Enhancing Historical Education through Research Data - A Poster Presentation
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866902184410480640 |
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| author | Lemaire, Marina Voigt, Anne |
| author_facet | Lemaire, Marina Voigt, Anne |
| contents | <p>Research datasets generated from academic projects are invaluable for addressing specific research questions and form the foundation of scholarly outcomes. These datasets are characterized by high scientific quality, validity, and reproducibility, making them particularly suitable as training materials for historical education. They offer a practical approach to teaching data literacy and research data management skills. These datasets encompass various types of historical research data, such as digitized sources like retro-digitized materials, transcripts, analysis scripts, digital reconstructions, or simulation data (see Cremer et al. 2021, 157–160 [1]). They are available in diverse media formats and represent a wide range of human expressions, including images, audio, and text. This diversity opens up versatile applications in teaching. Depending on the dataset's preparation level (e.g., raw or cleaned data), the teaching objectives, and the methods and tools employed, a broad spectrum of data literacy skills can be imparted. Didactic scenarios range from step-by-step guides to inquiry-based learning, catering to different target audiences and proficiency levels. Datasets can be annotated, cleaned, transformed, interpreted, analyzed, visualized, and enriched with standardized data. Scripts enable data queries, comparisons, integration, or in-depth modeling. Students learn not only how to handle data processing tools but also essential processes like data cleaning, enrichment, standardization, and analysis. These skills are relevant for both data-driven and traditional research approaches. Working with real research data also fosters critical reflection on digital methods and their application to historical inquiries. For educators, these datasets are a valuable resource, offering high-quality, adaptable teaching materials that can be integrated into various course formats. The assured scientific quality of the data facilitates the achievement of teaching objectives, as both educators and students know exactly what they are working with. Additionally, the time-consuming creation of custom training datasets is eliminated. Didactic guidelines simplify the preparation and execution of data-related learning units, providing flexibility to adapt to different target groups and teaching scenarios. Objective The Task Area "Data Literacy" of NFDI4Memory aims to promote the use of research data in historical science education by compiling didactically designed teaching scenarios and making them available to the community as Open Educational Resources (OER) with a DOI. These teaching sketches are intended to provide educators with didactic inspiration and a pool of ideas for integrating data literacy into their teaching. To achieve this, a template has been developed to capture essential information and metadata about the dataset and the didactic scenario. The template includes fields for dataset description (e.g., title, authors, publication date, PID, license, discipline, methods, data formats) and the content and context of the data's creation. In a second step, at least one potential teaching scenario is outlined, including fields for intended learning objectives, digital methods used, technical requirements, preparatory activities, prior knowledge, and a flowchart of planned teaching methods and tasks. The elaborated teaching sketches and dataset descriptions are digitally recorded, and their structured data is transferred to the 4Memory HISTOCAT , where they are made searchable via filters. The Poster The poster introduces the project idea, explains the benefits for the target groups, presents an example of a didactically elaborated scenario based on an existing real dataset, showcases the publication platform, and encourages educators to submit additional teaching scenarios.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16735783 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Enhancing Historical Education through Research Data - A Poster Presentation Lemaire, Marina Voigt, Anne NFDI4Memory Data Literacy OER Teaching Material Dataset <p>Research datasets generated from academic projects are invaluable for addressing specific research questions and form the foundation of scholarly outcomes. These datasets are characterized by high scientific quality, validity, and reproducibility, making them particularly suitable as training materials for historical education. They offer a practical approach to teaching data literacy and research data management skills. These datasets encompass various types of historical research data, such as digitized sources like retro-digitized materials, transcripts, analysis scripts, digital reconstructions, or simulation data (see Cremer et al. 2021, 157–160 [1]). They are available in diverse media formats and represent a wide range of human expressions, including images, audio, and text. This diversity opens up versatile applications in teaching. Depending on the dataset's preparation level (e.g., raw or cleaned data), the teaching objectives, and the methods and tools employed, a broad spectrum of data literacy skills can be imparted. Didactic scenarios range from step-by-step guides to inquiry-based learning, catering to different target audiences and proficiency levels. Datasets can be annotated, cleaned, transformed, interpreted, analyzed, visualized, and enriched with standardized data. Scripts enable data queries, comparisons, integration, or in-depth modeling. Students learn not only how to handle data processing tools but also essential processes like data cleaning, enrichment, standardization, and analysis. These skills are relevant for both data-driven and traditional research approaches. Working with real research data also fosters critical reflection on digital methods and their application to historical inquiries. For educators, these datasets are a valuable resource, offering high-quality, adaptable teaching materials that can be integrated into various course formats. The assured scientific quality of the data facilitates the achievement of teaching objectives, as both educators and students know exactly what they are working with. Additionally, the time-consuming creation of custom training datasets is eliminated. Didactic guidelines simplify the preparation and execution of data-related learning units, providing flexibility to adapt to different target groups and teaching scenarios. Objective The Task Area "Data Literacy" of NFDI4Memory aims to promote the use of research data in historical science education by compiling didactically designed teaching scenarios and making them available to the community as Open Educational Resources (OER) with a DOI. These teaching sketches are intended to provide educators with didactic inspiration and a pool of ideas for integrating data literacy into their teaching. To achieve this, a template has been developed to capture essential information and metadata about the dataset and the didactic scenario. The template includes fields for dataset description (e.g., title, authors, publication date, PID, license, discipline, methods, data formats) and the content and context of the data's creation. In a second step, at least one potential teaching scenario is outlined, including fields for intended learning objectives, digital methods used, technical requirements, preparatory activities, prior knowledge, and a flowchart of planned teaching methods and tasks. The elaborated teaching sketches and dataset descriptions are digitally recorded, and their structured data is transferred to the 4Memory HISTOCAT , where they are made searchable via filters. The Poster The poster introduces the project idea, explains the benefits for the target groups, presents an example of a didactically elaborated scenario based on an existing real dataset, showcases the publication platform, and encourages educators to submit additional teaching scenarios.</p> |
| title | Enhancing Historical Education through Research Data - A Poster Presentation |
| topic | NFDI4Memory Data Literacy OER Teaching Material Dataset |
| url | https://doi.org/10.5281/zenodo.16735783 |