Educational policy as predictor of computational thinking: A supervised machine learning approach.
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem‐solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the inf...
| Publicado en: | Journal of Computer Assisted Learning Vol. 40; no. 6; pp. 2872 - 2886 |
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| Autores principales: | , , , |
| Formato: | algorithm pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Dec2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180899673&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180899673 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Dec2024 vid: 40 iid: 6 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 180899673 178520760 180899673 180899673 10.1111/jcal.13041 180899673 ppf: 2872 ppct: 14 formats: tig: atl: Educational policy as predictor of computational thinking: A supervised machine learning approach. aug: au: Ezeamuzie, Ndudi O. Leung, Jessica S. C. Fung, Dennis C. L. Ezeamuzie, Mercy N. affil: Faculty of Education, University of Hong Kong, Pokfulam, Hong Kong sug: subj: Bioinformatics Machine Learning School Policies Technology Policy Making Autonomy Human Schools, Middle Students, Middle School Models, Educational Professional Autonomy Data Mining Conceptual Framework Rasch Analysis Pearson's Correlation Coefficient Chi Square Test ab: Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem‐solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational policies on computational thinking remains unclear. Objectives: This study examines the impact of basic and technology‐related educational policies on the development of computational thinking. Methods: Using supervised machine learning, the computational thinking achievements of 31,823 eighth graders across nine countries were analysed. Seven rule‐based and tree‐based classification models were generated and triangulated to determine how educational policies predicted students' computational thinking. Results and conclusions: Predictions show that students have a higher propensity to develop computational thinking skills when schools exercise full autonomy in governance and explicitly embed computational thinking in their curriculum. Plans to support students, teachers and schools with technology or introduce 1:1 computing have no discernible predicted influence on students' computational thinking achievement. Implications: Although predictions deduced from these attributes are not generalizable, traces of how educational policies affect computational thinking exist to articulate more fronts for future research on the influence of educational policies on computational thinking. Lay description: What is already known about this topicComputational thinking (CT) is a problem‐solving skill.Inquiries on CT focus on learners' factors such as age, gender and attitudes.Also, the choice of instructional strategies and learning environment influence CT development. What this paper addsArticulated how the wider community structures influence the development of CT.Educational policies affect the development of computational thinking. Implications for practicesStudents have a higher predicted propensity to develop CT when schools exercise full autonomy in governance and embed CT in the curriculum explicitly.Plans to support students, teachers and schools with technology or plans to introduce 1:1 computing have no discernible influence on students' CT. pubtype: Academic Journal doctype: algorithm pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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