From WikiPapers
Revision as of 06:44, December 8, 2015 by Nemo bis (Talk | contribs) (Created page with "{{Infobox Keyword |keyword=Diversity, }}")

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Diversity, is included as keyword or extra keyword in 0 datasets, 0 tools and 0 publications.


There is no datasets for this keyword.


There is no tools for this keyword.


Title Author(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Access and Efficiency in the Development of Distance Education and E-Learning Hulsmann T. Distance and E-Learning in Transition: Learning Innovation, Technology and Social Challenges English 2013 [No abstract available] 0 0
E-learning and the Quality of Knowledge in a Globalized World Van De Bunt-Kokhuis S. Distance and E-Learning in Transition: Learning Innovation, Technology and Social Challenges English 2013 [No abstract available] 0 0
Reranking web search results for diversity Ralf Krestel
Fankhauser P.
Information retrieval English 2012 Search engine results are often biased towards a certain aspect of a query or towards a certain meaning for ambiguous query terms. Diversification of search results offers a way to supply the user with a better balanced result set increasing the probability that a user finds at least one document suiting her information need. In this paper, we present a reranking approach based on minimizing variance of Web search results to improve topic coverage in the top-k results. We investigate two different document representations as the basis for reranking. Smoothed language models and topic models derived by Latent Dirichlet allocation. To evaluate our approach we selected 240 queries from Wikipedia disambiguation pages. This provides us with ambiguous queries together with a community generated balanced representation of their (sub)topics. For these queries we crawled two major commercial search engines. In addition, we present a new evaluation strategy based on Kullback-Leibler divergence and Wikipedia. We evaluate this method using the TREC sub-topic evaluation on the one hand, and manually annotated query results on the other hand. Our results show that minimizing variance in search results by reranking relevant pages significantly improves topic coverage in the top-k results with respect to Wikipedia, and gives a good overview of the overall search result. Moreover, latent topic models achieve competitive diversification with significantly less reranking. Finally, our evaluation reveals that our automatic evaluation strategy using Kullback-Leibler divergence correlates well with α-nDCG scores used in manual evaluation efforts. 0 0
Using wikis with teacher candidates: Promoting collaborative practice and contextual analysis Wake D.G.
Modla V.B.
Journal of Research on Technology in Education English 2012 This article examines a collaborative study that two teacher educators conducted across two sites. Participants included teacher candidates implementing a digital language experience approach project with elementary learners. The teacher candidates collaborated across sites, building joint wikis to examine their processes and products. The wikis were designed to support candidates critical thinking while promoting collaboration. Results indicate that the use of wikis effectively promoted collaboration, critical thinking, understanding of learners development and diversity, and understanding of literacy-based pedagogical strategies. However, results also show that teacher candidates need support in considering contexts of instructional practice (including community, school, and classroom factors) and need guidance in giving and receiving peer feedback. 0 0
Towards a diversity-minded Wikipedia Fabian Flöck
Denny Vrandečić
Elena Simperl
WebSci Conference English June 2011 Wikipedia is a top-ten Web site providing a free encyclopedia created by an open community of volunteer contributors. As investigated in various studies over the past years, contributors have different backgrounds, mindsets and biases; however, the effects - positive and negative - of this diversity on the quality of the Wikipedia content, and on the sustainability of the overall project are yet only partially understood. In this paper we discuss these effects through an analysis of existing scholarly literature in the area and identify directions for future research and development; we also present an approach for diversity-minded content management within Wikipedia that combines techniques from semantic technologies, data and text mining and quantitative social dynamics analysis to create greater awareness of diversity-related issues within theWikipedia community, give readers access to indicators and metrics to understand biases and their impact on the quality of Wikipedia articles, and support editors in achieving balanced versions of these articles that leverage the wealth of knowledge and perspectives inherent to large-scale collaboration. 24 1
A survival modeling approach to biomedical search result diversification using wikipedia Xiaoshi Yin
Jimmy Xiangji Huang
Xiaofeng Zhou
Zhoujun Li
SIGIR English 2010 0 0
The effects of diversity on group productivity and member withdrawal in online volunteer groups Jilin Chen
Yingjie Ren
John Riedl
Conference on Human Factors in Computing Systems - Proceedings English 2010 The "wisdom of crowds" argument emphasizes the importance of diversity in online collaborations, such as open source projects and Wikipedia. However, decades of research on diversity in offline work groups have painted an inconclusive picture. On the one hand, the broader range of insights from a diverse group can lead to improved outcomes. On the other hand, individual differences can lead to conflict and diminished performance. In this paper, we examine the effects of group diversity on the amount of work accomplished and on member withdrawal behaviors in the context of WikiProjects. We find that increased diversity in experience with Wikipedia increases group productivity and decreases member withdrawal - up to a point. Beyond that point, group productivity remains high, but members are more likely to withdraw. Strikingly, no such diminishing returns were observed for differences in member interest, which increases productivity and decreases member withdrawal in a linear fashion. Our results suggest that the low visibility of individual differences in online groups may allow them to harvest more of the benefits of diversity while bearing less of the cost. We discuss how our findings can inform further research of online collaboration. 0 0