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Venkataraman Balaji; Betty Obura Ogange; Tony Mays – Journal of Learning for Development, 2025
Artificial intelligence (AI) is rapidly transforming various sectors, including education. One of the most promising applications of AI in education is in the development and adaptation of Open Educational Resources (OER). COL's Teacher-in the-Loop (TiL-AI) initiative empowers teachers and TVET trainers across the Commonwealth to leverage…
Descriptors: Artificial Intelligence, Open Educational Resources, Teacher Empowerment, Relevance (Education)
Tingting Li; Kevin Haudek; Joseph Krajcik – Journal of Science Education and Technology, 2025
Scientific modeling is a vital educational practice that helps students apply scientific knowledge to real-world phenomena. Despite advances in AI, challenges in accurately assessing such models persist, primarily due to the complexity of cognitive constructs and data imbalances in educational settings. This study addresses these challenges by…
Descriptors: Artificial Intelligence, Scientific Concepts, Models, Automation
Kai Guo; Yuchun Zhong; Danling Li; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
This study proposed a novel approach to classroom debates, in which chatbots that are able to engage in argumentative dialogues are adopted to facilitate students' debate preparation. The approach comprised three stages: first, students interacted with a chatbot named Argumate to help them generate ideas; second, students discussed the ideas with…
Descriptors: Foreign Countries, Undergraduate Students, Debate, Persuasive Discourse
Kashyap, Ramgopal, Ed.; Kumar, A. V. Senthil, Ed. – IGI Global, 2020
Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing.…
Descriptors: Artificial Intelligence, Man Machine Systems, Video Technology, Computer Uses in Education
Jiangyue Liu; Siran Li; Qianyan Dong – Journal of Educational Computing Research, 2024
The emergence of Generative Artificial Intelligence (GAI) has caused significant disruption to the traditional educational teaching ecosystem. GAI possesses remarkable capabilities in generating human-like text and boasts an extensive knowledge repository, thereby paving the way for potential collaboration with humans. However, current research on…
Descriptors: Artificial Intelligence, Learning Analytics, Computer Uses in Education, Instructional Design
José Alexandre de Carvalho Gonçalves, Editor; José Luís Sousa de Magalhães Lima, Editor; João Paulo Coelho, Editor; Francisco José García-Peñalvo, Editor; Alicia García-Holgado, Editor – Lecture Notes in Educational Technology, 2024
This proceedings volume presents outstanding advances, with a multidisciplinary perspective, in the technological ecosystems that support Knowledge Society building and development. With its learning technology-based focus using a transversal approach, TEEM is divided into thematic and highly cohesive tracks, each of which is oriented to a…
Descriptors: Educational Assessment, Man Machine Systems, Electronic Learning, Computer Uses in Education
Schleicher, Andreas; Achiron, Marilyn; Burns, Tracey; Davis, Cassandra; Tessier, Rebecca; Chambers, Nick – OECD Publishing, 2019
This report, the product of a collaboration between the Organisation for Economic Co-operation and Development (OECD) and the UK-based charity, Education and Employers, offers a glimpse of how children see their future, and the forces that, if properly understood and harnessed, will drive them forward to realise their dreams. Through concerted…
Descriptors: Educational Trends, Trend Analysis, Computer Uses in Education, Artificial Intelligence
Fiebrink, Rebecca – ACM Transactions on Computing Education, 2019
This article aims to lay a foundation for the research and practice of machine learning education for creative practitioners. It begins by arguing that it is important to teach machine learning to creative practitioners and to conduct research about this teaching, drawing on related work in creative machine learning, creative computing education,…
Descriptors: Artificial Intelligence, Man Machine Systems, Population Groups, Creativity
Ramanarayanan, Vikram; Lange, Patrick; Evanini, Keelan; Molloy, Hillary; Tsuprun, Eugene; Qian, Yao; Suendermann-Oeft, David – ETS Research Report Series, 2017
Predicting and analyzing multimodal dialog user experience (UX) metrics, such as overall call experience, caller engagement, and latency, among other metrics, in an ongoing manner is important for evaluating such systems. We investigate automated prediction of multiple such metrics collected from crowdsourced interactions with an open-source,…
Descriptors: Automation, Prediction, Man Machine Systems, Open Source Technology
Snyder, Robin M. – Association Supporting Computer Users in Education, 2015
The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Computational Linguistics
Worsley, Marcelo; Blikstein, Paulo – Journal of Learning Analytics, 2014
Learning analytics and educational data mining are introducing a number of new techniques and frameworks for studying learning. The scalability and complexity of these novel techniques has afforded new ways for enacting education research and has helped scholars gain new insights into human cognition and learning. Nonetheless, there remain some…
Descriptors: Data Analysis, Data Collection, Engineering, Design
Peer reviewedSelnow, Gary W. – American Behavioral Scientist, 1988
Asks whether the computer is another channel of communication, if its interactive qualities make it an information source, or if it is an undefined hybrid. Concludes that computers are neither the medium nor the source but will in the future provide the possibility of a sophisticated interaction between human intelligence and artificial…
Descriptors: Artificial Intelligence, Computer Uses in Education, Computers, Cybernetics
Peer reviewedMandl, Heinz, Ed. – International Journal of Educational Research, 1988
Issues connected with knowledge acquisition through the development of complex computer programs--Intelligent Tutoring Systems (ITSs)--are discussed. The components of such a system and its applications are considered, including: elicitation of knowledge, tutoring with incomplete/uncertain knowledge, self-improving tutoring systems, and…
Descriptors: Aptitude Treatment Interaction, Artificial Intelligence, Computer Assisted Instruction, Computer Simulation
Peer reviewedAdams, Dennis M.; Hamm, Mary – Journal of Computers in Mathematics and Science Teaching, 1988
Surveys the current status of artificial intelligence (AI) technology. Discusses intelligent tutoring systems, robotics, and applications for educators. Likens the status of AI at present to that of aviation in the very early 1900s. States that educators need to be involved in future debates concerning AI. (CW)
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Software, Computer Uses in Education
Baylor, Amy L.; Kozbe, Barcin – 1998
This paper describes a Personal Intelligent Mentor (PIM) that facilitates metacognitive development in the domain of solving logic word puzzles. Metacognition is an important aspect for critical thinking skills. High school students must develop logical and critical thinking abilities as a prerequisite for higher-level math and computer…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer System Design, Computer Uses in Education
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