Cited By
View all- Henrich ANicklas D(2018)Datenbanken und Information Retrieval an der Universität BambergDatenbank-Spektrum10.1007/s13222-018-0298-518:3(195-202)Online publication date: 24-Oct-2018
Assessing Interestingness and Importance of Information Retrieval Course Topics in a Course for Three Different Target Groups
Article No.: 20, Pages 1 - 8
Abstract
Teaching an information retrieval (IR) course for three different target groups is challenging. These target groups are i) resident students at the University of Bamberg, Germany ii) remote full-time students from other Bavarian universities, and iii) remote but part-time students from all parts of Germany which usually study the course besides their day-to-day work relationship. As a consequence, we have participants with heterogeneous previous knowledge and potentially different expectations with respect to the course content.
In this paper we will only briefly describe the didactic aspects and challenges of the course. The clear focus of the paper lies on an in-depth quantitative evaluation how various IR topics presented in the lectures and tutorials fit the needs of the different target groups. We evaluate interestingness and importance of the course topics according to the students' impressions. The goal of the evaluation is to get hints for future refinements of IR course content---in general but also with respect to the needs of different target groups.
References
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D. Blank, N. Fuhr, A. Henrich, T. Mandl, T. Rölleke, H. Schütze, and B. Stein. Teaching IR: curricular considerations. In Efthimiadis et al. {4}, pages 31--46.
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O. Chapelle, D. Metzler, Y. Zhang, and P. Grinspan. Expected reciprocal rank for graded relevance. In Proceedings of the 18th ACM Conference on Information and Knowledge Management, CIKM '09, pages 621--630, New York, NY, USA, 2009. ACM.
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B. Croft, D. Metzler, and T. Strohman. Search Engines: Information Retrieval in Practice. Pearson, International Edition, Upper Saddle River, New Jersey, USA, 2010.
[4]
E. N. Efthimiadis, J. M. Fernández-Luna, J. F. Huete, and A. MacFarlane, editors. Teaching and Learning in Information Retrieval, volume 31 of The Information Retrieval Series. Springer, 2011.
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M. McCandless, E. Hatcher, and O. Gospodnetic. Lucene in Action. Manning Publications, 2 edition, 2010.
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M. Steyvers and T. Griffiths. Probabilistic Topic Models. Latent Semantic Analysis: A Road to Meaning., 427(7):424--440, 2007.
- Assessing Interestingness and Importance of Information Retrieval Course Topics in a Course for Three Different Target Groups
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Published In
June 2016
146 pages
ISBN:9781450341417
DOI:10.1145/2934732
Copyright © 2016 ACM.
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- University of Granada: University of Granada
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 14 June 2016
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CERI '16
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CERI '16 Paper Acceptance Rate 18 of 27 submissions, 67%;
Overall Acceptance Rate 36 of 51 submissions, 71%
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View all- Henrich ANicklas D(2018)Datenbanken und Information Retrieval an der Universität BambergDatenbank-Spektrum10.1007/s13222-018-0298-518:3(195-202)Online publication date: 24-Oct-2018
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