Summary:

These days many communes treat tourism as a major factor for economic activation and a simulator to economic growth. This is well visible in areas that are attractive in terms of tourism as follows: tourist values, access by transporta-tion and status of tourist development. The objective of the paper was to assess se-lected elements of tourist attractiveness of the districts in the province of Opole. The research has an additional practical objective since the results will be used by experts reviewing co-financing applications for projects under ROP OV
2007-2013. The research material used in this paper is secondary and has been acquired as a result of studies of statistics as well as bibliographic literature and studies. A descriptive method was applies which is one of induction research methods. The research covered 12 districts of the province of Opole and the year of 2008. The analysis covered selected elements of tourist attractiveness of the in-vestigated area. The research included: protected areas, number of musealia, length of public roads, number of road accidents, number of hotels and number of hotel beds. A development template method which is multidimensional comparative analysis was applied to assess the tourist attractiveness of the studied district. Con-sidering the diagnostic features analysed in the paper, aggregated as development measures, The following districts were found to be the most attractive in the prov-ince of Opole: Nysa, Opole and Strzelce, the least attractive districts were: Krap-kowice and Kędzierzyn-Koźle. The district of Nysa can be classified as a highly at-tractive district in terms of tourism while Opole has medium attractiveness. The other districts of the province are little attractive in terms of tourism. Since the is-sues studied in the paper provide much information and can be practically ap-plied, it seems necessary to continue in-depth studies of tourism attractiveness. However, it is necessary to expend the set of the diagnostic features describing the tourism attractiveness and to apply more sophisticated methods of statistical analysis.