This paper explores the use of Natural Language Generation (NLG) for facilitating the provision of feedback to citizen scientists in the context of a nature conservation programme, BeeWatch. BeeWatch aims to capture the distribution of bumblebees, an ecologically and economically important species group in decline, across the UK and beyond. The NLG module described here uses comparisons of visual features of bumblebee species as well as contextual information to improve the citizen scientists' identification skills and to keep them motivated. We report studies that show a positive effect of NLG feedback on accuracy of bumblebee identification and on volunteer retention, along with a positive appraisal of the generated feedback.
|Title of host publication||COLING 2012 :|
|Subtitle of host publication||24th International Conference on Computational Linguistics : Proceedings of COLING 2012 : Technical Papers|
|Editors||Martin Kay, Christian Boitet|
|Place of Publication||Mumbai|
|Publisher||The COLING 2012 Organizing Committee|
|Number of pages||14|
|Publication status||Published - 2012|