow education sector. In particular, it focuses on relatively new platforms which purportedly act as tutors themselves: web-based learning software providing "intelligent tutoring systems.' The question is not how effective and beneficial these platforms are for…
Descriptors: Intelligent Tutoring Systems, Design, Data, Business
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Castillo-Sepúlveda, Jorge; Pasmanik, Diana – European Journal of Engineering Education, 2021
This study addresses the interpretations of the human in the discourse of civil industrial engineers in Chile and analyses their relationship with ethics and training. We argue that engineering is a heterogeneous activity that requires the alignment of multiple elements. Among these, assumptions about the human influence both the design of…
Descriptors: Engineering Education, Discourse Analysis, Civil Engineering, Ethics
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Speed, Laura J.; Chen, Jidong; Huettig, Falk; Majid, Asifa – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2021
Do we structure object-related conceptual information according to real-world sensorimotor experience, or can it also be shaped by linguistic information? This study investigates whether a feature of language coded in grammar--numeral classifiers--affects the conceptual representation of objects. We compared speakers of Mandarin (a classifier…
Descriptors: Classification, Knowledge Representation, Mandarin Chinese, Indo European Languages
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Buhagiar, Kristina – Learning Organization, 2021
Purpose: While the importance of interorganizational learning (IOL) as a resource for strategic renewal has been acknowledged in research, limited attention has been placed on exploring IOL in complex networks or ecosystems. This paper aims to bridge this gap in literature through conceptualizing IOL in the tourism industry at the micro, meso and…
Descriptors: Tourism, Institutional Cooperation, Organizational Learning, Social Networks
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Aydogdu, Seyhmus – Journal of Educational Computing Research, 2021
Student modeling is one of the most important processes in adaptive systems. Although learning is individual, a model can be created based on patterns in student behavior. Since a student model can be created for more than one student, the use of machine learning techniques in student modeling is increasing. Artificial neural networks (ANNs),…
Descriptors: Mathematical Models, Artificial Intelligence, Bayesian Statistics, Learning Processes
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Weiss, Brandi A.; Dardick, William – Journal of Experimental Education, 2021
Classification measures and entropy variants can be used as indicators of model fit for logistic regression. These measures rely on a cut-point, "c," to determine predicted group membership. While recommendations exist for determining the location of the cut-point, these methods are primarily anecdotal. The current study used Monte Carlo…
Descriptors: Cutting Scores, Regression (Statistics), Classification, Monte Carlo Methods
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Cai, Liuhan; Albano, Anthony D.; Roussos, Louis A. – Measurement: Interdisciplinary Research and Perspectives, 2021
Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…
Descriptors: Adaptive Testing, Test Items, Item Response Theory, Test Construction
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Hofmann, Klaus; Baumann, Andreas – Journal of Child Language, 2021
This paper investigates whether typical stress patterns in English nouns and verbs are available as a prosodic cue for categorisation and accelerated word learning during first language acquisition. The stress typicality hypothesis states that left-stressed nouns and right-stressed verbs should be acquired earlier than the reverse configurations…
Descriptors: English, Suprasegmentals, Nouns, Verbs
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Friberg, Therese – Social Psychology of Education: An International Journal, 2021
Attributing negative categories such as 'weak' to pupils is a common practice in Sweden and a known phenomenon worldwide. While there has been a substantial amount of research on different expressions of 'deviance' in the educational arena, the research on how teachers communicate about pupils as 'weak' is scarce. In this study, teachers'…
Descriptors: Foreign Countries, Teacher Student Relationship, Teacher Expectations of Students, Attribution Theory
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Broda, Michael D.; Bogenschutz, Matthew; Dinora, Parthenia; Prohn, Seb M.; Lineberry, Sarah; Ross, Erica – American Journal on Intellectual and Developmental Disabilities, 2021
In this article, we demonstrate the potential of machine learning approaches as inductive analytic tools for expanding our current evidence base for policy making and practice that affects people with intellectual and developmental disabilities (IDD). Using data from the National Core Indicators In-Person Survey (NCI-IPS), a nationally validated…
Descriptors: Artificial Intelligence, Prediction, Employment Patterns, Day Programs
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Bond, Alesha D.; Washburn, David A.; Kleider-Offutt, Heather M. – Applied Cognitive Psychology, 2021
This present study was designed to investigate whether face-type (stereotypical or nonstereotypical) facilitates stereotype-consistent categorization and decision-making. Previous literature suggests an associative link between adults' stereotypically Black facial features and assumed criminality. The question addressed here is whether the…
Descriptors: Ethnic Stereotypes, African Americans, Human Body, Classification
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