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A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling
Picking a career stream profoundly influences people’s abilities in different ways. Nowadays, choosing the correct career stream in advanced education is troublesome, as the number of people wanting to be in specific specializations is growing. Therefore, it is essential to be able to select the app...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280512/ https://www.ncbi.nlm.nih.gov/pubmed/37346546 http://dx.doi.org/10.7717/peerj-cs.1256 |
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author | Alghamdi, Abdulrahman Abdullah |
author_facet | Alghamdi, Abdulrahman Abdullah |
author_sort | Alghamdi, Abdulrahman Abdullah |
collection | PubMed |
description | Picking a career stream profoundly influences people’s abilities in different ways. Nowadays, choosing the correct career stream in advanced education is troublesome, as the number of people wanting to be in specific specializations is growing. Therefore, it is essential to be able to select the appropriate career path. This article proposes a system that can suggest streams in advanced education schools. This system is influenced by agent-based stream proposal systems (ASPS). The proposed system aims to make picking out the correct stream to study at school simpler for an individual. Different streams are evaluated based on seven pre-characterized models. In our system, three unique sorts of tests, learning styles, and coaching were coordinated in a way that caused the system to recognize an individual’s interests and limits to an area of study. A sample of 238 participants was recruited for our questionnaire on accessibility, user-friendliness, accuracy, and satisfaction with the system. The incorporation of learning styles and coaching proved helpful in the study. The reliability and validity were proven in addition to incorporating a thinking-aloud protocol and immediate evaluation in the pre-, during and post-tests. To a large extent, respondents were satisfied with the model, as was revealed in the Likert scale response frequencies and percentages. The proposed system can be applied to undergraduates choosing engineering, medicine, arts and science degrees |
format | Online Article Text |
id | pubmed-10280512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102805122023-06-21 A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling Alghamdi, Abdulrahman Abdullah PeerJ Comput Sci Agents and Multi-Agent Systems Picking a career stream profoundly influences people’s abilities in different ways. Nowadays, choosing the correct career stream in advanced education is troublesome, as the number of people wanting to be in specific specializations is growing. Therefore, it is essential to be able to select the appropriate career path. This article proposes a system that can suggest streams in advanced education schools. This system is influenced by agent-based stream proposal systems (ASPS). The proposed system aims to make picking out the correct stream to study at school simpler for an individual. Different streams are evaluated based on seven pre-characterized models. In our system, three unique sorts of tests, learning styles, and coaching were coordinated in a way that caused the system to recognize an individual’s interests and limits to an area of study. A sample of 238 participants was recruited for our questionnaire on accessibility, user-friendliness, accuracy, and satisfaction with the system. The incorporation of learning styles and coaching proved helpful in the study. The reliability and validity were proven in addition to incorporating a thinking-aloud protocol and immediate evaluation in the pre-, during and post-tests. To a large extent, respondents were satisfied with the model, as was revealed in the Likert scale response frequencies and percentages. The proposed system can be applied to undergraduates choosing engineering, medicine, arts and science degrees PeerJ Inc. 2023-02-22 /pmc/articles/PMC10280512/ /pubmed/37346546 http://dx.doi.org/10.7717/peerj-cs.1256 Text en © 2023 Alghamdi https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Agents and Multi-Agent Systems Alghamdi, Abdulrahman Abdullah A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
title | A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
title_full | A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
title_fullStr | A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
title_full_unstemmed | A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
title_short | A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
title_sort | novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling |
topic | Agents and Multi-Agent Systems |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280512/ https://www.ncbi.nlm.nih.gov/pubmed/37346546 http://dx.doi.org/10.7717/peerj-cs.1256 |
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