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Yusuf Oc; Hela Hassen – Marketing Education Review, 2025
Driven by technological innovations, continuous digital expansion has transformed fundamentally the landscape of modern higher education, leading to discussions about evaluation techniques. The emergence of generative artificial intelligence raises questions about reliability and academic honesty regarding multiple-choice assessments in online…
Descriptors: Higher Education, Multiple Choice Tests, Computer Assisted Testing, Electronic Learning
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Elsa Morgado; Levi Leonido; Antonino Pereira; Luís Borges Gouveia – Educational Process: International Journal, 2025
Background/purpose: Artificial Intelligence (AI) and distance learning (EaD) have profoundly transformed education, redefining teaching methodologies and learning dynamics. When integrated into educational environments, these technologies facilitate equitable access to knowledge, enable personalized learning, and enhance pedagogical flexibility.…
Descriptors: Educational Technology, Technology Uses in Education, Distance Education, Artificial Intelligence
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Jasin, Jamil; Ng, He Tong; Atmosukarto, Indriyati; Iyer, Prasad; Osman, Faiezin; Wong, Peng Yu Kelly; Pua, Ching Yee; Cheow, Wean Sin – Education and Information Technologies, 2023
Low student engagement and motivation in online classes are well-known issues many universities face, especially with distance education during the COVID-19 pandemic. The online environment makes it even harder for teachers to connect with their students through traditional verbal and nonverbal behaviours, further decreasing engagement. Yet,…
Descriptors: Artificial Intelligence, Synchronous Communication, Electronic Learning, Chemistry
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Carruana Martín, Adrián; Alario-Hoyos, Carlos; Delgado Kloos, Carlos – Australasian Journal of Educational Technology, 2022
COVID-19 has brought new hybrid learning environments with some students in the classroom and some others online, synchronously, due to the needs of social distancing. These new hybrid learning environments pose new challenges, for example for group collaboration. This paper presents Smart Groups, a system aimed at helping teachers to orchestrate…
Descriptors: Blended Learning, Cooperative Learning, Electronic Learning, COVID-19
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Vidanaralage, A. J.; Dharmaratne, A. T.; Haque, S. – Australasian Journal of Educational Technology, 2022
Adapting innovative educational technologies to bolster students' academic learning is increasing rapidly. This study explored schema congruent and incongruent participants behaviour when experiencing video-based materials as the medium of learning within the frame of a flipped learning environment. The participants watched an educational learning…
Descriptors: Schemata (Cognition), Psychological Patterns, Emotional Response, Reaction Time
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Jun Chen Hsieh – RELC Journal: A Journal of Language Teaching and Research, 2024
Despite the increasing attention to technology-enhanced language learning in English-as-a-foreign-language contexts, investigation regarding the effects of multimodal technologies on affective factors (particularly emotions and grit) in digital storytelling has remained underexplored. Therefore, this mixed-methods study reports on…
Descriptors: Multimedia Materials, Story Telling, Second Language Learning, English (Second Language)
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Jo-Chi Hsiao; Jason S. Chang – Interactive Learning Environments, 2024
During the COVID-19 pandemic, global teachers gained extensive experiences with teaching online courses. To design quality online courses in the post-pandemic era, the impact of the latest technology, such as artificial intelligence (AI), must be considered. Investigating how teachers incorporate AI-powered tools and how students perceive learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Electronic Learning, English (Second Language)
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Liu, Xinyang; Ardakani, Saeid Pourroostaei – Education and Information Technologies, 2022
The purpose of this study is to propose an e-learning system model for learning content personalisation based on students' emotions. The proposed system collects learners' brainwaves using a portable Electroencephalogram and processes them via a supervised machine learning algorithm, named K-nearest neighbours (KNN), to recognise real-time…
Descriptors: Foreign Countries, Undergraduate Students, Electronic Learning, Artificial Intelligence
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Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction