| dc.contributor.author | Štefánik, Michal |
| dc.contributor.author | Nehyba, Jan |
| dc.date.accessioned | 2021-03-19T08:21:13Z |
| dc.date.available | 2021-03-19T08:21:13Z |
| dc.date.issued | 2021-03-18 |
| dc.identifier.uri | http://hdl.handle.net/11372/LRT-3573 |
| dc.description | The database contains annotated reflective sentences, which fall into the categories of reflective writing according to Ullmann's (2019) model. The dataset is ready to replicate these categories' prediction using machine learning. Available from: https://anonymous.4open.science/repository/c856595c-dfc2-48d7-aa3d-0ccc2648c4dc/data |
| dc.language.iso | eng |
| dc.language.iso | ces |
| dc.publisher | Masaryk University, Brno |
| dc.rights | Creative Commons - Attribution 4.0 International (CC BY 4.0) |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ |
| dc.source.uri | https://anonymous.4open.science/repository/c856595c-dfc2-48d7-aa3d-0ccc2648c4dc/data/ |
| dc.subject | reflective writing |
| dc.subject | reflective categories |
| dc.subject | pre-service teachers |
| dc.subject | hand annotation |
| dc.title | Czech and English Reflective Dataset (CEReD) |
| dc.type | corpus |
| metashare.ResourceInfo#ContentInfo.mediaType | text |
| dc.rights.label | PUB |
| has.files | yes |
| branding | LRT + Open Submissions |
| demo.uri | https://anonymous.4open.science/repository/c856595c-dfc2-48d7-aa3d-0ccc2648c4dc/data/sentences/en/val/sentences.tsv |
| contact.person | Michal Štefánik stefanik.m@mail.muni.cz Masaryk University, Brno |
| sponsor | Masarykova univerzita MUNI/A/1238/2019 Analýza reflektivních deníků studentů učitelství nationalFunds |
| size.info | 6777 sentences |
| files.size | 3119186 |
| files.count | 2 |
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- Name
- CEReD.zip
- Size
- 2.89 MB
- Format
- application/zip
- Description
- Archive containing Czech and English reflective sentences for classification, together with its original reflective diaries.
- MD5
- a583d362b9116dfec46eee120b878838
- Name
- diary_stats.tsv
- Size
- 81.83 KB
- Format
- Unknown
- Description
- Diaries statistics. See README in the attached archive for details
- MD5
- a52b61537c155d28bd5d8f066161b6a3