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SOME PATTERN RECOGNITIONS FOR A RECOMMENDATION FRAMEWORK FOR HIGHER EDUCATION STUDENTS' GENERIC COMPETENCE DEVELOPMENT USING MACHINE LEARNING.

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Title: SOME PATTERN RECOGNITIONS FOR A RECOMMENDATION FRAMEWORK FOR HIGHER EDUCATION STUDENTS' GENERIC COMPETENCE DEVELOPMENT USING MACHINE LEARNING.
Authors: Chi-ho So, Joseph1 joseph.so@cpce-polyu.edu.hk, Ka-lok Wong, Adam1 adam.wong@cpce-polyu.edu.hk, Kia Ho-yin Tsang1 kia.tsang@speed-polyu.edu.hk, Pui-ling Chan, Ada2 ada.chan@cpce-polyu.edu.hk, Chi-wang Wong, Simon1 simon.wong@cpce-polyu.edu.hk, Chan, Henry C. B.3 henry.chan.comp@polyu.edu.hk
Source: Journal of Technology & Science Education. 2023, Vol. 13 Issue 1, p104-115. 12p.
Subject Terms: *Machine learning, *Education students, *Higher education, *Student activities, Pattern recognition systems, Python programming language
Abstract: The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic competencies. The gap between the higher education students' generic competence development and their current statuses such as their academic performance and their student activity involvement was incorporated into the framework to come up with a recommendation for the student activities that lead to their generic competence development. For the formulation of the recommendation framework, the data mining tool Orange with some programming in Python and machine learning models was applied on 14,556 students' activity and academic records in the case higher education institution to find out three major types of patterns between the students' participation of the student activities and (1) their academic performance change, (2) their programmes of studies, and (3) their English results in the public examination. These findings are also discussed in this paper. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Technology & Science Education is the property of Omnia Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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PubType: Academic Journal
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  Data: SOME PATTERN RECOGNITIONS FOR A RECOMMENDATION FRAMEWORK FOR HIGHER EDUCATION STUDENTS' GENERIC COMPETENCE DEVELOPMENT USING MACHINE LEARNING.
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  Data: <searchLink fieldCode="AR" term="%22Chi-ho+So%2C+Joseph%22">Chi-ho So, Joseph</searchLink><relatesTo>1</relatesTo><i> joseph.so@cpce-polyu.edu.hk</i><br /><searchLink fieldCode="AR" term="%22Ka-lok+Wong%2C+Adam%22">Ka-lok Wong, Adam</searchLink><relatesTo>1</relatesTo><i> adam.wong@cpce-polyu.edu.hk</i><br /><searchLink fieldCode="AR" term="%22Kia+Ho-yin+Tsang%22">Kia Ho-yin Tsang</searchLink><relatesTo>1</relatesTo><i> kia.tsang@speed-polyu.edu.hk</i><br /><searchLink fieldCode="AR" term="%22Pui-ling+Chan%2C+Ada%22">Pui-ling Chan, Ada</searchLink><relatesTo>2</relatesTo><i> ada.chan@cpce-polyu.edu.hk</i><br /><searchLink fieldCode="AR" term="%22Chi-wang+Wong%2C+Simon%22">Chi-wang Wong, Simon</searchLink><relatesTo>1</relatesTo><i> simon.wong@cpce-polyu.edu.hk</i><br /><searchLink fieldCode="AR" term="%22Chan%2C+Henry+C%2E+B%2E%22">Chan, Henry C. B.</searchLink><relatesTo>3</relatesTo><i> henry.chan.comp@polyu.edu.hk</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Technology+%26+Science+Education%22">Journal of Technology & Science Education</searchLink>. 2023, Vol. 13 Issue 1, p104-115. 12p.
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  Data: *<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Education+students%22">Education students</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+activities%22">Student activities</searchLink><br /><searchLink fieldCode="DE" term="%22Pattern+recognition+systems%22">Pattern recognition systems</searchLink><br /><searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic competencies. The gap between the higher education students' generic competence development and their current statuses such as their academic performance and their student activity involvement was incorporated into the framework to come up with a recommendation for the student activities that lead to their generic competence development. For the formulation of the recommendation framework, the data mining tool Orange with some programming in Python and machine learning models was applied on 14,556 students' activity and academic records in the case higher education institution to find out three major types of patterns between the students' participation of the student activities and (1) their academic performance change, (2) their programmes of studies, and (3) their English results in the public examination. These findings are also discussed in this paper. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Technology & Science Education is the property of Omnia Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3926/jotse.1707
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        Text: English
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      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Education students
        Type: general
      – SubjectFull: Higher education
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      – SubjectFull: Student activities
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      – SubjectFull: Pattern recognition systems
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      – SubjectFull: Python programming language
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      – TitleFull: SOME PATTERN RECOGNITIONS FOR A RECOMMENDATION FRAMEWORK FOR HIGHER EDUCATION STUDENTS' GENERIC COMPETENCE DEVELOPMENT USING MACHINE LEARNING.
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            NameFull: Chi-ho So, Joseph
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            NameFull: Ka-lok Wong, Adam
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            NameFull: Pui-ling Chan, Ada
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            NameFull: Chi-wang Wong, Simon
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              Text: 2023
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