Experts Speak Out About Artificial Intelligence in Education: Second of Two Panel Roundtables

Hurlburt, George; Reisman, Sorel

doi:10.1109/mc.2023.3334798

Computer

2024

DOI: 10.1109/mc.2023.3334798

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Experts Speak Out About Artificial Intelligence in Education: Second of Two Panel Roundtables

George Hurlburt,

Sorel Reisman

Abstract: his is the second of two virtual roundtables (VRTs) on artificial intelligence (AI) in education. The first VRT explored the need for critical thinking among both educators and those educated. This panel examines some of the fundamentals underlying the use of AI in education. As a reminder, our participants are › George Strawn, director emeritus of the Board on Research Data and Information, National Academy of Sciences › George K. Thiruvathukal, chairperson,

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Error analysis of machine learning methods as the educational background for its use skills formation

Slavutskaya,

Slavutskii

2024

Vestnik of Minin University

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Introduction. Machine learning methods and elements of artificial intelligence are used to analyze random data, processes and signals. The study of relevant tools is already included in the various levels curricula. The purpose of the study is to demonstrate, using examples available to students of various specialties, that the error analysis of machine learning methods in solving specific tasks can be the basis in the educational process for the skills formation of using artificial intelligence elements.Materials and Methods. For processing random signals and data, widely available software is used: Microsoft Excel for preparing training and test samples, the Deductor analytical platform for implementing machine learning algorithms. As an example, quasi-harmonic signals with random parameters are processed for technical specialties, and the results of psycho diagnostics are used to process multidimensional random data.Results. As a typical solution of approximation technical problems, direct propagation neural network errors in using to determine random signal parameters are analyzed. As a solution of classification problems, multidimensional random data with different dimensions were processed using neural networks and the "decision tree" method. The advantages of the combined use of these two machine learning methods are analyzed. These examples and their analysis were tested in classes with university students in the disciplines of "Digital Signal Processing" and "Fundamentals of Statistics".Discussion and Conclusions. The statistical features of the obtained results, the possibilities of reducing the training sample and selective analysis of multidimensional random data are discussed. It is shown that an adequate assessment of the machine learning methods errors can significantly expand the possibilities of their application, and can be the basis for the formation of skills for their use.

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Error analysis of machine learning methods as the educational background for its use skills formation

Slavutskaya,

Slavutskii

2024

Vestnik of Minin University

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Experts Speak Out About Artificial Intelligence in Education: Second of Two Panel Roundtables

Cited by 1 publication

References 1 publication

Error analysis of machine learning methods as the educational background for its use skills formation

Error analysis of machine learning methods as the educational background for its use skills formation

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