/$1*8$*( 7(67,1* Confidence scoring of speaking performance: How does fuzziness become exact? Tan Jin and Barley Mak The Chinese University of Hong Kong, China Pei Zhou Shanghai Jiao Tong University, China Abstract The fuzziness of assessing second language speaking performance raises two difficulties in scoring speaking performance: indistinction between adjacent levels and overlap between scales. To address these two problems, this article proposes a new approach, confidence scoring, to deal with such fuzziness, leading to confidence scores between two adjacent levels applied to three scales. Since confidence scores have to be transformed to an exact score for test interpretation and use, membership functions and rule bases are applied and a confidence scoring algorithm is developed. Confidence scoring is demonstrated in the paper by an example to facilitate easy understanding. The paper then describes a pilot study that was conducted to try out the confidence scoring design. Initial results reveal that: first, confidence scoring is as feasible as traditional scoring; second, confidence scoring performs better in scoring dependability and in correlations with established benchmarks. At the end of the article, further studies are called for in order to build a validity argument and make further revisions to the confidence scoring method described here. Keywords confidence scoring, confidence scoring algorithm, membership functions, rule bases, speaking performance Language Testing 29(1) 43–65 © The Author(s) 2011 Reprints and permission: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0265532211404383 ltj.sagepub.com Corresponding author: Tan Jin, Department of Curriculum and Instruction, Faculty of Education, The Chinese University of Hong Kong, Hong Kong, China. Email: tjin@cuhk.edu.hk Article