The post-digital era is characterized by the vast presence of platforms imposing their digital affordances and algorithmic control on our behavior. This environment is challenging education and training, with implications for digital and transmedial literacy. Investigating instructional methodologies is crucial to foster critical comprehension of such novel informational environments. The argument maps (AM), which were first created and evaluated in static information contexts (analogical/old web), could be useful in the emergence of dynamic (post-digital) textual forms. The current paper describes a comprehensive literature review based on the assumptions above. We looked into state of the art in research on using AM to handle dynamic information. We found 150 papers using a PRISMA procedure and then examined 25 of them. Our review produced pertinent data about the current state of AM, including the sorts of texts on which they are used and the tools (especially digital and AI-based) that have been employed. Our research lays the groundwork for teaching the literacies needed in new informational settings, such as multimodal, dynamic, algorithmic, and data-driven contexts, with a specific focus on AM as an effective mediational tool. This Zenodo record presents the full dataset composed of the following sheets: 1.Codebook 2. Italian Journals 3. List of articles extracted from SCOPUS 4. List of articles extracted from ERIC 5. List of articles extracted from WOS 6. List of articles extracted from DOAJ 7. PRISMA workflow 8. Analysis - First Level (classification of 25 articles selected) 9. Analysis - Second Level (List of 19 articles selected) 10. Final Dataset 11. Interrater Agreement. As for the Keywords' Map, a primo file .txt displays the text over which basis was performed the keyword maps analysis. The second .txt file shows notes relating to the analysis procedures using the software VOS-Viewer http://www.vosviewer.com/

Argument maps as tools to support the development of new media literacies: a systematic review. [Zenodo Data set]

Francesca Crudele
Data Curation
;
Juliana E. Raffaghelli
Supervision
2023

Abstract

The post-digital era is characterized by the vast presence of platforms imposing their digital affordances and algorithmic control on our behavior. This environment is challenging education and training, with implications for digital and transmedial literacy. Investigating instructional methodologies is crucial to foster critical comprehension of such novel informational environments. The argument maps (AM), which were first created and evaluated in static information contexts (analogical/old web), could be useful in the emergence of dynamic (post-digital) textual forms. The current paper describes a comprehensive literature review based on the assumptions above. We looked into state of the art in research on using AM to handle dynamic information. We found 150 papers using a PRISMA procedure and then examined 25 of them. Our review produced pertinent data about the current state of AM, including the sorts of texts on which they are used and the tools (especially digital and AI-based) that have been employed. Our research lays the groundwork for teaching the literacies needed in new informational settings, such as multimodal, dynamic, algorithmic, and data-driven contexts, with a specific focus on AM as an effective mediational tool. This Zenodo record presents the full dataset composed of the following sheets: 1.Codebook 2. Italian Journals 3. List of articles extracted from SCOPUS 4. List of articles extracted from ERIC 5. List of articles extracted from WOS 6. List of articles extracted from DOAJ 7. PRISMA workflow 8. Analysis - First Level (classification of 25 articles selected) 9. Analysis - Second Level (List of 19 articles selected) 10. Final Dataset 11. Interrater Agreement. As for the Keywords' Map, a primo file .txt displays the text over which basis was performed the keyword maps analysis. The second .txt file shows notes relating to the analysis procedures using the software VOS-Viewer http://www.vosviewer.com/
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3503433
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