research-article

Improvement and Design of Genetic Algorithm in Personalized Test Paper Composition System

Authors:

Liping Ma,

Xun Zhu,

Qian FengAuthors Info & Claims

CSAE '20: Proceedings of the 4th International Conference on Computer Science and Application Engineering

Article No.: 30, Pages 1 - 5

https://doi.org/10.1145/3424978.3425008

Published: 20 October 2020 Publication History

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Abstract

Based on the question of test papers in personalized learning, this paper makes special improvements and designs for the individual genotype, selection, crossover, and mutation processes in traditional genetic algorithms. At the same time, in the design of the fitness function, based on the disadvantages that the dimension cannot be unified when calculating the fitness function by linear weighting method in the traditional literature, a vector distance calculation method was selected to calculate the objective function, which solved the unification of different constraints Questions that differ between dimensions. In addition, based on the problem that duplicate questions may appear in one test paper, this paper designs a deduplication operator and adds it to the step of genetic algorithm.

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Cited By

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Hosny MHayel RAltwaijry N(2023)Composing Multiple Online Exams: The Bees Algorithm SolutionApplied Sciences10.3390/app13231271013:23(12710)Online publication date: 27-Nov-2023
https://doi.org/10.3390/app132312710
Papadimitriou SChrysafiadi KVirvou M(2023)Adaptive Quizzes Using Fuzzy Genetic Algorithm2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345881(1-8)Online publication date: 10-Jul-2023
https://doi.org/10.1109/IISA59645.2023.10345881

Index Terms

Improvement and Design of Genetic Algorithm in Personalized Test Paper Composition System
1. Applied computing
  1. Education
    1. Computer-assisted instruction

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Published In

CSAE '20: Proceedings of the 4th International Conference on Computer Science and Application Engineering

October 2020

1038 pages

ISBN:9781450377720

DOI:10.1145/3424978

Conference Chair:
Ali Emrouznejad,
Program Chair:
Jui-Sheng Rayson Chou

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 October 2020

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CSAE 2020

CSAE 2020: The 4th International Conference on Computer Science and Application Engineering

October 20 - 22, 2020

Sanya, China

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Cited By

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Hosny MHayel RAltwaijry N(2023)Composing Multiple Online Exams: The Bees Algorithm SolutionApplied Sciences10.3390/app13231271013:23(12710)Online publication date: 27-Nov-2023
https://doi.org/10.3390/app132312710
Papadimitriou SChrysafiadi KVirvou M(2023)Adaptive Quizzes Using Fuzzy Genetic Algorithm2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345881(1-8)Online publication date: 10-Jul-2023
https://doi.org/10.1109/IISA59645.2023.10345881

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Real-coded Genetic Algorithm and Application in the Automatic Composing the Test Paper

A dual-population genetic algorithm for adaptive diversity control

An improved genetic algorithm with conditional genetic operators and its application to set-covering problem