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Asiye Toker Gokce; Arzu Deveci Topal; Aynur Kolburan Geçer; Canan Dilek Eren – Education and Information Technologies, 2025
Artificial intelligence (AI) literacy is critical to shaping students' academic experiences and future opportunities inhigher education. This study examines AI literacy among university students, examining variables such as gender, frequency of use of AI applications, completion of AI-related courses, and field of study. The research involved 664…
Descriptors: Artificial Intelligence, Technological Literacy, College Students, Decision Making
Lauren Weisberg; Joanne Barrett; Maya Israel; Don Miller – Computer Science Education, 2025
Background and Context: Although computing is a highly sought-after skill set in our modern economy, certain individuals are under represented in computer science (CS) courses and careers. The integration of visual and performing arts in K-12 CS education has been gaining "STEAM" as a viable strategy for making computing more inclusive.…
Descriptors: STEM Education, Art Education, Elementary Secondary Education, Computer Science Education
Sina Rismanchian; Eesha Tur Razia Babar; Shayan Doroudi – Annenberg Institute for School Reform at Brown University, 2025
In November 2022, OpenAI released ChatGPT, a groundbreaking generative AI chatbot backed by large language models (LLMs). Since then, these models have seen various applications in education, from Socratic tutoring and writing assistance to teacher training and essay scoring. Despite their widespread use among high school and college students in…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
Cyril Brom; Anna Drobná; Anna Yaghobová; Daniel Št’astný; Katerina Zábrodská; Marek Urban – ACM Transactions on Computing Education, 2025
Objectives: Limited research exists on how new computer science (CS) teachers understand fundamental Internet principles. This knowledge gap hinders the development of effective upskilling courses, especially as new CS curricula are being introduced worldwide. This study investigates new CS teachers' conceptions of fundamental Internet principles,…
Descriptors: Internet, Knowledge Level, Computer Science Education, Elementary School Teachers
Xuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study