Developing pedagogically appropriate language corpora through crowdsourcing and gamification

Author:

Zviel-Girshin Rina1ORCID,Kuhn Tanara Zingano2ORCID,Luís Ana R.2ORCID,Koppel Kristina3ORCID,Todorović Branislava Šandrih4ORCID,Holdt Špela Arhar5ORCID,Tiberius Carole6ORCID,Kosem Iztok7ORCID

Affiliation:

1. Ruppin Academic Center, Emek Hefer, Israel

2. CELGA-ILTEC/University of Coimbra, Coimbra, Portugal

3. Institute of the Estonian Language, Tallinn, Estonia

4. University of Belgrade, Belgrade, Serbia

5. University of Ljubljana, Ljubljana, Slovenia

6. Dutch Language Institute, Leiden, Netherlands

7. University of Ljubljana & Jožef Stefan Institute, Ljubljana, Slovenia

Abstract

Despite the unquestionable academic interest on corpus-based approaches to language education, the use of corpora by teachers in their everyday practice is still not very widespread. One way to promote usage of corpora in language teaching is by making pedagogically appropriate corpora, labelled with different types of problems (for instance, sensitive content, offensive language, structural problems), so that teachers can select authentic examples according to their needs. Because manually labelling corpora is extremely time-consuming, we propose to use crowdsourcing for this task. After a first exploratory phase, we are currently developing a multimode, multilanguage game in which players first identify problematic sentences and then classify them.

Publisher

Research-publishing.net

Reference8 articles.

1. Integrating corpus literacy into language teacher education

2. Matchin

3. Jiang, Y., Schlagwein, D., & Benatallah, B. (2018). A review on crowdsourcing for education: state of the art of literature and practice. In Proceedings of the 22nd Pacific Asia Conference on Information Systems. PACIS 2018 Proceedings.

4. Kilgarriff, A. (2009). Corpora in the classroom without scaring the students. In Proceedings of the 18th International Symposium on English Teaching and Learning in the Republic of China. National Taiwan Normal University. http://www.kilgarriff.co.uk/Publications/2009-K-ETA-Taiwan-scaring.doc

5. Kilgarriff, A., Husák, M., McAdam, K., Rundell, M., & Rychlý, P. (2008). GDEX: automatically finding good dictionary examples in a corpus. In Proceedings of the XIII EURALEX international congress (pp. 425-432). Universitat Pompeu Fabra.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data preparation in crowdsourcing for pedagogical purposes;Slovenščina 2.0: empirical, applied and interdisciplinary research;2022-12-29

2. EnetCollect – European Network for Combining Language Learning with Crowdsourcing Techniques (COST Action CA16105);Slovenščina 2.0: empirical, applied and interdisciplinary research;2022-12-29

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3