In the EU foreign language skills are increasingly important in making young people more employable, raising their competitiveness, helping them better understand other nations and their cultures. Still many Europeans leave school without a working knowledge of a second language - reason enough to make language teaching and learning more efficient (Multilingualism, European Commission, 2018).

The quality of language learning, summarized in Rudzinska quality system (Rudzinska, 2011), has been discussed in several works by Khampirat and Rudzinska (Khampirat and Rudzinska, 2017; Rudzinska & Khampirat, 2016). Language learning strategies (LLS) are key to learner autonomy; higher strategy use can be associated with higher proficiency in a second language (Ardesheva, 2011; G.Hu et al., 2009, Cohen & Macaro, 2007). For assessing LLS currently most frequently used instrument is SLIL (Oxford, 1990), embracing 6 categories: memory, cognitive, compensation, metacognitive, affective and social. Researchers worldwide have different findings about the use of LLS. In, for example, Hong-Kong, mostly used were compensation and cognitive strategies, while memory strategies were reported to be used the least, besides, higher proficiency students used strategies, involving a lot of active practice (Bremner, 2000); in contrast, in a Korean language as a Foreign Language classroom in the USA most frequently used strategies were compensation and social strategies (Murray, 2010); but female Arabic-speaking students used strategies in the order as follows: metacognitive, cognitive, compensation, social, memory, and affective; freshmen students reported the highest rate of strategy use (Riazi, 2007). SLIL is still being modified and validated: there exists justified criticism and recommendations for enhancing the instrument’s validity (Hsiao & Oxford, 2002);  Bremner emphasized that the problem in trying to establish the direction of causality in the relationship between proficiency and strategy use, correlations between each of the six subscales of the SILL were not so well defined, so they could not be used as predictors for achievement (Bremner, 2000). In Bremner opinion more useful would be to investigate the effect of every strategy on specific aspects of proficiency, in specific contexts and over a period of time. Murray (Murray, 2010) considered that SLIL mainly dealt with the frequency of strategy use, but more important consideration might be the quality of strategy use, pointing out that language learning strategies should be treated as only one among many variables in the language learning process, models for learning should include other student variables, such as learning styles, student affective disposition, social context and cultural differences. Hsiao & Oxford (Hsiao & Oxford, 2002) suggested that other possible approaches to strategy classification should be considered, including among others a task–based strategy inventory. Research has shown that the broader the repertoire of strategies a learner has, the greater the likelihood of success (Yabukoshi & Takeuchi, 2009).  At University of Minnesota, in Center for Advanced Research on Language Acquisition (CARLA Center; Cohen, Oxford & Chi, 2009) was developed Language Learning Strategy Use Inventory (2009; Kappler, Cohen, & Paige, 2009), consisting of four language skills (listening, speaking, reading, writing), vocabulary development and translation strategy use. In previous paper (Rudzinska, Khampirat, 2017) the emphasis was on assessing the construct validity of a Language Learning Strategy Use (LLS) Inventory Instrument. The results showed that Speaking and Listening Strategy Use represented the most important strategies and vital skills to have and to develop.

 Raising awareness about language learning strategy use could help youngsters improve their foreign language skills not only in the EU, but as well beyond it, and the view from outside the EU might help to see our problems better, therefore authors focuse on the comparison of language learning strategy use in two completely different countries – Thailand and Latvia. 

The participants from Thailand were 50 undergraduate Sport Sciences students from a university in Thailand (24 females, 25 - males; 44 and 3 were Year 3 and 4 students, respectively. The age: 20 to 25 year old (M = 21.10, SD = .92). The participants from Latvia were 51 undergraduate Sport science students from Latvian Academy of Sport Education, 27 females, 21 males; 8 and 43 were Year 3 and 4 students, respectively, age: 20 to 39 year old (M = 23.10, SD = 3.27). The original LLS questionnaire contained 6 strategies (90 items): Listening Strategy Use - 5 indicators, 26 items; Vocabulary Strategy Use: 4 indicators, 18 items; Speaking Strategy Use: 3 indicators, 18 items; Reading Strategy Use: 2 indicators, 12 items; Writing Strategy Use: 3 indicators, 10 items; Translation Strategy Use: 2 indicators, 6 items. Each item was rated on a four-point Likert scale (1-4). The LLS questionnaire was translated into the Thai language, Latvian students used the original questionnaire in English. To assess internal consistency reliability of the LLS questionnaire, Cronbach’s alpha coefficient was employed; in the Thai students it was from 0.89 to 0.96; in Latvian students - 0.37 to 0.85. Statistical analysis: means (M), standard deviations (SD), Pearson correlation coefficient between strategies. In order to test whether there is a difference between two country's’ mean, Independent sample t-test was employed to assess statistical significance. The statistical analyses of the 50 Sport Sciences students from Thailand showed that the level of using English LLS was comparatively high (M = 2.54 to 2.91); the largest mean scores were obtained in Translation Strategy Use (M = 2.91, SD = 0.61), followed by Listening (M = 2.80, SD = 0.62), Reading (M = 2.77, SD = 0.67), Speaking (M = 2.73, SD = 0.64), Vocabulary (M = 2.63, SD = 0.59); and Writing Strategy Use (M = 2.54, SD = .0.67). The statistical analyses of 51 Sport science students from Latvia showed that the level of using English LLS English LLS is rather high (M = 2.48 to 2.74); the largest mean scores were obtained in Translation Strategy Use (M = 2.74, SD = 0.46), followed by Listening (M = 2.58, SD = 0.37), Writing (M = 2.56, SD = 0.51), Reading (M = 2.50, SD = 0.50), Speaking (M = 2.49, SD = 0.46); and finally: Vocabulary Strategy Use (M = 2.48, SD = 0.51). The correlation coefficients between the strategies use in Thai and Latvian students were statistically significant and positively related.

The independent t-test results indicated that there was no significant difference between Thai and Latvian students in using of overall Language Strategy, t(85.63) = 1.80, p = .08. However, there was statistically significant difference between two groups in (a) Strategy of Listening [t(79.39) = 2.14, p = .04]; (b) Speaking [t(89.29) = 2.15, p = .03]; and (c) Reading [t(98.00) = 2.22, p = .03]. Thai students use Listening, Speaking and Reading strategies more than Latvian students. The authors consider that systematically tested CARLA questionnaire could be applied with some modification in European and other countries in the world. This conclusion is important because LLS can be used as a tool for helping student or other learners to study or use a language more effectively, raise student autonomy, which is the target of every educational institution. As well as we observed differences in the importance and variety of strategy use in two countries. Both Thai and Latvian students prefer Translation and Listening Strategies. This might reflect the fact that when learning English, students often used Translation and Listening strategies to help them overcome limitations in existing language knowledge and skills. But in Latvia Vocabulary Strategy received the lowest rank of use, whereas in Thailand the lowest rank of use was Writing strategy. However, in Thai students, the largest variety of strategies used was observed in Reading and Writing strategies, in Latvian students – in Vocabulary and Writing strategies. Data on the level of Language Learning Strategy that may contribute to the causal pathway linking student’s background, institutional environment, outcome expectations, and willingness to communicate. Relationships such as that between the quality of the institutional environment and the outcome expectations level may also affect Language Learning Strategy use. The further studies might examine causality or the relationship between these factors and LLS.

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