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Allison Master; Taylor Alexander; Jennifer Thompson; Weihua Fan; Andrew N. Meltzoff; Sapna Cheryan – Journal of Research on Technology in Education, 2025
Motivating girls to enroll in computer science (CS) courses is critically important. Stereotypes that girls are less interested than boys in CS may deter girls. Three preregistered experimental studies (N = 1,053) examined causal links between gender-interest stereotypes and middle school students' CS motivation. Experiment 1 showed that…
Descriptors: Females, Womens Education, Middle School Students, Computer Science Education
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Xiaodong Huang; Chengche Qiao – Science & Education, 2024
Artificial intelligence is the unification of philosophy, cognitive science, mathematics, neurophysiology, psychology, computer science, information theory, cybernetics, and uncertainty theory. Therefore, it is feasible and necessary to utilize STEAM (Science, Technology, Engineering, Liberal Arts, and Mathematics) education to learn artificial…
Descriptors: Thinking Skills, Artificial Intelligence, STEM Education, Art Education
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Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
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Sibley F. Lyndgaard; Ruth Kanfer – Journal of the Learning Sciences, 2024
Background: "21st century learning" is reliant on not only cognitive competencies such as problem-solving, but also interpersonal (e.g., collaboration) and intrapersonal (e.g., self-regulation) competencies. Building on research in K-12/undergraduate contexts, we investigated cognitive, interpersonal, and intrapersonal learning tactics…
Descriptors: 21st Century Skills, Interpersonal Competence, Learning Strategies, Graduate Students
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Xinlei Li; Guoyuan Sang; Martin Valcke; Johan van Braak – Education and Information Technologies, 2024
Computational thinking (CT) is valued as a thinking process that is required to adapt to the development of curriculum in primary education. In the context of modern information technology, English as a language subject emphasizes the necessity for changes in both learning and teaching modes. However, there is a lack of up-to-date synthesis…
Descriptors: Computer Science Education, Technological Literacy, Pedagogical Content Knowledge, Elementary School Students
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Jiyoung Kim; Anne Leftwich; Daniel Castner – Education and Information Technologies, 2024
Many K-12 computer science (CS) education initiatives at the local, state, and federal levels have recently started to focus on engaging the young children. Although most CS education research has focused on the secondary level, only minimal research has explored how computer science (CS) and computational thinking (CT) can be taught in elementary…
Descriptors: Computation, Thinking Skills, Preschool Teachers, Kindergarten
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Jiahong Su; Kai Guo; Xinyu Chen; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
The teaching of artificial intelligence (AI) has increasingly become a topic of investigation among educational researchers. Studies of AI education have predominantly focused on the university level; less attention has been paid to teaching AI in K-12 classrooms. This study synthesised empirical studies on K-12 AI education, with the aims of…
Descriptors: Artificial Intelligence, Computer Science Education, Elementary Secondary Education, Teaching Methods
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Ceren Ocak; Katherine Walters; Theodore J. Kopcha – TechTrends: Linking Research and Practice to Improve Learning, 2024
In this article, we present a conceptual framework for teaching computer science (CS) to address the unique challenges faced by marginalized groups. The framework is grounded in feminist standpoint theory and describes three key practitioner-focused areas aimed at broadening participation and increasing participation in CS education (CSEd). These…
Descriptors: Computer Science Education, Power Structure, Disadvantaged, Barriers
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Sarika Tomar; Arundhathi Arundhathi; Shikha Gupta; Mansi Sharma – Journal of Education and Learning (EduLearn), 2024
As universities shifted to online education with the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, both pedagogy and assessment patterns across disciplines underwent a change, with a shift towards collaborative digital assessments. In this context, using qualitative and quantitative methods for data collection from an assessment…
Descriptors: Student Evaluation, Cooperative Learning, Video Technology, Web Sites
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Cyril Brom; Tereza Hannemann; Tereza Tetourová; Anna Drobná; Nikol Kopánková; Kristina Volná; Katerina Kacerovská; Filip Dechterenko; Pavel Ježek; Tereza Stárková – International Journal of Technology and Design Education, 2024
Primary school children frequently use digital devices, which can be infected by computer viruses. In this mixed methods paper with two studies (N = 278 + 114), we examined 8-year-olds' preconceptions about computer viruses and protection against them; how to teach these children about said topics using three different, 30-min-long,…
Descriptors: Computers, Children, Computer Security, Knowledge Level
Melissa Unger – ProQuest LLC, 2024
Computer Science (CS) is a rapidly growing field that impacts almost every aspect of students' lives. From media consumption to future careers in medicine, agriculture, security, finance, and other areas, understanding computer programming is essential for 21st-century society and careers. Over the next decade, employment opportunities in computer…
Descriptors: Computer Science Education, Self Efficacy, Grade 2, Teacher Attitudes
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Amanpreet Kaur; Kuljit Kaur Chahal – Education and Information Technologies, 2024
Research so far has overlooked the contribution of students' noncognitive factors to their performance in introductory programming in the context of personalized learning support. This study uses learning analytics to design and implement a Dashboard to understand the contribution of introductory programming students' learning motivation,…
Descriptors: Learning Analytics, Introductory Courses, Programming, Computer Science Education
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Claudio Alvarez; Maira Marques Samary; Alyssa Friend Wise – Journal of Computing in Higher Education, 2024
Computer programming is a skill of increasing importance in scientific and technological fields. However, in introductory computer science (CS1) courses in higher education, approximately one in every three students fails. A common reason is that students are overwhelmed by an accelerated and inflexible pace of learning that jeopardizes success.…
Descriptors: Mastery Learning, Computer Science Education, Programming, Action Research
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Rebecca L. Matz; Mark Mills; Holly A. Derry; Benjamin T. Hayward; Caitlin Hayward – British Journal of Educational Technology, 2024
Mastery-based assignments typically provide students with multiple opportunities to improve their performance, but getting students to take advantage of these opportunities is difficult. We report on the implementation of a two-part series of nudges designed to improve students' engagement with and performance on mastery-based assignments in…
Descriptors: Mastery Learning, Scores, Assignments, Prompting
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Camille Ferguson; Vanora Thomas; Juan Del Toro; Daniel Light; Kamau Bobb; Peta-Gay Clarke; Shameeka Emanuel; Ed Gronke; Mary Jo Madda; Imani Jennings – ACM Transactions on Computing Education, 2024
Black women represent the greatest underrepresentation in STEM fields, particularly the technology sector. According to a 2015 article in "The Verge," Black women make up between 0% and 7% of the staff at the eight largest technology firms in the United States. This points to a glaring problem in terms of equity and inclusivity in the…
Descriptors: Social Capital, Computer Science Education, Ecology, African American Students
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