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Areej ElSayary, Editor – IGI Global, 2025
By creating specific prompts, educators can harness the power of AI models to generate tailored content, provide instant feedback, and simulate real-world scenarios for deeper learning engagement. Whether it's creating personalized lesson plans, generating creative writing prompts, or assisting with problem-solving exercises, generative AI creates…
Descriptors: Prompting, Engineering, Artificial Intelligence, Technology Uses in Education
Sebrechts, Marc M.; Schooler, Lael J. – Collegiate Microcomputer, 1987
Describes the development of an artificial intelligence system called GIDE that analyzes student errors in statistics problems by inferring the students' intentions. Learning strategies involved in problem solving are discussed and the inclusion of goal structures is explained. (LRW)
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Diagnostic Teaching, Inferences
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Lieberman, Henry – Instructional Science, 1986
Describes a programming environment called Tinker, in which a beginning programmer presents examples to the machine, distinguishing accidental and essential aspects of the examples. Examples of programming in Tinker are presented in which programmers demonstrate how to handle specific examples and the machine formulates a procedure for handling…
Descriptors: Artificial Intelligence, Decision Making, Educational Environment, Feedback
Horak, Willis J. – 1991
Metacognitive skills may be defined in a variety of ways. Generally, these ways all apply to people's thinking about their own personal thinking. This research study analyzed students' interactions to computer programs to assess their metacognitive skills. The metacognitive skills assessed were: (1) planning a course of action; (2) monitoring the…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Learning Strategies, Metacognition
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Ploetzner, Rolf; And Others – European Journal of Psychology of Education, 1990
Discusses the artificial-intelligence-based microworld DiBi and MULEDS, a multilevel diagnosis system. Developed to adapt tutoring style to the individual learner. Explains that DiBi sets up a learning environment, and simulates elastic impacts as a subtopic of classical mechanics, and supporting reasoning on different levels of mental domain…
Descriptors: Artificial Intelligence, Computer Uses in Education, Educational Technology, Learning Strategies
White, Barbara Y.; Frederiksen, John R. – 1986
This report discusses the importance of presenting qualitative, causally consistent models in the initial stages of learning so that students can gain an understanding of basic electrical circuit concepts and principles that builds on their preexisting ways of reasoning about physical phenomena, and it argues that tutoring environments must help…
Descriptors: Artificial Intelligence, Cognitive Processes, Electric Circuits, Experiential Learning
Pirie, Susan; Kieren, Thomas – 1990
There has been considerable interest in mathematical understanding. Both those attempting to build, and those questioning the possibility of building intelligent artificial tutoring systems, struggle with the notions of mathematical understanding. The purpose of this essay is to show a transcendently recursive theory of mathematical understanding…
Descriptors: Artificial Intelligence, Cognitive Development, Elementary School Mathematics, Elementary Secondary Education
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Rumelhart, David E.; Zipser, David – Cognitive Science, 1985
Reports results of studies with an unsupervised learning paradigm called competitive learning which is examined using computer simulation and formal analysis. When competitive learning is applied to parallel networks of neuron-like elements, many potentially useful learning tasks can be accomplished. (Author)
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Simulation, Input Output
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Langley, Pat – Cognitive Science, 1985
Examines processes by which general but weak search methods are transformed into powerful, domain-specific search strategies by classifying types of heuristics learning that can occur and components that contribute to such learning. A learning system--SAGE.2--and its structure, behavior in different domains, and future directions are explored. (36…
Descriptors: Artificial Intelligence, Computer Software, Design, Heuristics
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Steinberg, Esther R.; And Others – Journal of Educational Computing Research, 1986
This study was conducted to determine whether students would use a computer-presented organizational/memory tool as an aid in problem solving, and whether and how locus of control would affect tool use and problem-solving performance. Learners did use the tools, which were most effective in the learner control with feedback condition. (MBR)
Descriptors: Artificial Intelligence, Feedback, Higher Education, Learning Strategies