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Xue, Kang; Huggins-Manley, Anne Corinne; Leite, Walter – Educational and Psychological Measurement, 2022
In data collected from virtual learning environments (VLEs), item response theory (IRT) models can be used to guide the ongoing measurement of student ability. However, such applications of IRT rely on unbiased item parameter estimates associated with test items in the VLE. Without formal piloting of the items, one can expect a large amount of…
Descriptors: Virtual Classrooms, Artificial Intelligence, Item Response Theory, Item Analysis
Kerimbayev, Nurassyl; Beisov, Nurbol; Kovtun, ?natoly; Nurym, Nurdaulet; Akramova, Aliya – Education and Information Technologies, 2020
Nowadays robotics is one of promising avenues in the sphere of emerging technologies. In the teaching/learning environment we deal with educational robotics, which is a mixture of theory and practice, knowledge of computer technology, Mathematics and Physics. The two vectors are combined in educational robotics: the educational vector and the…
Descriptors: Robotics, Technology Uses in Education, Educational Technology, Interdisciplinary Approach
Knox, Jeremy; Williamson, Ben; Bayne, Sian – Learning, Media and Technology, 2020
This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…
Descriptors: Data Collection, Data Analysis, Artificial Intelligence, Man Machine Systems
Siegle, Del – Gifted Child Today, 2023
This article explores the potential uses of AI in gifted education programs. Gifted students often have unique learning characteristics and require specialized program services. The use of AI can provide advanced content, personalized learning, creative writing and image manipulation, critical thinking and problem-solving, collaboration, research…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Gifted Education
Shah, Priten – Jossey-Bass, An Imprint of Wiley, 2023
Among teachers, there is a cloud of rumors, confusion, and fear surrounding the rise of artificial intelligence. "AI and the Future of Education" is a timely response to this general state of panic, showing you that AI is a tool to leverage, not a threat to teaching and learning. By understanding what AI is, what it does, and how it can…
Descriptors: Artificial Intelligence, Futures (of Society), Teaching (Occupation), Ethics
American Association of Colleges and Universities, 2024
Humanity is building exciting new partnerships with technology in the artificial intelligence age. Careers and work are rapidly being transformed and many of the jobs of tomorrow have not yet been invented. Students should make it their goal to become skilled in using AI comfortably, effectively, safely and ethically. Learn AI's capabilities and…
Descriptors: College Students, Student Experience, Technology Uses in Education, Artificial Intelligence
Xinghua Wang; Hui Pang; Matthew P. Wallace; Qiyun Wang; Wenli Chen – Computer Assisted Language Learning, 2024
This study investigated the application of an artificial intelligence (AI) coach for second language (L2) learning in a primary school involving 327 participants. In line with Community of Inquiry, learners were expected to perceive social, cognitive, and teaching presences when interacting with the AI coach, which was considered a humanized…
Descriptors: Artificial Intelligence, Second Language Instruction, Second Language Learning, Student Attitudes
Smith, Bevan I.; Chimedza, Charles; Bührmann, Jacoba H. – International Journal of Artificial Intelligence in Education, 2020
Identifying students at risk of failing a course has potential benefits, such as recommending the At-Risk students to various interventions that could improve pass rates. The challenges however, are firstly in measuring how effective these interventions are, i.e. measuring treatment effects, and secondly, to not only predict overall (average)…
Descriptors: Artificial Intelligence, Man Machine Systems, Probability, Scoring
Chen, Fu; Cui, Ying; Chu, Man-Wai – International Journal of Artificial Intelligence in Education, 2020
The purpose of this case study is to demonstrate how to utilize machine learning approaches to analyze student process data for validating and informing digital game-based assessments (DGBAs) with an evidence-centered game design (ECgD). The first analysis was conducted to examine whether students' mastery of the overall skill required by the game…
Descriptors: Game Based Learning, Learning Analytics, Design, Evidence Based Practice
Yanagiura, Takeshi – Community College Research Center, Teachers College, Columbia University, 2020
Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…
Descriptors: Community Colleges, Man Machine Systems, Artificial Intelligence, Prediction
Julia Cambre; Chinmay Kulkarni – Grantee Submission, 2019
When a smart device talks, what should its voice sound like? Voice-enabled devices are becoming a ubiquitous presence in our everyday lives. Simultaneously, speech synthesis technology is rapidly improving, making it possible to generate increasingly varied and realistic computerized voices. Despite the flexibility and richness of expression that…
Descriptors: Assistive Technology, Speech Communication, Computer Use, Man Machine Systems
Pack, Austin; Maloney, Jeffrey – Teaching English with Technology, 2023
With recent public access to large language models via chatbots, the field of language education is seeing unprecedented levels of interest in how AI will affect language learning and teaching. As attention is primarily focused on student misuse of the technology, the potential affordances of generative AI tools may often be overlooked. In this…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Language Acquisition
Yun Dai; Ziyan Lin; Ang Liu; Wenlan Wang – British Journal of Educational Technology, 2024
While AI has become more prevalent in our society than ever, many young learners are found holding various naive, erroneous conceptions of AI due to the influence of their technology and media environments. To address this issue, this study seeks to propose a novel pedagogical solution to improve upper-elementary school students' scientific…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Education, Elementary School Students
Lior Naamati-Schneider; Dorit Alt – Education and Information Technologies, 2024
The integration of ChatGPT into educational systems underscores the critical importance of reevaluating the relevance of digital literacy skills. This study empirically tested, for the first time, the theoretical premise that the use of ChatGPT could render certain digital skills obsolete by assuming competencies that students were previously…
Descriptors: Artificial Intelligence, Handheld Devices, Users (Information), Skill Development
Irene Picton; Christina Clark – National Literacy Trust, 2024
Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The ability of generative-AI tools such as ChatGPT, Gemini and Claude to both 'write' and 'read' texts in a human-like manner means they are set to play an increasingly important role in the literacy lives of children, young people and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education