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Showing 1 to 15 of 195 results Save | Export
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Pu Wang; Yifeng Lin; Tiesong Zhao – Education and Information Technologies, 2025
With the emergence of Artificial Intelligence (AI), smart education has become an attractive topic. In a smart education system, automated classrooms and examination rooms could help reduce the economic cost of teaching, and thus improve teaching efficiency. However, existing AI algorithms suffer from low surveillance accuracies and high…
Descriptors: Supervision, Artificial Intelligence, Technology Uses in Education, Automation
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Ilker Cingillioglu; Uri Gal; Artem Prokhorov – Journal of Marketing for Higher Education, 2024
The extant literature on the use of social media marketing for recruiting higher education students has an unstructured nature. To address this gap, this paper introduces a novel method called 'algorithmic document sequencing' (ADS) that links the key findings of 43 relevant articles procured from all databases to one another on the use of social…
Descriptors: Literature Reviews, Higher Education, Social Media, Marketing
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Gulnara Z. Karimova; Yevgeniya D. Kim; Amir Shirkhanbeik – Education and Information Technologies, 2025
This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners' responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent…
Descriptors: Artificial Intelligence, Marketing, Student Attitudes, Higher Education
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Jaiteg Singh; Nandini Modi – Interactive Learning Environments, 2024
Eye gaze tracking has recently become indispensable for domains like virtual reality, augmented reality, human-computer interaction and advertisement. The commercial eye gaze tracking equipment is too expensive to be used by the masses. In this manuscript, a non-invasive, low-resolution ordinary camera-based system has been proposed for tracking…
Descriptors: Eye Movements, Attention, Validity, College Students
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Rongjie Huang; Yusheng Sun; Zhifeng Zhang; Bo Wang; Junxia Ma; Yangyang Chu – International Journal of Information and Communication Technology Education, 2024
The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing…
Descriptors: Models, Innovation, Higher Education, Evaluation
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Yang Shi; Tiffany Barnes; Min Chi; Thomas Price – International Educational Data Mining Society, 2024
Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…
Descriptors: Algorithms, Artificial Intelligence, Models, Programming
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Meng Cao; Philip I. Pavlik Jr.; Wei Chu; Liang Zhang – International Educational Data Mining Society, 2024
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences between categories while blocking directs attention toward similarities within categories [4, 5]. Although a…
Descriptors: Attention, Algorithms, Artificial Intelligence, Classification
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Aysun Günes; Aysegül Liman Kaban – Higher Education Quarterly, 2025
The rapid integration of artificial intelligence (AI) into higher education has revolutionised academic research and teaching, offered transformative opportunities while raising significant ethical challenges. This Delphi study investigates the ethical dilemmas and institutional requirements for maintaining academic integrity in AI-driven…
Descriptors: Artificial Intelligence, Ethics, Integrity, Higher Education
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Sourajit Ghosh; Md. Sarwar Kamal; Linkon Chowdhury; Biswarup Neogi; Nilanjan Dey; Robert Simon Sherratt – Education and Information Technologies, 2024
Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic…
Descriptors: Engineering Education, Artificial Intelligence, College Students, Student Interests
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Mouna Ben Said; Yessine Hadj Kacem; Abdulmohsen Algarni; Atef Masmoudi – Education and Information Technologies, 2024
In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
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YuChun Chen; Lorraine A. Jacques – Journal of Teaching in Physical Education, 2025
Purpose: This study examined how physical education majors used computational thinking (CT) skills in a movement concept course. Method: Twenty-two physical education majors were tasked to create two gymnastics routines (i.e., algorithm design), analyze their routines (i.e., decomposition and abstraction), create and follow a personalized fitness…
Descriptors: Majors (Students), Computation, Thinking Skills, Athletics
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Xiaorui Wang; Chao Liu; Jing Guo – International Journal of Web-Based Learning and Teaching Technologies, 2025
This research works on creating a hybrid Knowledge Recommendation System (KRS) for an Entrepreneurship Course using the Knowledge Graph (KG) and Clustering Technologies (CTs). The system aims at improving students' learning experience by providing relevant learning materials and even focusing on learner preferences. These results are already part…
Descriptors: Entrepreneurship, Individualized Instruction, Learning Experience, Feedback (Response)
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Sinan Aydin – Turkish Online Journal of Distance Education, 2025
Open education systems play a significant role in providing flexible and accessible learning opportunities to large student populations, independent of time and location. These systems achieve cost efficiency through the effective implementation of economies of scale, reducing unit costs as student numbers increase. However, decision-making in the…
Descriptors: Testing, Planning, Heuristics, Algorithms
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Changhao Liang; Peixuan Jiang; Kensuke Takii; Hiroaki Ogata – Australasian Journal of Educational Technology, 2025
Collaborative learning in tertiary education faces challenges such as limited teacher intervention and effective student pairing. This study addresses these issues by proposing a data-driven peer recommendation approach enhanced with learner profile visualisation. The system dynamically matches students based on evolving learning profiles, using…
Descriptors: Cooperative Learning, Peer Relationship, College Students, Peer Evaluation
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Susan Gardner Archambault – Information and Learning Sciences, 2024
Purpose: Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts' insights and perceptions of the…
Descriptors: Algorithms, Literacy, Artificial Intelligence, Mathematics Instruction
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