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Sidney was displeased by the “crass commercialization” of teaching machines. He objected to this use of teaching machines feeling they had a lack of questioning about basic theory. He also felt that their full potential was not being fully utilized. He felt that programmed texts were “no more learning than simple silent reading”. [4]
The term machine learning was coined in 1959 by Arthur Samuel, an IBM employee and pioneer in the field of computer gaming and artificial intelligence. [8] [9] The synonym self-teaching computers was also used in this time period.
The ideas of teaching machines and programmed learning provided the basis for later ideas such as open learning and computer-assisted instruction. Illustrations of early teaching machines can be found in the 1960 sourcebook, Teaching Machines and Programmed Learning. [12] An "Autotutor" was demonstrated at the 1964 World's Fair. [13]
The concept of intelligent machines for instructional use date back as early as 1924, when Sidney Pressey of Ohio State University created a mechanical teaching machine to instruct students without a human teacher. [5] [6] His machine resembled closely a typewriter with several keys and a window that provided the learner with questions. The ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]
Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate the interaction with the learner and deliver customized resources and learning activities to address the unique needs of each learner. [1]
Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns in the data, or when the data itself is ...