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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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Sarah Emily Wilson; Joseph B. Wiggins; Lauren N. Wong; Tracy Gault Ulrich; Bill Causey; Jorge Parra; Nicholas A. Gage; Jose Blackorby – Journal of Special Education Technology, 2025
Over the past few decades, advances in computing power and the widespread adoption of the Internet have completely transformed the ways that people obtain information, communicate, educate, and conduct business. Unfortunately, access to technology and to the training required to use technology are not equitably distributed in the United States,…
Descriptors: Students with Disabilities, Educational Technology, Technology Uses in Education, Intervention
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Ramon Mayor Martins; Christiane G. Von Wangenheim; Marcelo F. Rauber; Adriano F. Borgatto; Jean C. R. Hauck – ACM Transactions on Computing Education, 2024
As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…
Descriptors: Artificial Intelligence, Computer Science Education, Socioeconomic Status, Correlation
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Yun Dai – Education and Information Technologies, 2025
There is a growing consensus that AI literacy requires a holistic lens, including not only technical knowledge and skills but also social and ethical considerations. Yet, providing holistic AI education for upper-primary students remains challenging due to the abstract and complex nature of AI and a lack of pedagogical experiences in schools.…
Descriptors: Integrated Activities, Holistic Approach, Artificial Intelligence, Computer Science Education
de Vera, Shaun P. – ProQuest LLC, 2023
Contributing to a growing body of research on broadening participation in computing for historically underrepresented racial communities (e.g., Black and Latinx), this qualitative study describes the knowledge (content and sources) six antiracist Computer Science (CS) teachers have about examples (and counterexamples) of modern techno-racism, a…
Descriptors: Racism, Computer Science Education, Middle School Teachers, High School Teachers
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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
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Hao-Yue Jin; Maria Cutumisu – Education and Information Technologies, 2024
Computational thinking (CT) is considered to be a critical problem-solving toolkit in the development of every student in the digital twenty-first century. Thus, it is believed that the integration of deeper learning in CT education is an approach to help students transfer their CT skills beyond the classroom. Few literature reviews have mapped…
Descriptors: Computation, Thinking Skills, Problem Solving, Artificial Intelligence
Xiaoyi Tian – ProQuest LLC, 2024
As Artificial Intelligence (AI) becomes increasingly ubiquitous in society, conversational agents such as Siri, Alexa, and ChatGPT are shaping the experiences of younger generations. However, these young users often lack opportunities to learn about the inner workings of these AI technologies. One way to foster such learning is by empowering…
Descriptors: Artificial Intelligence, Technology Uses in Education, Access to Computers, Access to Education
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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Janice D. Gobert; Haiying Li; Rachel Dickler; Christine Lott – Grantee Submission, 2024
An intelligent tutoring system (ITS, henceforth) is currently defined as a computer system that delivers personalized instruction to students by using computational techniques to evaluate the learner in a variety of ways, including (but not limited to) their prior knowledge, competency/skill levels, motivation, and affective states. ITSs are…
Descriptors: Artificial Intelligence, Scaffolding (Teaching Technique), Computer Science Education, Teaching Methods
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Juho Kahila; Henriikka Vartiainen; Matti Tedre; Eetu Arkko; Anssi Lin; Nicolas Pope; Ilkka Jormanainen; Teemu Valtonen – Informatics in Education, 2024
The integration of artificial intelligence (AI) topics into K-12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and…
Descriptors: Personal Autonomy, Data, Children, Creativity
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Gresse Von Wangenheim, Christiane; Da Cruz Alves, Nathalia; Rauber, Marcelo F.; Hauck, Jean C. R.; Yeter, Ibrahim H. – Informatics in Education, 2022
Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for…
Descriptors: Performance Based Assessment, Artificial Intelligence, Learning Processes, Scoring Rubrics
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Açisli Çelik, Sibel; Ergin, Ismet – International Journal of Technology in Education, 2022
In this research, in the "Artvin gets Color with Science and Robotics-2" project, which was supported with the Project number 121B899 within the scope of the 2020/1 call period launched in the 15thyear of the Scientific and Technological Research Council of Turkey (TÜBITAK) 4004-Nature Education and Science Schools Support Program,…
Descriptors: Middle School Students, Student Attitudes, Scientific Concepts, Concept Formation
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Fagan, Bryan J.; Payne, Bryson R. – Proceedings of the Interdisciplinary STEM Teaching and Learning Conference, 2017
The US Bureau of Labor Statistics predicts over 8 million job openings in IT and computing, including 1 million cybersecurity postings, over the current five-year period. This paper presents lessons learned in preparing middle-school students in rural Georgia for future careers in computer science/ IT by teaching computer programming in the free,…
Descriptors: Programming Languages, Teaching Methods, Computer Science Education, Open Source Technology
Rachmatullah, Arif – ProQuest LLC, 2021
This dissertation conducted a science classroom intervention using two instructional approaches, computational modeling and paper-based pictorial modeling, in the context of food webs. A series of research papers were written on the impact of the intervention on students' attitudes and learning, and on teachers via professional development and…
Descriptors: Teaching Methods, Science Instruction, Food, Intervention
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