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Annotierte Bibliographie zum Einsatz von Comics im (Russisch)Unterricht
No full text<p>Dieser Datensatz enthält eine annotierte Bibliographie zum Einsatz von Comics im (Russisch)Unterricht. Die Bibliographie gibt einen Überblick über fachdidaktische Literatur, Forschungsarbeiten, Materialquellen und Tools zur Erstellung von Comics. Sämtliche Einträge sind mit Schlagwörtern versehen.</p><p>Dieser Datensatz basiert auf der online einsehbaren Zotero Group Library https://www.zotero.org/groups/5062074/comics_im_sprachunterricht</p><p> </p>
Eingangsbefragung der Lehramtsstudierenden im Projekt WegE (Wintersemester 2018/19; EK 3)
No full text<p>Befragung von Lehramtsstudierenden im Projekt "Wegweisende Lehrer:innenbildung (WegE)" im Wintersemester 2018/19, N=475 </p><p>Das Projekt WegE wird unter den Förderkennzeichen 01JA1615 und 01JA1915 im Rahmen der gemeinsamen 'Qualitätsoffensive Lehrerbildung' von Bund und Ländern aus Mitteln des Bundesministeriums für Bildung und Forschung gefördert. </p><p>Der Datensatz ist erhältlich auf Anfrage unter: [email protected] </p>
Multi-CAST: Multilingual corpus of annotated spoken texts
Get PDF<p><strong>Multi-CAST</strong>, the <em>Multilingual Corpus of Annotated Spoken Texts</em> (Haig & Schnell 2015), is a collection of annotated spoken-language corpora from a typologically diverse set of languages. Most of the data stem from documentation projects undertaken on lesser-researched and endangered languages. The texts are overwhelmingly unscripted, non-elicited, monologic narratives. </p>
<p>Each corpus in the collection is an individually citable resource that was contributed by experts on the respective languages in cooperation with the collection editors. The Multi-CAST collection as a whole was designed and compiled by Geoffrey Haig and Stefan Schnell with the assistance of Nils Schiborr, and is to date the only freely-available, multilingual, spoken-language corpus that combines morphological and morphosyntactic glossing with annotation of discourse referents. Each Multi-CAST corpus includes audio recordings (as WAV and MP3 files; archived separately, see below), annotation files in a number of file formats (including as EAF files for use with the free <a href="https://archive.mpi.nl/tla/elan">linguistic annotation software ELAN</a>, and as TSV and XML files), metadata on the speakers and texts, as well as documentation on the language, speech communities, recording situations, and analytical decisions pertinent to the annotations.</p>
<p>The annotation files use a multi-tier structure built on a time-aligned segmentation of the text into utterance units, from which derive a transcription and idiomatic English translation. Utterance units are segmented further into grammatical words with morphological glossing (following the <a href="https://www.eva.mpg.de/lingua/resources/glossing-rules.php">Leipzig Glossing Rules</a>) and annotations with the GRAID (<em>Grammatical Relations and Animacy in Discourse</em>, <a href="https://nbn-resolving.org/urn:nbn:de:bvb:473-opus4-262354">Haig & Schnell 2014</a>) and RefIND (<em>Referent Indexing in Natural Language Discourse</em>, <a href="https://fis.uni-bamberg.de/handle/uniba/91175">Schiborr et al. 2018</a>) annotation schemes. Further information on the contents of the collection and the structure of the annotations can be found in the <em>Multi-CAST collection overview</em> (Schiborr 2023), which is included in this archive. The <a href="https://CRAN.R-project.org/package=multicastR"><em>multicastR</em> package</a> (Schiborr 2018) provides a simple interface for directly accessing the Multi-CAST annotation data through the <a href="https://www.r-project.org/">statistical computing language R</a>.</p>
<p><strong>This archive contains version 2311</strong> <strong>of the Multi-CAST collection</strong> (originally published in November 2023) and comprises data from 18 languages, encompassing around 19 hours of recordings, 29000 clause units, and 140000 words across 136 individual texts. The audio files accompanying these data sets have been archived separately; they can be found via the links in the list below.</p>
<ul>
<li><strong>Arta</strong> [<a href="https://glottolog.org/resource/languoid/id/arta1239">arta1239</a>] (Kimoto 2019)<br>— link to audio: <em><a href="https://doi.org/10.48564/unibafd-c0jd0-7qt52">10.48564/unibafd-c0jd0-7qt52</a></em></li>
<li><strong>Bora</strong> [<a href="https://glottolog.org/resource/languoid/id/bora1263">bora1263</a>] (Seifart & Hong 2022)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-zcyz8-x7f04">10.48564/unibafd-zcyz8-x7f04</a></li>
<li><strong>Cypriot Greek</strong> [<a href="https://glottolog.org/resource/languoid/id/cypr1249">cypr1249</a>] (Hadjidas & Vollmer 2015)<br>— <em>no audio files available</em></li>
<li><strong>English</strong> [<a href="https://glottolog.org/resource/languoid/id/sout3282">sout3282</a>] (Schiborr 2015)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-4nays-jwa80">10.48564/unibafd-4nays-jwa80</a></li>
<li><strong>Jinghpaw</strong> [<a href="https://glottolog.org/resource/languoid/id/kach1280">kach1280</a>] (Kurabe 2021)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-jav5f-paa07">10.48564/unibafd-jav5f-paa07</a></li>
<li><strong>Kalamang</strong> [<a href="https://glottolog.org/resource/languoid/id/kara1499">kara1499</a>] (Visser 2021)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-z9wt8-jwd54">10.48564/unibafd-z9wt8-jwd54</a></li>
<li><strong>Mandarin</strong> [<a href="https://glottolog.org/resource/languoid/id/mand1415">mand1415</a>] (Vollmer 2020)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-bxcvm-m9e27">10.48564/unibafd-bxcvm-m9e27</a></li>
<li><strong>Matukar Panau</strong> [<a href="https://glottolog.org/resource/languoid/id/matu1261">matu1261</a>] (Barth, Davey & Matheas 2023) <strong>[NEW!]</strong><br>— link to audio: <a href="https://doi.org/10.48564/unibafd-0sa31-g8r71">doi.org/10.48564/unibafd-0sa31-g8r71</a></li>
<li><strong>Nafsan</strong> [<a href="https://glottolog.org/resource/languoid/id/sout2856">sout2856</a>] (Thieberger & Brickell 2019)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-jq8x6-d8p78">10.48564/unibafd-jq8x6-d8p78</a></li>
<li><strong>Northern Kurdish</strong> [<a href="https://glottolog.org/resource/languoid/id/nort2641">nort2641</a>] (Haig, Vollmer & Thiele 2019)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-6sbd4-r0868">10.48564/unibafd-6sbd4-r0868</a></li>
<li><strong>Persian</strong> [<a href="https://glottolog.org/resource/languoid/id/tehr1242">tehr1242</a>] (Adibifar 2016)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-37wvv-n0j98">10.48564/unibafd-37wvv-n0j98</a></li>
<li><strong>Sanzhi Dargwa</strong> [<a href="https://glottolog.org/resource/languoid/id/sanz1248">sanz1248</a>] (Forker & Schiborr 2019)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-fahwc-1ha62">10.48564/unibafd-fahwc-1ha62</a></li>
<li><strong>Sumbawa</strong> [<a href="https://glottolog.org/resource/languoid/id/sumb1241">sumb1241</a>] (Shiohara 2022)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-p63kx-vzd97">10.48564/unibafd-p63kx-vzd97</a></li>
<li><strong>Tabasaran</strong> [<a href="https://glottolog.org/resource/languoid/id/taba1259">taba1259</a>] (Bogomolova, Ganenkov & Schiborr 2021)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-vqjky-k8g84">10.48564/unibafd-vqjky-k8g84</a></li>
<li><strong>Teop</strong> [<a href="https://glottolog.org/resource/languoid/id/teop1238">teop1238</a>] (Mosel & Schnell 2015)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-03n2z-bm579">10.48564/unibafd-03n2z-bm579</a></li>
<li><strong>Tondano</strong> [<a href="https://glottolog.org/resource/languoid/id/tond1251">tond1251</a>] (Brickell 2016)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-1nkkj-f9352">10.48564/unibafd-1nkkj-f9352</a></li>
<li><strong>Tulil</strong> [<a href="https://glottolog.org/resource/languoid/id/taul1251">taul1251</a>] (Meng 2019)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-h1wq5-wzh05">10.48564/unibafd-h1wq5-wzh05</a></li>
<li><strong>Vera'a</strong> [<a href="https://glottolog.org/resource/languoid/id/vera1241">vera1241</a>] (Schnell 2015)<br>— link to audio: <a href="https://doi.org/10.48564/unibafd-es22h-1j872">10.48564/unibafd-es22h-1j872</a></li>
</ul>
<p> </p>
<p><strong>Citation for the entire Multi-CAST collection:</strong></p>
<ul>
<li>Haig, Geoffrey & Schnell, Stefan (eds.). 2015. <em>Multi-CAST: Multilingual corpus of annotated spoken texts.</em> Version 2311. Bamberg: University of Bamberg. (DOI: <a href="https://doi.org/10.48564/unibafd-q1h0x-3kf71">10.48564/unibafd-q1h0x-3kf71</a>)<br> </li>
</ul>
<p><strong>Citations for individual Multi-CAST corpora:</strong></p>
<ul>
<li>Adibifar, Shirin. 2016. Multi-CAST Persian. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Barth, Danielle & Davey, Kira & Matheas, Maria. 2023. Multi-CAST Matukar Panau. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Bogomolova, Natalia & Ganenkov, Dmitry & Schiborr, Nils N. 2021. Multi-CAST Tabasaran. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Brickell, Timothy. 2016. Multi-CAST Tondano. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Forker, Diana & Schiborr, Nils N. 2019. Multi-CAST Sanzhi Dargwa. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Hadjidas, Harris & Vollmer, Maria. 2015. Multi-CAST Cypriot Greek. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Haig, Geoffrey & Vollmer, Maria & Thiele, Hanna. 2019. Multi-CAST Northern Kurdish. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Kimoto, Yukinori. 2019. Multi-CAST Arta. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Kurabe, Keita. 2021. Multi-CAST Jinghpaw. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Meng, Chenxi. 2019. Multi-CAST Tulil. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Mosel, Ulrike & Schnell, Stefan. 2015. Multi-CAST Teop. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Schiborr, Nils N. 2015. Multi-CAST English. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Schnell, Stefan. 2015. Multi-CAST Vera'a. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Seifart, Frank & Hong, Tai. 2022. Multi-CAST Bora. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Shiohara, Asako. 2022. Multi-CAST Sumbawa. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Thieberger, Nick & Brickell, Timothy. 2019. Multi-CAST Nafsan. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Visser, Eline. 2021. Multi-CAST Kalamang. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
<li>Vollmer, Maria. 2020. Multi-CAST Mandarin. In Haig, Geoffrey & Schnell, Stefan (eds.), <em>Multi-CAST.</em></li>
</ul>
<p> </p>
Befragung der Lehramtsstudierenden in EWS-Vorbereitungskursen im Projekt WegE (Wintersemester 2018/19; EWS-K 4)
No full textoai:fd-repo.uni-bamberg.de:nkpgf-xb115<p>Befragung von Lehramtsstudierenden im Projekt "Wegweisende Lehrer:innenbildung (WegE)" im Wintersemester 2018/19, N=93 </p><p>Das Projekt WegE wird unter den Förderkennzeichen 01JA1615 und 01JA1915 im Rahmen der gemeinsamen 'Qualitätsoffensive Lehrerbildung' von Bund und Ländern aus Mitteln des Bundesministeriums für Bildung und Forschung gefördert. </p><p>Der Datensatz ist erhältlich auf Anfrage unter: [email protected] </p>
Eingangsbefragung der Lehramtsstudierenden im Projekt WegE (Wintersemester 2016/17; EK 1)
No full text<p>Befragung von Lehramtsstudierenden im Projekt "Wegweisende Lehrer:innenbildung (WegE)" im Wintersemester 2016/17, N=384 </p><p>Das Projekt WegE wird unter den Förderkennzeichen 01JA1615 und 01JA1915 im Rahmen der gemeinsamen 'Qualitätsoffensive Lehrerbildung' von Bund und Ländern aus Mitteln des Bundesministeriums für Bildung und Forschung gefördert. </p><p>Der Datensatz ist erhältlich auf Anfrage unter: [email protected] </p>
VRScan3D - lectures and practical exercises towards laserscanning, pointclouds processing and virtual laserscanning simulator
No full text<p>These teaching materials have been developed as part of the DAAD project VRScan3D (<a href="https://fis.uni-bamberg.de/entities/project/9aba7793-4686-47a2-b0bc-513b35bb8d76/details">https://fis.uni-bamberg.de/entities/project/9aba7793-4686-47a2-b0bc-513b35bb8d76/details</a>), whereby a worldwide unique virtual simulator for teaching terrestrial 3D laser scanning has been developed using the game programming environment Unreal Engine (<a href="http://vrscan3d.com/">http://vrscan3d.com/</a>).</p><p>The virtual scanner enables teachers and students to learn the process of terrestrial laser scanning without having the need for a real instrument. Here you can find the lectures towards basics of terrestrial laserscanning as well as practical exercises on the developed software. Target group includes all persons interested in 3D recording with terrestrial laserscanning without prior knowledge. Languages - English and Ukrainian.</p><p>For practical exercises you can <a href="http://vrscan3d.com/"><strong>download here</strong></a> the software. The VRScan3D-software basically allows the planning and simulation of practice-orientated surveying processes with 3D laser scanners within a predefined virtual 3D reality. It allows you to move interactively with an avatar, define scanning stations and targets, select different scanner types according to their specifications and generate realistic 3D point clouds, which can then be further processed in real surveying applications.</p><p>The project is financed under the DAAD program: Support for the internationalization of Ukrainian higher education institutions – shaping the digital future together: German-Ukrainian higher education institution collaborations.</p>
Multi-CAST Matukar Panau (audio recordings)
No full text<p>This archive contains audio recordings for the <strong>Multi-CAST Matukar Panau</strong> corpus (Barth et al. 2023), originally published in November 2023 with version 2311 of the <i>Multi-CAST</i> collection (Haig & Schnell 2015). The annotation and documentation files accompanying these files have been archived separately. The recordings are available as WAV and MP3 files.</p><p><strong>Matukar Panau</strong> [<a href="https://glottolog.org/resource/languoid/id/matu1261">matu1261</a>] is a highly endangered Oceanic language spoken around 45 km north of Madang, Papua New Guinea. Although most children are no longer learning Matukar Panau, current speakers (approximately 300) form a vibrant community of multilinguals in dense social networks. As an Oceanic language on the Papua New Guinea coast, Matukar Panau has many interesting Papuan features.</p><p>The Multi-CAST Matukar Panau corpus constitutes a small subset of recordings made by Danielle Barth during her fieldwork between 2010–2020 (Australian National University Asia-Pacific Innovation Program Grant, <i>Resolving Ambiguity: What face-to-face communication can contribute</i>, PI: Danielle Barth); language documentation is ongoing. Data has been transcribed and translated with help from local community members, especially Kadagoi Rawad Forepiso and Rudolf Raward. Recordings can be found in the <a href="http://hdl.handle.net/2196/00-0000-0000-0012-388F-3">ELAR</a> and PARADISEC (<a href="http://catalog.paradisec.org.au/collections/DGB1">1</a>, <a href="http://catalog.paradisec.org.au/collections/SocCog">2</a>) archives. More information and resources on the language can be found on the <a href="https://matukar.wordpress.com/">project website</a>.</p><p>The texts in Multi-CAST were glossed with GRAID and RefIND by Danielle Barth, Kira Davey, and Maria Matheas. In addition to monologue narratives, some stimulus-based conversational descriptions have also been annotated with these schemata to enable research about referent expression when describing familiar and unfamiliar objects, places, and people. Recordings of these events are archived in ELAR and PARADISEC and those archives will eventually also provide open access to ELAN files with the annotations.</p><p> </p><p><strong>Citation</strong></p><ul><li>Barth, Danielle & Davey, Kira & Matheas, Maria. 2023. Multi-CAST Matukar Panau. In Haig, Geoffrey & Schnell, Stefan (eds.), <i>Multi-CAST: Multilingual corpus of annotated spoken texts.</i> [version of the annotations used]. Bamberg: University of Bamberg.</li></ul><p><strong>References</strong></p><ul><li>Haig, Geoffrey & Schnell, Stefan (eds.). 2015. <i>Multi-CAST: Multilingual corpus of annotated spoken texts.</i> [version]. Bamberg: University of Bamberg.</li></ul><p> </p>
Konzeptionelles Mapping des DataCite Metadata Schema auf das Metadaten-Schema für Forschungsdaten im Forschungsinformationssystem der Universität Bamberg
No full text<p>Im Rahmen des Aufbaus eines institutionellen Forschungsdatenmanagements (FDM) für die Otto-Friedrich-Universität Bamberg wurden Forschungsinformationen zu Forschungsdaten in das Forschungsinformationssystem (FIS) (https://fis.uni-bamberg.de/) integriert. Dieses basiert auf der Software DSpace-CRIS 5, wird aber in 2023 auf DSpace-CRIS 7 umgestellt. Für die Version 7 wurde ein DataCite-DOI-Import entwickelt und auf GitHub eingebracht (https://github.com/DSpace/DSpace/pull/8593). Das vorliegende Mapping bezieht sich auf das DataCite Metadata Schema 4.4 (https://doi.org/10.14454/3w3z-sa82, veröffentlicht am 30.03.2021).</p>
Kommentierte Auswahlbibliographie Comics und graphic novels russischsprachiger Autor:innen
No full text<p>Diese Sammlung enthält eine Auswahlbibliographie von Comics und <i>graphic novels</i> russischsprachiger Autor:innen, die zwischen 2014 und 2021 erschienen sind und online bestellt werden können. </p><p>Da es sich um Originaltexte handelt (und nicht um Adaptationen ursprünglich anderssprachiger Comics) eignen sich diese Comics besonders gut, um landeskundliche Aspekte zu behandeln. </p>