Research in interactive information retrieval (IR) usually relies on lab user studies or online ones. A key concern of these studies is the generalizability and reproducibility of the results, especially when the studies involved only a limited number of participants. The interactive IR community, however, does not have a commonly agreed guideline regarding how many participants should recruit. We study this fundamental research protocol issue by examining the generalizability and reproducibility of results with respect to a different number of participants using simulation-based approaches. Specifically, we collect a relatively large number of participants' observations for a representative interactive IR experiment setting from online user studies using crowdsourcing. We sample smaller numbers of participants' results from the collected observations to simulate the results of online user studies with a smaller scale. We empirically analyze the patterns of generalizability and reproducibility regarding different dependent variables and draw conclusions related to the optimal number of participants. Our study contributes to interactive information retrieval research by 1) establishing a methodology for evaluating the generalizability and reproducibility of results, and 2) providing guidelines regarding the optimal number of participants for search engine user studies. / Master of Science / In the domain of Information Retrieval, researchers or scientists usually require human participants to interact, test and evaluate a novel system, which is usually called user studies. However, researchers usually perform these studies with small sample size, some of them recruited fewer than 20 participants, which casts doubt on the generalizability and reproducibility of these studies. Generalizability means how reliable the results of relatively small sample size in an experimental setting can be generalized to the outcomes of a larger population. Reproducibility means whether the results from two groups with the same amount of sample size are consistent with each other. In order to examine the generalizability and reproducibility of online user studies in interactive information retrieval systems, we conducted an online user study with large sample size. We reproduced a well-recognized lab user study from Kelly et al. (2015) in an online environment. We established a simulation-based methodology for evaluating the generalizability and reproducibility of the results and then provided guidelines regarding the optimal number of participants for search engine user studies.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/106831 |
| Date | 11 June 2020 |
| Creators | Xu, Zijian |
| Contributors | Computer Science, Jiang, Jiepu, Luther, Kurt, Lee, Sang Won |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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