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Schulentwicklung als Kooperationsprojekt zwischen Bildungsforschung und Schulpraxis am Beispiel von […]
Heer, Jana; Sauerwein, Markus
Book Chapter
| Aus: Kielblock, Stephan; Arnoldt, Bettina; Fischer, Natalie; Gaiser, Johanna M.; Holtappels, Heinz-Günter (Hrsg.): Individuelle Förderung an Ganztagsschulen: Forschungsergebnisse der Studie zur Entwicklung von Ganztagsschulen (StEG) | Weinheim: Beltz Juventa | 2021
39735 Endnote
Author(s):
Heer, Jana; Sauerwein, Markus
Title:
Schulentwicklung als Kooperationsprojekt zwischen Bildungsforschung und Schulpraxis am Beispiel von StEG-Tandem
In:
Kielblock, Stephan; Arnoldt, Bettina; Fischer, Natalie; Gaiser, Johanna M.; Holtappels, Heinz-Günter (Hrsg.): Individuelle Förderung an Ganztagsschulen: Forschungsergebnisse der Studie zur Entwicklung von Ganztagsschulen (StEG), Weinheim: Beltz Juventa, 2021 , S. 135-157
URL:
https://www.beltz.de/fachmedien/erziehungs_und_sozialwissenschaften/buecher/produkt_produktdetails/43636-individuelle_foerderung_an_ganztagsschulen.html
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Deutsch
Keywords:
Akteur; Audioaufzeichnung; Bildungsforschung; Deutschland; Evidenz; Implementation; Innovation; Intervention; Konzeption; Kooperation; Kooperatives Lernen; Praxis; Schule; Schulentwicklung; Textanalyse; Transfer; Wissenschaft
Abstract:
Im vorliegenden Beitrag wird mittels Daten aus StEG-Tandem der Dialog zwischen Bildungsforschung und Schulpraxis in der Schulentwicklungsstudie nachgezeichnet. Anknüpfend an theoretische Modelle des Wissenschafts-Praxis-Transfers wird untersucht, wie Akteurinnen und Akteure der Schule sowie der Wissenschaft gemeinsam mit je einem Schulbegleiter Konzepte zur Implementation kooperativer Lernformen erarbeiten. Die Zusammenarbeit konturiert sich als sukzessiver Annäherungs- und Aushandlungsprozess, der durch unterschiedliche Fokusse gekennzeichnet ist und in schulspezifisch ausgearbeitete Konzepte zur Umsetzung von Peer Mentoring mündet. (DIPF/Orig.)
DIPF-Departments:
Lehr und Lernqualität in Bildungseinrichtungen
Argumentation mining in user-generated web discourse
Habernal, Ivan; Gurevych, Iryna
Journal Article
| In: Computational Linguistics Journal | 2017
36233 Endnote
Author(s):
Habernal, Ivan; Gurevych, Iryna
Title:
Argumentation mining in user-generated web discourse
In:
Computational Linguistics Journal, 43 (2017) 1, S. 125-179
DOI:
10.1162/COLI_a_00276
URL:
http://www.mitpressjournals.org/doi/abs/10.1162/COLI_a_00276#.WIDIonpp-nU
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Language:
Englisch
Keywords:
Argumentation; Automatisierung; Computerlinguistik; Data Mining; Diskurs; Erziehungswissenschaft; Information Retrieval; Modell; Reliabilität; Soziale Software; Textanalyse; World wide web 2.0
Abstract:
The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Processing of positive-causal and negative-causal coherence relations in primary school children […]
Knoepke, Julia; Richter, Tobias; Isberner, May-Britt; Naumann, Johannes; Neeb, Yvonne; […]
Journal Article
| In: Journal of Child Language | 2017
36656 Endnote
Author(s):
Knoepke, Julia; Richter, Tobias; Isberner, May-Britt; Naumann, Johannes; Neeb, Yvonne; Weinert, Sabine
Title:
Processing of positive-causal and negative-causal coherence relations in primary school children and adults. A test of the cumulative cognitive complexity approach in German
In:
Journal of Child Language, 44 (2017) 2, S. 297-328
DOI:
10.1017/S0305000915000872
URN:
urn:nbn:de:0111-dipfdocs-191627
URL:
http://www.dipfdocs.de/volltexte/2020/19162/pdf/J.Child_Lang_2017_2_Knoepke_et_al_Processing_of_positivecausal_and_negativecausal_coherence_relations_A.pdf
Publication Type:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Language:
Englisch
Keywords:
Deutsch; Deutschland; Empirische Untersuchung; Erwachsener; Grundschule; Grundschüler; Hören; Kognition; Kognitive Prozesse; Lesen; Leseverstehen; Semantik; Technologiebasiertes Testen; Test; Textanalyse; Textinterpretation; Textverständnis
Abstract:
Establishing local coherence relations is central to text comprehension. Positive-causal coherence relations link a cause and its consequence, whereas negative-causal coherence relations add a contrastive meaning (negation) to the causal link. According to the cumulative cognitive complexity approach, negative-causal coherence relations are cognitively more complex than positive-causal ones. Therefore, they require greater cognitive effort during text comprehension and are acquired later in language development. The present cross-sectional study tested these predictions for German primary school children from Grades 1 to 4 and adults in reading and listening comprehension. Accuracy data in a semantic verification task support the predictions of the cumulative cognitive complexity approach. Negative-causal coherence relations are cognitively more demanding than positive-causal ones. Moreover, our findings indicate that children's comprehension of negative-causal coherence relations continues to develop throughout the course of primary school. Findings are discussed with respect to the generalizability of the cumulative cognitive complexity approach to German. (DIPF/Orig.)
DIPF-Departments:
Bildungsqualität und Evaluation
What is the essence of a claim? Cross-domain claim identification
Daxenberger, Johannes; Habernal, Ivan; Stab, Christian; Gurevych, Iryna
Book Chapter
| Aus: Association for Computational Linguistics (Hrsg.): The Conference on Empirical Methods in Natural Language Processing (EMNLP 2017): Proceedings of the conference, September 9-11, 2017, Copenhagen, Denmark | Stroudsburg; PA: Association for Computational Linguistics | 2017
37872 Endnote
Author(s):
Daxenberger, Johannes; Habernal, Ivan; Stab, Christian; Gurevych, Iryna
Title:
What is the essence of a claim? Cross-domain claim identification
In:
Association for Computational Linguistics (Hrsg.): The Conference on Empirical Methods in Natural Language Processing (EMNLP 2017): Proceedings of the conference, September 9-11, 2017, Copenhagen, Denmark, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 2045-2056
URL:
http://www.aclweb.org/anthology/D/D17/D17-1217.pdf
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Argumentation; Computerlinguistik; Data Mining; Qualitative Forschung; Sprachanalyse; Text; Textanalyse
Abstract:
Argument mining has become a popular research area in NLP. It typically includes the identification of argumentative components, e.g. claims, as the central component of an argument. We perform a qualitative analysis across six different datasets and show that these appear to conceptualize claims quite differently. To learn about the consequences of such different conceptualizations of claim for practical applications, we carried out extensive experiments using state-of-the-art feature-rich and deep learning systems, to identify claims in a cross-domain fashion. While the divergent conceptualization of claims in different datasets is indeed harmful to cross-domain classification, we show that there are shared properties on the lexical level as well as system configurations that can help to overcome these gaps. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Neural end-to-end learning for computational argumentation mining
Eger, Steffen; Daxenberger, Johannes; Gurevych, Iryna
Book Chapter
| Aus: Association for Computational Linguistics (Hrsg.): The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017): Proceedings of the conference, vol. 1 (long papers), July 30 - August 4, 2017, Vancouver, Canada | Stroudsburg; PA: Association for Computational Linguistics | 2017
37878 Endnote
Author(s):
Eger, Steffen; Daxenberger, Johannes; Gurevych, Iryna
Title:
Neural end-to-end learning for computational argumentation mining
In:
Association for Computational Linguistics (Hrsg.): The 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017): Proceedings of the conference, vol. 1 (long papers), July 30 - August 4, 2017, Vancouver, Canada, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 11-22
DOI:
10.18653/v1/P17-1002
URL:
https://aclanthology.info/pdf/P/P17/P17-1002.pdf
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Argumentation; Automatisierung; Computerlinguistik; Data Mining; Klassifikation; Rhetorik; Semantik; Textanalyse
Abstract:
We investigate neural techniques for end-to-end computational argumentation mining (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging problem, including a multi-task learning setup. Contrary to models that operate on the argument component level, we find that framing AM as dependency parsing leads to subpar performance results. In contrast, less complex (local) tagging models based on BiL-STMs perform robustly across classification scenarios, being able to catch long-range dependencies inherent to the AM problem. Moreover, we find that jointly learning 'natural' subtasks, in a multi-task learning setup, improves performance. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
EELECTION at SemEval-2017 Task 10. Ensemble of nEural Learners for kEyphrase ClassificaTION
Eger, Steffen; Do Dinh, Erik-Lân; Kuznetsov, Ilia; Kiaeeha, Masoud; Gurevych, Iryna
Book Chapter
| Aus: Association for Computational Linguistics (Hrsg.): 11th International Workshop on Semantic Evaluations (SemEval-2017): Proceedings of the workshop, August 3-4, 2017, Vancouver, Canada | Stroudsburg; PA: Association for Computational Linguistics | 2017
37870 Endnote
Author(s):
Eger, Steffen; Do Dinh, Erik-Lân; Kuznetsov, Ilia; Kiaeeha, Masoud; Gurevych, Iryna
Title:
EELECTION at SemEval-2017 Task 10. Ensemble of nEural Learners for kEyphrase ClassificaTION
In:
Association for Computational Linguistics (Hrsg.): 11th International Workshop on Semantic Evaluations (SemEval-2017): Proceedings of the workshop, August 3-4, 2017, Vancouver, Canada, Stroudsburg; PA: Association for Computational Linguistics, 2017 , S. 942-946
URL:
http://aclweb.org/anthology/S17-2163
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Computerlinguistik; Klassifikation; Publikation; Semantik; Textanalyse; Wissenschaft
Abstract:
This paper describes our approach to the SemEval 2017 Task 10: "Extracting Keyphrases and Relations from Scientific Publications", specifically to Subtask (B): "Classification of identified keyphrases". We explored three different deep learning approaches: a character-level convolutional neural network (CNN), a stacked learner with an MLP meta-classifier, and an attention based Bi-LSTM. From these approaches, we created an ensemble of differently hyper-parameterized systems, achieving a micro-F1-score of 0.63 on the test data. Our approach ranks 2nd (score of 1st placed system: 0.64) out of four according to this official score. However, we erroneously trained 2 out of 3 neural nets (the stacker and the CNN) on only roughly 15% of the full data, namely, the original development set. When trained on the full data (training+development), our ensemble has a micro-F1-score of 0.69. Our code is available from https://github.com/UKPlab/semeval2017-scienceie. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
A "Wind of Change" Shaping public opinion of the "Arab Spring" using metaphors
Núñez, Alexandra; Gerloff, Malte; Do Dinh, Erik-Lan; Rapp, Andrea; Gehring, Petra; Gurevych, Iryna
Book Chapter
| Aus: Alliance of Digital Humanities (Hrsg.): Digital Humanities 2017: Conference abstracts, McGill University & Université de Montréal, Montréal, Canada, August 8.11, 2017 | Montréal: Alliance of Digital Humanities | 2017
37342 Endnote
Author(s):
Núñez, Alexandra; Gerloff, Malte; Do Dinh, Erik-Lan; Rapp, Andrea; Gehring, Petra; Gurevych, Iryna
Title:
A "Wind of Change" Shaping public opinion of the "Arab Spring" using metaphors
In:
Alliance of Digital Humanities (Hrsg.): Digital Humanities 2017: Conference abstracts, McGill University & Université de Montréal, Montréal, Canada, August 8.11, 2017, Montréal: Alliance of Digital Humanities, 2017 , S. 551-553
URL:
https://dh2017.adho.org/abstracts/041/041.pdf
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Automatisierung; Computerlinguistik; Einflussfaktor; Grammatik; Metapher; Öffentliche Meinung; Presseberichterstattung; Semantik; Textanalyse
Abstract:
How does mass media affect the way we think about controversial topics such as the "Arab Spring"? What persuasive role do metaphors play especially in opinion pieces? We analyze how the political events of the years 2010-2011 in the Middle East and North Africa Region ("Arab Spring") are categorized and assessed using metaphorical constructions in newspaper opinion pieces. We show ways in which particularly the use of metaphors reveals how the media tried to achieve acceptance for the events based on our cultural models (Quinn and Holland, 1987), which are grounded on our western knowledge. To this end, we constructed a pipeline that automatically detects (and filters) metaphors appearing within certain grammatical constructions, before clustering them by presumed source and target domains (Conceptual Metaphor Theory, Lakoff and Johnson, 1980). The results give us insights into how the "Arab Spring" is metaphorically structured by semantic clusters in opinion pieces. (DIPF/Autor)
DIPF-Departments:
Informationszentrum Bildung
Training argumentation skills with argumentative writing support
Stab, Christian; Gurevych, Iryna
Book Chapter
| Aus: Petukhova, Volha; Tian, Ye (Hrsg.): Proceedings of the 21st Workshop on the Semantics and Pragmatics Dialogue (SEMDIAL 2017 SaarDial), Saarbrücken, 15-17 August 2017 | Saarbrücken: Saarland Universität | 2017
37873 Endnote
Author(s):
Stab, Christian; Gurevych, Iryna
Title:
Training argumentation skills with argumentative writing support
In:
Petukhova, Volha; Tian, Ye (Hrsg.): Proceedings of the 21st Workshop on the Semantics and Pragmatics Dialogue (SEMDIAL 2017 SaarDial), Saarbrücken, 15-17 August 2017, Saarbrücken: Saarland Universität, 2017 (Proceedings (SemDial)), S. 174-175
URL:
www.saardial.uni-saarland.de/wordpress/wp-content/uploads/SemDial2017SaarDial_proceedings.pdf#page=182
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Argumentation; Computerlinguistik; Textanalyse
Abstract:
We present an writing support system for assessing written arguments. Our system incorporates three analysis models allowing for rich feedback about argumentation structure, quality of reasons, and presence of opposing arguments. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Visualization for text mining in the digital humanities. Empowering researchers to use advanced […]
Hocker, Julian
Book Chapter
| Aus: Gäda, Maria;Trkulja, Violeta;Petras, Vivien (Hrsg.): Everything changes, everything stays the same? Understanding information spaces: Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin, Germany, 13th - 15th March 2017 | Glückstadt: Hülsbusch | 2017
37200 Endnote
Author(s):
Hocker, Julian
Title:
Visualization for text mining in the digital humanities. Empowering researchers to use advanced tools for text mining
In:
Gäda, Maria;Trkulja, Violeta;Petras, Vivien (Hrsg.): Everything changes, everything stays the same? Understanding information spaces: Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin, Germany, 13th - 15th March 2017, Glückstadt: Hülsbusch, 2017 (Schriften zur Informationswissenschaft, 70), S. 308-314
URL:
http://isi2017.ib.hu-berlin.de/ISI_17_ONLINE_FINAL.pdf#page=309
Publication Type:
4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Benutzerfreundlichkeit; Visualisierung; Data Mining; Geisteswissenschaften; Digitalisierung; Forscher; Qualitative Forschung; Textanalyse; Computerunterstütztes Verfahren; Tool; Konzeption
Abstract:
In this PhD thesis, a visual interface for text analysis and text mining in the digital humanities (DH) will be developed. Text analysis is a crucial task in the DH, but advanced text mining technologies like topic modeling or clustering are difficult to use for most researchers. My work bridges this gap using visualizations. To ensure an adequate usability of visualizations for epistemological practices, the visualizations will be realized with researchers in an agile and participatory approach. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Grasping the materializations of practices in Digital Humanities. A semantic research environment […]
Hocker, Julian; Schindler, Christoph; Müller, Lars; Mealeshkova, Maria; Weller, Tobias
Book Chapter
| Aus: Gäde, Maria;Trkulja, Violeta;Petras, Vivien (Hrsg.): Everything changes, everything stays the same? Understanding information spaces: Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin, Germany, 13th - 15th March 2017 | Glückstadt: Hülsbusch | 2017
37199 Endnote
Author(s):
Hocker, Julian; Schindler, Christoph; Müller, Lars; Mealeshkova, Maria; Weller, Tobias
Title:
Grasping the materializations of practices in Digital Humanities. A semantic research environment for analyzing exam grading practices in German high schools
In:
Gäde, Maria;Trkulja, Violeta;Petras, Vivien (Hrsg.): Everything changes, everything stays the same? Understanding information spaces: Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin, Germany, 13th - 15th March 2017, Glückstadt: Hülsbusch, 2017 (Schriften zur Informationswissenschaft, 70), S. 365-367
URL:
http://isi2017.ib.hu-berlin.de/ISI_17_ONLINE_FINAL.pdf#page=366
Publication Type:
4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Semantik; Computerunterstütztes Verfahren; Digitalisierung; Geisteswissenschaften; Forschungsprojekt; Forschungsdesign; Abschlussprüfung; Sekundarbereich; Notengebung; Textanalyse
DIPF-Departments:
Bibliothek für Bildungsgeschichtliche Forschung; Informationszentrum Bildung
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