Paper
Artificial Intelligence and Science Education
Published Apr 1, 1987 · R. Good
Journal of Research in Science Teaching
28
Citations
1
Influential Citations
Abstract
Artificial intelligence (AI) is defined and related to intelligent computer-assisted instruction (ICAI) and science education. Modeling the student, the teacher, and the natural environment are discussed as important parts of ICAI and the concept of “microworlds” as a powerful tool for science education is presented. Optimistic predictions about ICAI are tempered with the complex, persistent problems of: 1) teaching and learning as a soft or fuzzy knowledge base, 2) natural language processing, and 3) machine learning. The importance of accurate diagnosis of a student's learning state, including misconceptions and naive theories about nature, is stressed and related to the importance of accurate diagnosis by a physician. Based on the cognitive science/AI paradigm, a revised model of the well-known Karplus/Renner learning cycle is proposed.
AI can enhance science education by modeling students, teachers, and the natural environment, but challenges remain in teaching and learning with a fuzzy knowledge base, natural language processing, and machine learning.
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