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Sriram Sampath – Higher Education for the Future, 2025
Artificial intelligence (AI) has been put forth as a technological innovation which can change the way in which healthcare will be delivered in the near future. AI developers plan to deploy tools that will aid diagnosis, improve therapy, minimize errors, increase safety, and optimize systems and bring down costs. In addition, a paradigmatic shift…
Descriptors: Artificial Intelligence, Health Services, Technological Advancement, Innovation
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Kyeng Gea Lee; Mark J. Lee; Soo Jung Lee – International Journal of Technology in Education and Science, 2024
Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, textbased questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of…
Descriptors: Artificial Intelligence, Computer Software, Biology, Science Instruction
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Chakraborty, Udit Kr.; Konar, Debanjan; Roy, Samir; Choudhury, Sankhayan – Education and Information Technologies, 2016
Evaluating Learners' Response in an e-Learning environment has been the topic of current research in areas of Human Computer Interaction, e-Learning, Education Technology and even Natural Language Processing. The current paper presents a twofold strategy to evaluate single word response of a learner in an e-Learning environment. The response of…
Descriptors: Spelling, Electronic Learning, Student Reaction, Error Patterns
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Ohlsson, Stellan – International Journal of Artificial Intelligence in Education, 2016
The ideas behind the constraint-based modeling (CBM) approach to the design of intelligent tutoring systems (ITSs) grew out of attempts in the 1980's to clarify how declarative and procedural knowledge interact during skill acquisition. The learning theory that underpins CBM was based on two conceptual innovations. The first innovation was to…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Models, Learning Theories
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Sun, Wei; And Others – Journal of the American Society for Information Science, 1992
Identifies types and distributions of errors in text produced by optical character recognition (OCR) and proposes a process using machine learning techniques to recognize and correct errors in OCR texts. Results of experiments indicating that this strategy can reduce human interaction required for error correction are reported. (25 references)…
Descriptors: Artificial Intelligence, Automation, Character Recognition, Error Correction
Soloway, Elliot; And Others – 1982
This report examines the features and performance of the BUG-FINDing component of MENO-II, a computer-based tutor for beginning PASCAL programming students. A discussion of the use of artificial intelligence techniques is followed by a summary of the system status and objectives. The two main components of MENO-II are described, beginning with the…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Programs, Computer Science Education
Johnson, W. Lewis; Soloway, Elliot – 1983
This report describes PROUST, a computer-based system for online analyses and understanding of PASCAL programs written by novice programmers, which takes as input a program and a non-algorithmic description of the program requirements and finds the most likely mapping between the requirements and the code. Both the theory and processing techniques…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Oriented Programs, Computer Programs