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Orkun Kocak; Sahin Idil – Journal of Education in Science, Environment and Health, 2025
This study is developing a Deep Learning model automating the coding of drawings students provide about climate change phenomena in our world, as a learning contribution through formative assessment. We started first with ResNet50 architecture, but ultimately, we settled on MobileNetV2 reduced architecture for the sake of being able to integrate…
Descriptors: Climate, Artificial Intelligence, Accuracy, Environmental Education
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Jonathan Liu; Seth Poulsen; Erica Goodwin; Hongxuan Chen; Grace Williams; Yael Gertner; Diana Franklin – ACM Transactions on Computing Education, 2025
Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both…
Descriptors: Teaching Methods, Algorithms, Design, Computer Science Education
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Wenlong Yi; Xuan Huang; Sergey Kuzmin; Igor Gerasimov; Yun Luo – Education and Information Technologies, 2025
This study proposes a knowledge graph-based big data analysis model for course quality evaluation, aiming to address issues in online education course evaluations such as semantic bias, grammatical deficiencies, vocabulary limitations, false evaluations, information distortion, and imbalanced evaluation categories. The model incorporates three…
Descriptors: Electronic Learning, Online Courses, Course Evaluation, Concept Mapping
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Khaldi, Amina; Bouzidi, Rokia; Nader, Fahima – Smart Learning Environments, 2023
In recent years, university teaching methods have evolved and almost all higher education institutions use e-learning platforms to deliver courses and learning activities. However, these digital learning environments present significant dropout and low completion rates. This is primarily due to the lack of student motivation and engagement.…
Descriptors: Gamification, Electronic Learning, Higher Education, Recognition (Achievement)
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Zhao, Zhong; Wei, Jiwei; Xing, Jiayi; Zhang, Xiaobin; Qu, Xingda; Hu, Xinyao; Lu, Jianping – Journal of Autism and Developmental Disorders, 2023
This study segmented the time series of gaze behavior from nineteen children with autism spectrum disorder (ASD) and 20 children with typical development in a face-to-face conversation. A machine learning approach showed that behavior segments produced by these two groups of participants could be classified with the highest accuracy of 74.15%.…
Descriptors: Children, Autism Spectrum Disorders, Symptoms (Individual Disorders), Eye Movements
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Sen, Sedat; Cohen, Allan S. – Educational and Psychological Measurement, 2023
The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test…
Descriptors: Sample Size, Item Response Theory, Accuracy, Classification
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Pirinen, Veera; Loukusa, Soile; Dindar, Katja; Mäkinen, Leena; Hurtig, Tuula; Jussila, Katja; Mattila, Marja-Leena; Eggers, Kurt – Journal of Speech, Language, and Hearing Research, 2023
Purpose: The purpose of this study was to examine the nature of speech disfluencies in autistic young adults and controls by using a wide-range disfluency classification of typical disfluencies (TD; i.e., filled pauses, revisions, abandoned utterances, and multisyllable word and phrase repetitions), stuttering-like disfluencies (SLD; i.e., sound…
Descriptors: Autism Spectrum Disorders, Young Adults, Stuttering, Speech Impairments
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Akkaya, Burcu – International Journal of Contemporary Educational Research, 2023
This study focuses on Grounded Theory, which is one of the qualitative research designs. Glaser and Strauss developed the Grounded Theory; it has been revised by other scientists, resulting in three distinct Grounded Theory approaches: the systematic design (Corbin and Strauss approach), the classical design (Glaser approach), and the…
Descriptors: Grounded Theory, Systems Approach, Design, Data
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Espinoza, Oscar; González, Luis Eduardo; Castillo, Dante; McGinn, Noel – Urban Education, 2023
Chile offers high school dropouts a chance to graduate through enrollment in Second Opportunity Centers, located in cities ranging in population from 5 million inhabitants to less than 100,000. Participants in 18 centers were classified into four distinct classes based on their family situation, handicaps, employment, experience with…
Descriptors: Foreign Countries, Dropouts, Secondary Education, Graduation
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Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
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Zheng, Rong; Busemeyer, Jerome R.; Nosofsky, Robert M. – Cognitive Science, 2023
Though individual categorization or decision processes have been studied separately in many previous investigations, few studies have investigated how they interact by using a two-stage task of first categorizing and then deciding. To address this issue, we investigated a categorization-decision task in two experiments. In both, participants were…
Descriptors: Classification, Decision Making, Task Analysis, Feedback (Response)
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Ilagan, Michael John; Falk, Carl F. – Educational and Psychological Measurement, 2023
Administering Likert-type questionnaires to online samples risks contamination of the data by malicious computer-generated random responses, also known as bots. Although nonresponsivity indices (NRIs) such as person-total correlations or Mahalanobis distance have shown great promise to detect bots, universal cutoff values are elusive. An initial…
Descriptors: Likert Scales, Questionnaires, Artificial Intelligence, Identification
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Cömert, Zeynep; Samur, Yavuz – Interactive Learning Environments, 2023
Almost in every aspect of life, classification and categorization make it easier for humans to analyze complex structures and systems. In games, the classification of the players based on their demographics, behaviors, expectations and preferences of the game is important to increase players' motivation and satisfaction. Likewise, knowing the…
Descriptors: Classification, Student Characteristics, Models, Student Motivation
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Ison, Shelby E.; Richards, Kevin Andrew; Hemphill, Michael A.; Templin, Thomas J. – Journal of Teaching in Physical Education, 2023
Background: Over the past several decades, scholars have regularly reviewed qualitative research published in the "Journal of Teaching in Physical Education," among other outlets, to understand the developing role of qualitative methods in physical education and sport pedagogy. In this review, the authors present a descriptive and…
Descriptors: Qualitative Research, Physical Education, Periodicals, Journal Articles
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Liang, Xinya; Cao, Chunhua – Journal of Experimental Education, 2023
To evaluate multidimensional factor structure, a popular method that combines features of confirmatory and exploratory factor analysis is Bayesian structural equation modeling with small-variance normal priors (BSEM-N). This simulation study evaluated BSEM-N as a variable selection and parameter estimation tool in factor analysis with sparse…
Descriptors: Factor Analysis, Bayesian Statistics, Structural Equation Models, Simulation
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