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Stefanie Beninger; Alex Reppel; Julie Stanton; Forrest Watson – Journal of Marketing Education, 2025
The emergence of generative AI (GenAI) has illustrated that higher education needs to adapt to the technology. Its speed of evolution requires that we adequately prepare students for an ever-changing landscape. Toward achieving that aim, we draw on the concept of interpretive flexibility, where the interpretations, uses, and outcomes of a new…
Descriptors: Business Education, Marketing, Artificial Intelligence, Computer Software
Wesley F. Reinhart; Reed Williams; Ryan Solnosky; R. Allen Kimel; Rebecca Napolitano – Advances in Engineering Education, 2025
Data science has become an increasingly popular topic among engineering students and practitioners as high-profile engineering applications of machine learning and artificial intelligence continue to make headlines. Companies in engineering domains are placing a growing emphasis on hiring engineers who can extract insights and create value from…
Descriptors: Engineering Education, Statistics Education, Education Work Relationship, Artificial Intelligence
Shahper Richter; Marilyn Giroux; Inna Piven; Herbert Sima; Patrick Dodd – Journal of Marketing Education, 2025
AI advancements in higher education have reshaped marketing education, posing challenges for educators in integrating AI into curricula. This integration is essential for aligning with industry advancements and fostering responsible AI utilization among students. The purpose of this study is to provide insights into how marketing educators can…
Descriptors: Constructivism (Learning), Artificial Intelligence, Computer Software, Technology Integration
Victor A. Barger; Pavan Rao Chennamaneni; Andrew J. Dahl; James W. Peltier – Marketing Education Review, 2025
The rapid rise of artificial intelligence (AI) presents both challenges and opportunities for marketing educators. This paper outlines a transformative process undertaken by our department to integrate AI across the marketing curriculum. We detail a strategic shift from initial resistance to acceptance, resulting in the successful integration of…
Descriptors: Business Education, Marketing, Artificial Intelligence, Teaching Methods
Yi-Ping Wu; Hui-Hsien Feng; Bo-Ren Mau – Interpreter and Translator Trainer, 2025
Corpus analysis methods have been widely employed in literary translation research by numerous scholars. However, their integration into literary translation training has yet to be developed. With the advancement of AI technology, this paper explores the potential of employing AI-enhanced corpus text analysis and text mining techniques in this…
Descriptors: Translation, Computer Software, Comparative Analysis, Language Styles
Dina Fitria Murad; Meta Amalya Dewi; Arbaiah Inn; Silvia Ayunda Murad; Noor Udin; Taufik Darwis – Journal of Educators Online, 2025
This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…
Descriptors: Electronic Learning, Data Collection, Context Effect, Learning Processes
Md. Mahadhi Hasan; Anika Sikder; Rashed Mahmud – Language Teaching Research Quarterly, 2025
Some serious instances of plagiarism have been discussed in Bangladesh's institutions, where students, researchers, and even faculty members were given severe penalties. This study explores the factors influencing teachers of English at the tertiary level in Bangladesh regarding plagiarism, including emerging concerns around AI-based plagiarism. A…
Descriptors: Language Teachers, English (Second Language), Second Language Learning, Second Language Instruction
Amir Reza Rahimi; Zahra Mosalli – Smart Learning Environments, 2025
Researchers have significantly explored language learners' attitudes toward ChatGPT through the lens of technology acceptance models, particularly with its development and integration into computer-assisted language learning (CALL). However, further research in this area is necessary to apply a theoretical framework with a pedagogical-oriented…
Descriptors: Second Language Learning, Second Language Instruction, Artificial Intelligence, Technology Uses in Education