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Fatma Merve Mustafaoglu; Fatma Alkan – Science Education International, 2025
Recycling waste is essential to mitigate environmental damage caused by human activity. Environmentally responsible behaviors, shaped during early ages, are closely linked to environmental attitudes, as demonstrated by prior research. This study aims to predict middle school students' recycling behaviors using machine learning algorithms. A…
Descriptors: Middle School Students, Recycling, Student Behavior, Artificial Intelligence
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Idam Ragil Widianto Atmojo; Roy Ardiansyah; Joko Tri Widianto – Elementary School Forum (Mimbar Sekolah Dasar), 2024
This study aims to determine whether there is a relationship between linguistic intelligence and computational thinking. The research method employed is quantitative, utilizing a correlational research design. The research sample comprised 73 students from 4 elementary schools in the Laweyan District, Surakarta City. Data collection involved a…
Descriptors: Intelligence, Linguistics, Computation, Grade 5
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Józsa, Krisztián; Amukune, Stephen; Zentai, Gabriella; Barrett, Karen Caplovitz – Journal of Intelligence, 2022
Research has shown that the development of cognitive and social skills in preschool predicts school readiness in kindergarten. However, most longitudinal studies are short-term, tracking children's development only through the early elementary school years. This study aims to investigate the long-term impact of preschool predictors, intelligence,…
Descriptors: Foreign Countries, School Readiness, Intelligence Tests, Preschool Children
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Andrew Rockliffe – Design and Technology Education, 2025
Design and Technology (D&T) in the UK is approaching a crisis point, with declining enrolment, staffing shortages and increasing marginalisation in the curriculum. However, this paper argues that D&T is not a problem to be solved. Rather, it is a solution to be scaled. Positioned at the intersection of material practice, iteration and…
Descriptors: Design, Technology, Foreign Countries, Creativity
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He, Xinyue; Wang, Huan; Friesen, Dimitris; Shi, Yaojiang; Chang, Fang; Liu, Han – Compare: A Journal of Comparative and International Education, 2022
Little attention has been paid to the role that low levels of cognitive development (or IQ) play among both left-behind children (LBCs) and children living with parents (CLPs) in the context of poor educational attainment in rural China. In this paper, we examine how general cognitive abilities contribute to the academic achievement gains of both…
Descriptors: Cognitive Ability, Academic Achievement, Rural Areas, Foreign Countries
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Jyoti Sharma; B. Biswal; Pankaj Tyagi; Shobha Bagai – Gifted and Talented International, 2024
Academically gifted students or high potential learners don't feel challenged in regular classrooms. Teachers in schools are also not quipped with pedagogical interventions to meet the advanced learning needs of gifted students. Mentoring is considered an effective method to guide, motivate and optimize learning abilities of gifted students. The…
Descriptors: Mentors, Academically Gifted, Program Development, Science Education
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Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Matti Tedre – IEEE Transactions on Learning Technologies, 2025
The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer Science Education, Grade 4
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Jiawei Xiong; George Engelhard; Allan S. Cohen – Measurement: Interdisciplinary Research and Perspectives, 2025
It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…
Descriptors: Responses, Test Items, Test Format, Grade 8
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Chelsea Chandler; Rohit Raju; Jason G. Reitman; William R. Penuel; Monica Ko; Jeffrey B. Bush; Quentin Biddy; Sidney K. D’Mello – International Educational Data Mining Society, 2025
We investigated methods to enhance the generalizability of large language models (LLMs) designed to classify dimensions of collaborative discourse during small group work. Our research utilized five diverse datasets that spanned various grade levels, demographic groups, collaboration settings, and curriculum units. We explored different model…
Descriptors: Artificial Intelligence, Models, Natural Language Processing, Discourse Analysis
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Bayan Al-Kasasbeh; Waleed Nawafleh – Educational Process: International Journal, 2025
Background/purpose: The study aimed to investigate the effectiveness of teaching based on multiple intelligences in acquiring chemical concepts and the ability to explain household chemical phenomena among basic-stage students. Materials/methods: The study employed an experimental method with a quasi-experimental design for two non-equivalent…
Descriptors: Instructional Effectiveness, Science Instruction, Chemistry, Scientific Concepts
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Andres Felipe Zambrano; Nidhi Nasiar; Jaclyn Ocumpaugh; Alex Goslen; Jiayi Zhang; Jonathan Rowe; Jordan Esiason; Jessica Vandenberg; Stephen Hutt – International Educational Data Mining Society, 2024
Research into student affect detection has historically relied on ground truth measures of emotion that utilize one of three sources of data: (1) self-report data, (2) classroom observations, or (3) sensor data that is retrospectively labeled. Although a few studies have compared sensor- and observation-based approaches to student affective…
Descriptors: Psychological Patterns, Measurement Techniques, Observation, Middle School Students
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Kim, Keunjae; Kwon, Kyungbin; Ottenbreit-Leftwich, Anne; Bae, Haesol; Glazewski, Krista – Education and Information Technologies, 2023
This study aims to explore the middle schoolers' common naive conceptions of AI and the evolution of these conceptions during an AI summer camp. Data were collected from 14 middle school students (12 boys and 2 girls) from video observations and learning artifacts. The findings revealed 6 naive conceptions about AI concepts: (1) AI was the same as…
Descriptors: Middle School Students, Misconceptions, Artificial Intelligence, Summer Programs
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Ünal Çakiroglu; Volkan Selçuk – Education and Information Technologies, 2025
In recent years, when computational thinking (CT) has become increasingly important, utilizing machine learning (ML) techniques provides a revolutionary method for comprehending and improving cognitive skills for young students. However, few studies deepen the process of learning ML and CT. This exploratory study aims to investigate the impact of…
Descriptors: Thinking Skills, Computation, Grade 5, Secondary School Students
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Man Huang – Education and Information Technologies, 2025
As educational technology advances, the role of artificial intelligence (AI) in enhancing language education becomes increasingly prominent. However, there is a scarcity of empirical research assessing how AI integration influences student engagement and contributes to the language learning performance. This mixed-methods study seeks to fill the…
Descriptors: Foreign Countries, Middle School Students, Artificial Intelligence, Learner Engagement
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Khabib Sholeh; Onok Yayang Pamungkas; Main Sufanti; Semi Sukarni; Umi Faizah; Shaleh Afif – Educational Process: International Journal, 2025
Background/purpose. Character education has become a central focus in Indonesia's national education policy. However, conventional teaching methods still fail to address the diverse learning styles of students. The Multiple Intelligences (MI) approach offers a promising alternative to improving reading literacy and encouraging character…
Descriptors: Foreign Countries, Values Education, Multiple Intelligences, Reading Instruction
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