Collaborative learning with block-based programming: investigating human-centered artificial intelligence in education.
In this article, we investigate human-centered artificial intelligence (HCAI) in an educational context where pupils used block-based programming in small groups to solve tasks given by the teacher. We used a design-based research approach in which we, together with the teachers, created a maker spa...
| Publicado en: | Behaviour & Information Technology Vol. 41; no. 9; pp. 1830 - 1848 |
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| Autores principales: | , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Jul2022
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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=158633110&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158633110 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0144929X B6Q jtl: Behaviour & Information Technology issn: 0144929X maglogo: Y pubinfo: dt: Jul2022 vid: 41 iid: 9 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 158633110 157166897 158633110 158633110 10.1080/0144929X.2022.2083981 158633110 ppf: 1830 ppct: 18 formats: tig: atl: Collaborative learning with block-based programming: investigating human-centered artificial intelligence in education. aug: au: Andersen, Renate Mørch, Anders I. Litherland, Kristina Torine affil: Dept. of Primary and Secondary Teacher Education, Oslo Metropolitan University, Oslo, Norway sug: subj: Artificial Intelligence Learning Methods Software Human ab: In this article, we investigate human-centered artificial intelligence (HCAI) in an educational context where pupils used block-based programming in small groups to solve tasks given by the teacher. We used a design-based research approach in which we, together with the teachers, created a maker space for explorative science learning and organised teaching interventions wherein the pupils met online three hours a week for 16 weeks for an entire school year. Due to COVID-19, data were collected through Zoom, with collaborative learning situations captured through screen sharing and online communication using webcams. We employed three data analysis techniques: interaction analysis, visual artifact analysis, and thematic analysis. We developed an analytical framework for integration using thematic coding that combined concepts from computer-supported collaborative learning (CSCL) and domain-oriented design environments. We report the following findings: 1) Three types of rules between design units were identified with visual artifact analysis: latent, generic, and domain-specific rules; 2) two types of CSCL artifacts (technology and discussions) were intertwined and developed in parallel, along with a computer-based scaffolding scenario that offloads domain-specific scaffolding from humans to computers. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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