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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
Language: English
Authors: So, Joseph Chi-ho (ORCID 0000-0001-8784-3083), Wong, Adam Ka-lok (ORCID 0000-0001-7288-0199), Tsang, Kia Ho-yin (ORCID 0000-0003-2513-7102), Chan, Ada Pui-ling (ORCID 0000-0001-5546-0838), Wong, Simon Chi-wang (ORCID 0000-0003-3408-9747), Chan, Henry C. B. (ORCID 0000-0001-8024-0597)
Source: Journal of Technology and Science Education. 2023 13(1):104-115.
Availability: Journal of Technology and Science Education. ESEIAAT, Department of Projectes d'Enginyeria c/Colom 11, 08222 Terrassa, Spain. e-mail: info@jotse.org; e-mail: info@omniascience.com; Web site: http://www.jotse.org/index.php/jotse
Peer Reviewed: Y
Page Count: 12
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Pattern Recognition, Artificial Intelligence, Higher Education, College Students, Competence, Skill Development, Student Characteristics, Expectation, Self Evaluation (Individuals), Data Collection, Programming Languages, Academic Achievement, Classification, Extracurricular Activities, Grade Point Average, Second Language Learning, English (Second Language), Foreign Countries
Geographic Terms: Hong Kong
ISSN: 2014-5349
2013-6374
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.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1391893
Database: ERIC
FullText Text:
  Availability: 0
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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: English
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  Data: <searchLink fieldCode="AR" term="%22So%2C+Joseph+Chi-ho%22">So, Joseph Chi-ho</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8784-3083">0000-0001-8784-3083</externalLink>)<br /><searchLink fieldCode="AR" term="%22Wong%2C+Adam+Ka-lok%22">Wong, Adam Ka-lok</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7288-0199">0000-0001-7288-0199</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tsang%2C+Kia+Ho-yin%22">Tsang, Kia Ho-yin</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2513-7102">0000-0003-2513-7102</externalLink>)<br /><searchLink fieldCode="AR" term="%22Chan%2C+Ada+Pui-ling%22">Chan, Ada Pui-ling</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5546-0838">0000-0001-5546-0838</externalLink>)<br /><searchLink fieldCode="AR" term="%22Wong%2C+Simon+Chi-wang%22">Wong, Simon Chi-wang</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3408-9747">0000-0003-3408-9747</externalLink>)<br /><searchLink fieldCode="AR" term="%22Chan%2C+Henry+C%2E+B%2E%22">Chan, Henry C. B.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8024-0597">0000-0001-8024-0597</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Technology+and+Science+Education%22"><i>Journal of Technology and Science Education</i></searchLink>. 2023 13(1):104-115.
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  Data: Journal of Technology and Science Education. ESEIAAT, Department of Projectes d'Enginyeria c/Colom 11, 08222 Terrassa, Spain. e-mail: info@jotse.org; e-mail: info@omniascience.com; Web site: http://www.jotse.org/index.php/jotse
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  Data: Y
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  Data: 12
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  Data: 2023
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Pattern+Recognition%22">Pattern Recognition</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Competence%22">Competence</searchLink><br /><searchLink fieldCode="DE" term="%22Skill+Development%22">Skill Development</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Expectation%22">Expectation</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Evaluation+%28Individuals%29%22">Self Evaluation (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Collection%22">Data Collection</searchLink><br /><searchLink fieldCode="DE" term="%22Programming+Languages%22">Programming Languages</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Classification%22">Classification</searchLink><br /><searchLink fieldCode="DE" term="%22Extracurricular+Activities%22">Extracurricular Activities</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+Point+Average%22">Grade Point Average</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Hong+Kong%22">Hong Kong</searchLink>
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 2014-5349<br />2013-6374
– Name: Abstract
  Label: Abstract
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  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.
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  Data: 2023
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  Data: EJ1391893
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      – Text: English
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        PageCount: 12
        StartPage: 104
    Subjects:
      – SubjectFull: Pattern Recognition
        Type: general
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Competence
        Type: general
      – SubjectFull: Skill Development
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Expectation
        Type: general
      – SubjectFull: Self Evaluation (Individuals)
        Type: general
      – SubjectFull: Data Collection
        Type: general
      – SubjectFull: Programming Languages
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Classification
        Type: general
      – SubjectFull: Extracurricular Activities
        Type: general
      – SubjectFull: Grade Point Average
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      – SubjectFull: Second Language Learning
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      – SubjectFull: English (Second Language)
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Hong Kong
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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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