Cultural competence, sometimes referred to as sociolinguistic competence (Canale and Swayne 1980), is an important element of language proficiency (one of the five C’s standards for foreign language learning outlined by ACTFL). However teaching culture still remains one of the under-emphasized areas in teaching foreign languages especially when compared to teaching other language skills. One of the economical, inclusive, and convenient ways to assess cultural competence is with the help of a computerized test. The present paper looks at problems, difficulties and methodology involved in devising software modules to assess cultural competence.
The lack of a defined corpus of cultural competence relevant for the learners of Russian at each level, and the diversity with which it is treated and presented in current textbooks of Russian are some of the problems we encountered. On the basis of sociolinguistic and second language acquisition studies (van Ek 1979, Brown 1980, Seeley 1984, Galloway 1984), we identified convention clusters relevant for the English-speaking learners of Russian (formal/informal greetings, forms of addressing, request, hesitation, thanking, expressing preference, accepting/declining invitation, offer, etc.). We then comprised sixty situations based on Russian everyday life which would reflect these clusters. The paper analyzes textbooks of Russian in use with regard to how they treat cultural competence. A table showing the difference in current textbooks in teaching culture is provided.
The format of the test is a multiple-choice exam (based on Haladyna 1994). The stem consists of the question, three distractors and one right answer. A photo illustrating the situation is provided. Multiple choice answers are read by a native speaker and students are asked to select the best possible response. A sample of the test will be presented at the conference.
The paper presents the intermediate stage of the work in progress which is intended to identify the content of cultural competence relevant for learners of Russian and to devise a tool to measure it. It will be followed by piloting the test and analyzing the empirical data it generated. The project is sponsored by the Center for Language Education and Research (CLEAR) at Michigan State University.