{"took":1,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":504,"relation":"eq"},"max_score":1.0,"hits":[{"_index":"soda-2026-05-14-06-20-01","_id":"2535.json","_score":1.0,"_ignored":["abstract.pref.raw","abstract.en.raw","abstract.de.raw"],"_source":{ "abstract" : { "pref" : "+++++++++++++++\r\nVersion 2.0.0 of the study is outdated and therefore only available in exceptional cases. Please use the revised version 3.0.0 here. \r\n+++++++++++++++\r\n\r\n\r\nWe carried out an harmonization of the Eurobarometer 2004-2021(spring). This dataset includes 35 single standard Eurobarometers, and morethan 140 variables about EU policies, attitudes towards Europe and the EU, identity, cognitive mobilization, political institutions, socio-political characteristics and partisanship, etc.\r\n\r\nThe harmonization was carried out using existing Eurobarometer datasets published by GESIS. To allow the user to replicate the harmonization and be able to modify some codes if needed, we publish one example of do-file used to pursue the harmonization, as well as the corresponding (harmonized) dataset. The user can find the do-file containing the codes used to modify and clean EB 953 (ZA7783, conducted in spring 2021) according to the harmonization procedure that we followed. Moreover, the user can find the cleaned dataset for EB 953 that was obtained after running the do-file. The files are named “EB 953.do” and “953_new.dta”.\r\n\r\nWe include:\r\n- a harmonized dataset (\"harmonised_EB_2004-2021.dta\"),\r\n- a technical report (\"User Guide Harmonized Eurobarometer 2004-2021\"),\r\n- a summary of the original survey questions corresponding to the variables included in the dataset (\"Trends_EBs_1970-2021.xlsx\"),\r\n- one of the do-files used to carry out the harmonization (“EB 953.do” ),\r\n- one of the datasets used before merging all datasets (“953_new.dta”).", "de" : "+++++++++++++++\r\nVersion 2.0.0 of the study is outdated and therefore only available in exceptional cases. Please use the revised version 3.0.0 here. \r\n+++++++++++++++\r\n\r\n\r\nWe carried out an harmonization of the Eurobarometer 2004-2021(spring). This dataset includes 35 single standard Eurobarometers, and morethan 140 variables about EU policies, attitudes towards Europe and the EU, identity, cognitive mobilization, political institutions, socio-political characteristics and partisanship, etc.\r\n\r\nThe harmonization was carried out using existing Eurobarometer datasets published by GESIS. To allow the user to replicate the harmonization and be able to modify some codes if needed, we publish one example of do-file used to pursue the harmonization, as well as the corresponding (harmonized) dataset. The user can find the do-file containing the codes used to modify and clean EB 953 (ZA7783, conducted in spring 2021) according to the harmonization procedure that we followed. Moreover, the user can find the cleaned dataset for EB 953 that was obtained after running the do-file. The files are named “EB 953.do” and “953_new.dta”.\r\n\r\nWe include:\r\n- a harmonized dataset (\"harmonised_EB_2004-2021.dta\"),\r\n- a technical report (\"User Guide Harmonized Eurobarometer 2004-2021\"),\r\n- a summary of the original survey questions corresponding to the variables included in the dataset (\"Trends_EBs_1970-2021.xlsx\"),\r\n- one of the do-files used to carry out the harmonization (“EB 953.do” ),\r\n- one of the datasets used before merging all datasets (“953_new.dta”).", "en" : "+++++++++++++++\r\nVersion 2.0.0 of the study is outdated and therefore only available in exceptional cases. Please use the revised version 3.0.0 here. \r\n+++++++++++++++\r\n\r\n\r\nWe carried out an harmonization of the Eurobarometer 2004-2021(spring). This dataset includes 35 single standard Eurobarometers, and morethan 140 variables about EU policies, attitudes towards Europe and the EU, identity, cognitive mobilization, political institutions, socio-political characteristics and partisanship, etc.\r\n\r\nThe harmonization was carried out using existing Eurobarometer datasets published by GESIS. To allow the user to replicate the harmonization and be able to modify some codes if needed, we publish one example of do-file used to pursue the harmonization, as well as the corresponding (harmonized) dataset. The user can find the do-file containing the codes used to modify and clean EB 953 (ZA7783, conducted in spring 2021) according to the harmonization procedure that we followed. Moreover, the user can find the cleaned dataset for EB 953 that was obtained after running the do-file. 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\nDer verwendete Datensatz der Exmatrikuliertenbefragung 2014/2017 ist derzeit nicht öffentlich verfügbar. Eine Version zur wissenschaftlichen Nutzung (Scientific Use File) ist derzeit in Erstellung und soll Ende 2021 oder Anfang 2022 über das Forschungsdatenzentrum des DZHW (https://www.fdz.dzhw.eu/de) zur Verfügung gestellt werden.", "de" : "Kommentierte, vollständige Stata-Syntax, die zur Berechnung der publizierten Ergebnisse mit dem Programm Stata notwendig ist.
\nDer verwendete Datensatz der Exmatrikuliertenbefragung 2014/2017 ist derzeit nicht öffentlich verfügbar. Eine Version zur wissenschaftlichen Nutzung (Scientific Use File) ist derzeit in Erstellung und soll Ende 2021 oder Anfang 2022 über das Forschungsdatenzentrum des DZHW (https://www.fdz.dzhw.eu/de) zur Verfügung gestellt werden.", "en" : "Kommentierte, vollständige Stata-Syntax, die zur Berechnung der publizierten Ergebnisse mit dem Programm Stata notwendig ist.
\nDer verwendete Datensatz der Exmatrikuliertenbefragung 2014/2017 ist derzeit nicht öffentlich verfügbar. Eine Version zur wissenschaftlichen Nutzung (Scientific Use File) ist derzeit in Erstellung und soll Ende 2021 oder Anfang 2022 über das Forschungsdatenzentrum des DZHW (https://www.fdz.dzhw.eu/de) zur Verfügung gestellt werden." }, "collections" : [ "Continue without selection" ], "contributions" : [ { "type" : [ "Contribution" ], "agent" : { "type" : [ "Person" ], "uri" : "info:searchapp/vocab/adhoc/TWV5ZXIsIEphc21pbg==", "label" : "Meyer, Jasmin", "affiliation" : { "uri" : "info:searchapp/vocab/adhoc/VW5pdmVyc2l0w6R0IEtvbnN0YW56", "label" : { "pref" : "Universität Konstanz", "de" : "Universität Konstanz", "en" : "Universität Konstanz" } } }, "role" : [ ] }, { "type" : [ "Contribution" ], "agent" : { "type" : [ "Person" ], "uri" : "info:searchapp/vocab/adhoc/TWFudGluZ2VyLCBNYXJh", "label" : "Mantinger, Mara", "affiliation" : { "uri" : "info:searchapp/vocab/adhoc/U3RhdGlzdGlzY2hlcyBMYW5kZXNhbXQgQmFkZW4tV8O8cnR0ZW1iZXJn", "label" : { "pref" : "Statistisches Landesamt Baden-Württemberg", "de" : "Statistisches Landesamt Baden-Württemberg", "en" : "Statistisches Landesamt Baden-Württemberg" } } }, "role" : [ ] } ], "describedBy" : { "uri" : "https://api.vitrine.gesis.org/search/soda/_doc/2252.json", "type" : "ResearchData", "modifiedBy" : { "uri" : "https://searchapp-indexer", "label" : { "pref" : "Searchapp Indexer" }, "dateCreated" : "2026-05-14T06:20:41.058+02:00", "dateModified" : "2026-05-14T06:20:41.058+02:00", "inDataset" : { "uri" : "https://git.gesis.org/datorium/soda-index-data" }, "resultOf" : { "type" : [ "CreateAction" ], "endTime" : "2026-05-14T06:20:41.058+02:00", "instrument" : { "uri" : "https://git.gesis.org/datorium/searchapp-indexer", "type" : [ "SoftwareApplication" ], "label" : "Searchapp Indexer" }, "srcObject" : { "uri" : "https://git.gesis.org/datorium/soda-index-data/-/blob/main/data/2252.json", "type" : [ "DataFeedItem" ], "inDataset" : { "uri" : "https://git.gesis.org/datorium/soda-index-data", "label" : "raw data" } } } } }, "documentId" : "2252", "geographicCoverages" : [ { "geographicCoveragesFree" : { "pref" : "Germany / DE", "de" : "Germany / DE", "en" : "Germany / DE" } } ], "handles" : [ { "type" : "DOI", "notation" : "10.7802/2252", "url" : "https://doi.org/10.7802/2252", "source" : { "uri" : "info:searchapp/vocab/soda", "label" : "SowiDataNet" } } ], "issuers" : [ { "uri" : "info:searchapp/vocab/adhoc/bnVsbA==", "label" : { "pref" : "null", "de" : "null", "en" : "null" } } ], "natureOfContents" : [ { "uri" : "info:searchapp/vocab/researchData", "label" : { "pref" : "researchData", "de" : "researchData", "en" : "researchData" } } ], "publications" : [ { "type" : [ "PublicationEvent" ], "startDate" : "2021" } ], "subjects" : [ { "type" : [ "SubjectHeading" ], "uri" : "info:searchapp/vocab/adhoc/W1NvY2lvbG9neV0=", "notation" : "", "label" : { "pref" : "[Sociology]", "de" : "[Sociology]", "en" : "[Sociology]" } } ], "timeDimensions" : [ { "timeDimensionsFree" : { "pref" : "Längsschnitt (Panelstudie)", "de" : "Längsschnitt (Panelstudie)", "en" : "Longitudinal (panel study)" } } ], "title" : { "pref" : "Code/Syntax: Drehtür-Effekt im deutschen Hochschulsystem? 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We publish the results in a nowcasting fashion on the project’s WebApp (https://dtecbw.de/sparta/). Among other findings, we present the stances expressed toward the main parties and their leading candidates. We also illustrate the salient issues discussed as well as the most frequently used hashtags by the election Twittersphere (for example, all tweets addressing the election and its central actors), political parties, leading candidates, and candidates for a mandate in the state parliament. We also measure the extent of negative campaigning and personalization.\n\nTo enable real-time analyses of the election campaign, we created a dataset with the Twitter/X handles of all candidates for a mandate in the state parliament in August 2023. The dataset contains the Twitter/X handles and additional information about the candidates from six parties: CSU, Bündnis 90/Die Grünen, Freie Wähler, AfD, SPD, and FDP.", "de" : "The research project, SPARTA (Society, Politics, and Risk with Twitter Analysis), funded by dtec.bw (which is funded by the European Union – NextGenerationEU), monitors the 2023 state election campaign in Bavaria live as it unfolds on Twitter/X.\n\nFrom September 4 to the election day on October 8, 2023, we collect and analyze all German-language posts and reposts related to the election and its central actors in real time. We publish the results in a nowcasting fashion on the project’s WebApp (https://dtecbw.de/sparta/). Among other findings, we present the stances expressed toward the main parties and their leading candidates. We also illustrate the salient issues discussed as well as the most frequently used hashtags by the election Twittersphere (for example, all tweets addressing the election and its central actors), political parties, leading candidates, and candidates for a mandate in the state parliament. We also measure the extent of negative campaigning and personalization.\n\nTo enable real-time analyses of the election campaign, we created a dataset with the Twitter/X handles of all candidates for a mandate in the state parliament in August 2023. The dataset contains the Twitter/X handles and additional information about the candidates from six parties: CSU, Bündnis 90/Die Grünen, Freie Wähler, AfD, SPD, and FDP.", "en" : "The research project, SPARTA (Society, Politics, and Risk with Twitter Analysis), funded by dtec.bw (which is funded by the European Union – NextGenerationEU), monitors the 2023 state election campaign in Bavaria live as it unfolds on Twitter/X.\n\nFrom September 4 to the election day on October 8, 2023, we collect and analyze all German-language posts and reposts related to the election and its central actors in real time. We publish the results in a nowcasting fashion on the project’s WebApp (https://dtecbw.de/sparta/). Among other findings, we present the stances expressed toward the main parties and their leading candidates. We also illustrate the salient issues discussed as well as the most frequently used hashtags by the election Twittersphere (for example, all tweets addressing the election and its central actors), political parties, leading candidates, and candidates for a mandate in the state parliament. We also measure the extent of negative campaigning and personalization.\n\nTo enable real-time analyses of the election campaign, we created a dataset with the Twitter/X handles of all candidates for a mandate in the state parliament in August 2023. The dataset contains the Twitter/X handles and additional information about the candidates from six parties: CSU, Bündnis 90/Die Grünen, Freie Wähler, AfD, SPD, and FDP." }, "collectionModes" : [ { "label" : { "pref" : "Eigenständig durchgeführte schriftliche Aufzeichnung:Web-basiert", "de" : "Eigenständig durchgeführte schriftliche Aufzeichnung:Web-basiert", "en" : "Self-administered writings and/or diaries:Web-based" } } ], "collections" : [ "Continue without selection" ], "contributions" : [ { "type" : [ "Contribution" ], "agent" : { "type" : [ "Person" ], "uri" : "info:searchapp/vocab/adhoc/Q2hyaXN0bG1haWVyLCBSYWZhZWw=", "label" : "Christlmaier, Rafael", "affiliation" : { "uri" : "info:searchapp/vocab/adhoc/VW5pdmVyc2l0w6R0IGRlciBCdW5kZXN3ZWhyIE3DvG5jaGVu", "label" : { "pref" : "Universität der Bundeswehr München", "de" : "Universität der Bundeswehr München", "en" : "Universität der Bundeswehr München" } } }, "role" : [ ] }, { "type" : [ "Contribution" ], "agent" : { "type" : [ 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"pref" : "Diese repräsentativen Daten einer Bevölkerungsbefragung sind im Rahmen der Arbeiten der Nachwuchsgruppe \"Mentalitäten im Fluss. Vorstellungswelten in modernen bio-kreislaufbasierten Gesellschaften (flumen)\" erhoben worden. Das Projekt untersuchte von 2019 bis 2025 wie sich die Grundhaltungen, Einstellungen und gemeinsamen Vorstellungswelten von Menschen verändern, wenn sich die Rohstoff- und Energiebasis der Gesellschaft, in der sie leben, weg von fossilen und hin zu bio-basierten Grundstoffen verschiebt. Bio-basierte Kreislaufwirtschaften, so die zentrale Annahme, verlangen und bedingen andere Formen von Zeit- und Zukunftsbewusstsein, Selbst- und Weltverhältnissen, kurz: andere Mentalitäten als fossile Durchflusswirtschaften.\n\nUm diese Mentalitäten zu erfassen, ihre Prägung durch die soziale Position und ihre Zusammenhänge mit Lebensweisen zu untersuchen, enthält die Umfrage drei Themenblöcke: 1. Einstellungen zu allgemeinen sozialen und ökologischen Themen, 2. ausgewählte Alltagspraktiken, aus denen sich auch ein einfacher Co2-Fußabdruck berechnen lässt, sowie 3. eine Vielzahl von sozio-demografischen Merkmalen, welche die Operationalisierung von ökonomischem und kulturellem Kapital und somit die Konstruktion eines differenzierten sozialen Raumes nach Bourdieu erlauben. Zusätzlich wurden Fragen zur Bioökonomie gestellt wie z.B. zur Biolandwirtschaft, Gentechnik und zur Ersetzung von Plastik durch erneuerbare Rohstoffe. Die Daten enthalten auch einige Fragen zur politischen Situation 2021/2022 im Umfeld der Bundestagswahl, aus der die Ampelregierung hervorging, und zur Corona Pandemie, so z.B. zur Akzeptanz von Masken und zu Impfungen.\n\nDie Umfrage wurde telefonisch (n=2000) und online (n=2000) für ganz Deutschland durchgeführt sowie im Frühjahr 2022 postalisch nur für Einwohner:innen von Bioenergiedörfern (n=523).", "de" : "Diese repräsentativen Daten einer Bevölkerungsbefragung sind im Rahmen der Arbeiten der Nachwuchsgruppe \"Mentalitäten im Fluss. Vorstellungswelten in modernen bio-kreislaufbasierten Gesellschaften (flumen)\" erhoben worden. Das Projekt untersuchte von 2019 bis 2025 wie sich die Grundhaltungen, Einstellungen und gemeinsamen Vorstellungswelten von Menschen verändern, wenn sich die Rohstoff- und Energiebasis der Gesellschaft, in der sie leben, weg von fossilen und hin zu bio-basierten Grundstoffen verschiebt. Bio-basierte Kreislaufwirtschaften, so die zentrale Annahme, verlangen und bedingen andere Formen von Zeit- und Zukunftsbewusstsein, Selbst- und Weltverhältnissen, kurz: andere Mentalitäten als fossile Durchflusswirtschaften.\n\nUm diese Mentalitäten zu erfassen, ihre Prägung durch die soziale Position und ihre Zusammenhänge mit Lebensweisen zu untersuchen, enthält die Umfrage drei Themenblöcke: 1. Einstellungen zu allgemeinen sozialen und ökologischen Themen, 2. ausgewählte Alltagspraktiken, aus denen sich auch ein einfacher Co2-Fußabdruck berechnen lässt, sowie 3. eine Vielzahl von sozio-demografischen Merkmalen, welche die Operationalisierung von ökonomischem und kulturellem Kapital und somit die Konstruktion eines differenzierten sozialen Raumes nach Bourdieu erlauben. Zusätzlich wurden Fragen zur Bioökonomie gestellt wie z.B. zur Biolandwirtschaft, Gentechnik und zur Ersetzung von Plastik durch erneuerbare Rohstoffe. Die Daten enthalten auch einige Fragen zur politischen Situation 2021/2022 im Umfeld der Bundestagswahl, aus der die Ampelregierung hervorging, und zur Corona Pandemie, so z.B. zur Akzeptanz von Masken und zu Impfungen.\n\nDie Umfrage wurde telefonisch (n=2000) und online (n=2000) für ganz Deutschland durchgeführt sowie im Frühjahr 2022 postalisch nur für Einwohner:innen von Bioenergiedörfern (n=523).", "en" : "Diese repräsentativen Daten einer Bevölkerungsbefragung sind im Rahmen der Arbeiten der Nachwuchsgruppe \"Mentalitäten im Fluss. Vorstellungswelten in modernen bio-kreislaufbasierten Gesellschaften (flumen)\" erhoben worden. Das Projekt untersuchte von 2019 bis 2025 wie sich die Grundhaltungen, Einstellungen und gemeinsamen Vorstellungswelten von Menschen verändern, wenn sich die Rohstoff- und Energiebasis der Gesellschaft, in der sie leben, weg von fossilen und hin zu bio-basierten Grundstoffen verschiebt. Bio-basierte Kreislaufwirtschaften, so die zentrale Annahme, verlangen und bedingen andere Formen von Zeit- und Zukunftsbewusstsein, Selbst- und Weltverhältnissen, kurz: andere Mentalitäten als fossile Durchflusswirtschaften.\n\nUm diese Mentalitäten zu erfassen, ihre Prägung durch die soziale Position und ihre Zusammenhänge mit Lebensweisen zu untersuchen, enthält die Umfrage drei Themenblöcke: 1. Einstellungen zu allgemeinen sozialen und ökologischen Themen, 2. ausgewählte Alltagspraktiken, aus denen sich auch ein einfacher Co2-Fußabdruck berechnen lässt, sowie 3. eine Vielzahl von sozio-demografischen Merkmalen, welche die Operationalisierung von ökonomischem und kulturellem Kapital und somit die Konstruktion eines differenzierten sozialen Raumes nach Bourdieu erlauben. Zusätzlich wurden Fragen zur Bioökonomie gestellt wie z.B. zur Biolandwirtschaft, Gentechnik und zur Ersetzung von Plastik durch erneuerbare Rohstoffe. 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Additionally, it provides data on 1,345 additional politicians without a twitter account, giving a comprehensive overview over all elected politicians in Germany. This hand-curated dataset not only provides up-to-date information, it also supplements additional variables such as their party affiliation, age or gender. Furthermore, it provides linkages to additional data sources by providing the accounts' Wikidata and Abgeordnetenwatch (Parliamentwatch) IDs. While it does not provide actual tweet data, the data set enables easy access to elected German politicians on Twitter. This research was funded by the Klaus Tschira Foundation (https://www.klaus-tschira-stiftung.de/) as part of the EPINetz Project (https://epinetz.de/).", "de" : "The EPINetz Twitter Politicians Dataset is a comprehensive dataset of 2,811 Twitter accounts of German parliamentarians, ministers, state secretaries, parties and ministries on a state, federal and EU level, now updated until March 2023. Additionally, it provides data on 1,345 additional politicians without a twitter account, giving a comprehensive overview over all elected politicians in Germany. This hand-curated dataset not only provides up-to-date information, it also supplements additional variables such as their party affiliation, age or gender. Furthermore, it provides linkages to additional data sources by providing the accounts' Wikidata and Abgeordnetenwatch (Parliamentwatch) IDs. While it does not provide actual tweet data, the data set enables easy access to elected German politicians on Twitter. This research was funded by the Klaus Tschira Foundation (https://www.klaus-tschira-stiftung.de/) as part of the EPINetz Project (https://epinetz.de/).", "en" : "The EPINetz Twitter Politicians Dataset is a comprehensive dataset of 2,811 Twitter accounts of German parliamentarians, ministers, state secretaries, parties and ministries on a state, federal and EU level, now updated until March 2023. Additionally, it provides data on 1,345 additional politicians without a twitter account, giving a comprehensive overview over all elected politicians in Germany. This hand-curated dataset not only provides up-to-date information, it also supplements additional variables such as their party affiliation, age or gender. Furthermore, it provides linkages to additional data sources by providing the accounts' Wikidata and Abgeordnetenwatch (Parliamentwatch) IDs. While it does not provide actual tweet data, the data set enables easy access to elected German politicians on Twitter. 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dritten Klassen zu untersuchen und Bedingungen zu identifizieren, die einen erfolgreichen Einsatz und die Verstetigung der Schreibförderung besonders begünstigen. In einem Studiendesign mit Wartekontrollgruppe nahmen Lehrkräfte an einer Blended-Learning-Fortbildung teil und führten anschließend ein Training zur Schreibflüssigkeit sowie ein Schreibstrategietraining in ihren dritten Klassen durch. Dabei wurden sie von Multiplikatorinnen und Multiplikatoren begleitet, die den Blended-Learning-Kurs zuvor selbst absolviert hatten. Die Erhebung der Lehrkräftedaten erfolgte mittels Fragebögen, welche neben den schulischen Rahmenbedingungen das Unterrichtshandeln im Schreibunterricht, das selbst eingeschätzte Wissen zur Schreibförderung, Einstellungen zu verschiedenen schreibdidaktischen Maßnahmen, die Implementationstreue sowie die Einschätzungen der Lehrkräfte zu den durchgeführten Trainings und ihrer Zufriedenheit mit der Blended-Learning-Fortbildung erfassten.\nEin weiteres Ziel war es, zu untersuchen, in welchem Maße sich die Schreibkompetenzen der Schülerinnen und Schüler durch die Teilnahme an der Schreibförderung verbesserten. Hierfür wurden in einem Prä-Post-Follow-Up-Design Kompetenztests mit den Schülerinnen und Schülern durchgeführt. Daten der Schülerinnen und Schüler können aus datenschutzrechtlichen Gründen nicht zur Verfügung gestellt werden.", "de" : "Das übergeordnete Ziel der Studie war es, die Implementation eines Programms zur systematischen Schreibförderung im Unterricht der dritten Klassen zu untersuchen und Bedingungen zu identifizieren, die einen erfolgreichen Einsatz und die Verstetigung der Schreibförderung besonders begünstigen. In einem Studiendesign mit Wartekontrollgruppe nahmen Lehrkräfte an einer Blended-Learning-Fortbildung teil und führten anschließend ein Training zur Schreibflüssigkeit sowie ein Schreibstrategietraining in ihren dritten Klassen durch. Dabei wurden sie von Multiplikatorinnen und Multiplikatoren begleitet, die den Blended-Learning-Kurs zuvor selbst absolviert hatten. Die Erhebung der Lehrkräftedaten erfolgte mittels Fragebögen, welche neben den schulischen Rahmenbedingungen das Unterrichtshandeln im Schreibunterricht, das selbst eingeschätzte Wissen zur Schreibförderung, Einstellungen zu verschiedenen schreibdidaktischen Maßnahmen, die Implementationstreue sowie die Einschätzungen der Lehrkräfte zu den durchgeführten Trainings und ihrer Zufriedenheit mit der Blended-Learning-Fortbildung erfassten.\nEin weiteres Ziel war es, zu untersuchen, in welchem Maße sich die Schreibkompetenzen der Schülerinnen und Schüler durch die Teilnahme an der Schreibförderung verbesserten. Hierfür wurden in einem Prä-Post-Follow-Up-Design Kompetenztests mit den Schülerinnen und Schülern durchgeführt. Daten der Schülerinnen und Schüler können aus datenschutzrechtlichen Gründen nicht zur Verfügung gestellt werden.", "en" : "Das übergeordnete Ziel der Studie war es, die Implementation eines Programms zur systematischen Schreibförderung im Unterricht der dritten Klassen zu untersuchen und Bedingungen zu identifizieren, die einen erfolgreichen Einsatz und die Verstetigung der Schreibförderung besonders begünstigen. In einem Studiendesign mit Wartekontrollgruppe nahmen Lehrkräfte an einer Blended-Learning-Fortbildung teil und führten anschließend ein Training zur Schreibflüssigkeit sowie ein Schreibstrategietraining in ihren dritten Klassen durch. Dabei wurden sie von Multiplikatorinnen und Multiplikatoren begleitet, die den Blended-Learning-Kurs zuvor selbst absolviert hatten. 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Participants were aged 18-77 of various backgrounnds, although the majority were university students. All tests were administered in German. The cognitive ability tests used were the Short Form of the Berlin-Intelligence-Structure Test (BIS-S), a recently developed figural matrices test (HeiQ), and three working memory capacity tasks (Running Span Task, Operation Span Task, and the Symmetry Span Task). All tests were administered in person three times over three test sessions that lasted three hours each. Test sessions were about 10-12 weeks apart. For every test session, cognitive ability tests and their order were held constant. Additionally, psychological questionnaires of interest were administered. 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Participants were aged 18-77 of various backgrounnds, although the majority were university students. All tests were administered in German. The cognitive ability tests used were the Short Form of the Berlin-Intelligence-Structure Test (BIS-S), a recently developed figural matrices test (HeiQ), and three working memory capacity tasks (Running Span Task, Operation Span Task, and the Symmetry Span Task). All tests were administered in person three times over three test sessions that lasted three hours each. Test sessions were about 10-12 weeks apart. For every test session, cognitive ability tests and their order were held constant. Additionally, psychological questionnaires of interest were administered. 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Modelle, die auf diesen Daten trainiert werden, sollen Behauptungen klassifizieren können, die wahr oder falsch sein können, also einen Wahrheitswert haben. Dies dient als Grundbaustein, um automatisiert Behauptungen aufzuspüren, die potentielle Desinformation sind. Ein Anwendungsfeld ist z.B. die Unterstützung von Faktenchecker:innen.\nInsgesamt gibt es 4 Klassen: Aussage (Aussagesätze in Gegenwarts- oder Vergangenheitsform, die keine subjektive Inhalte mit sich tragen), Meinung (Aussagesätze, die subjektive Weltanschauungen mit sich tragen), Prognose (Aussagesätze, die in der Zukunftsform sind) und Sonstiges (Sätze, die keine Aussagesätze sind, also z.B. Fragen oder Befehle).\n\nSchlagworte: Faktencheck, Natural Language Processing (NLP), Fake News, Computational Social Science, Desinformation, Computerlinguistik\nKeywords: fact check, Natural Language Processing (NLP), fake news, computational social science, disinformation, computational linguistics.", "de" : "Es handelt sich um einen natural language processing (NLP) Trainingsdatensatz. Modelle, die auf diesen Daten trainiert werden, sollen Behauptungen klassifizieren können, die wahr oder falsch sein können, also einen Wahrheitswert haben. Dies dient als Grundbaustein, um automatisiert Behauptungen aufzuspüren, die potentielle Desinformation sind. 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