Construct Validation Of Language Learning Strategy Use Inventory
Author(s):
Ieva Rudzinska (presenting / submitting) Buratin Khampirat (presenting)
Conference:
ECER 2017
Format:
Paper

Session Information

11 SES 10 A, Teaching Strategies and Learning Quality

Paper Session

Time:
2017-08-24
15:30-17:00
Room:
W2.10
Chair:
Ineta Luka

Contribution

Multilingual EU supports language learning mainly because better language skills enable more people to improve their job prospects, enhance understanding people from different cultures (The new European programme for languages, 2014-2020).  The quality of language learning, summarized in Rudzinska quality system for a study course (Rudzinska, 2011), has been discussed in several works by Khampirat and Rudzinska (Rudzinska & Khampirat, 2015; Rudzinska & Khampirat, 2016).

Present Paper deals with language learning strategies (LLS) that 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).  There are 6 categories: memory, cognitive, compensation, metacognitive, affective and social. Bremner (Bremner, 2000) found that students in Hong-Kong mostly use compensation and cognitive strategies, while memory strategies are reported to be used the least. Higher proficiency students use strategies, involving a lot of active practice. Murray investigation (Murray, 2010) showed that in a Korean language as a Foreign Language classroom in the USA most frequently used strategies were compensation and social strategies. Riazi (Riazi, 2007) study investigated 120 female Arabic-speaking students,  finding that this group of English as Foreign language learners used strategy in the order of metacognitive, cognitive, compensation, social, memory, and affective ones, freshmen students reported the highest rate of strategy use with a mean of 3.64. Freshmen students also use more compensation strategies than other level students.

SLIL structural validity, however, is far from established, exists justified criticism and recommendations for enhancing the instrument’s validity (Hsiao & Oxford, 2002),   Ardasheva (Ardasheva & Tretter, 2013) modified and validated the SILL (Oxford, 1990), developed for adults, for school-aged ELL students, developing a shorter, 28 item version. Bremner emphasizes that there is a problem in trying to establish the direction of causality in the relationship between proficiency and strategy use (Bremner, 2000). 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. 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) considers that SLIL mainly deals with the frequency of strategy use, but more important consideration might be the quality of strategy use, points 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) compared classification theories of language learning strategies. Results from confirmatory factor analysis (CFA) of the data measured by the ESL/EFL version of the Strategy Inventory for Language Learning and collected from 517 college EFL learners. The findings suggest that other possible approaches to strategy classification should be considered, including among others a task–based strategy inventory.

In CARLA Center (Cohen, Oxford & Chi, 2009) has been developed Language Learning Strategy (LLS) Use Inventory, consisting of different language skill (listening, speaking, reading, writing) and vocabulary development strategy use. The purpose of the Inventory is to find out more about students as language learners and help them discover strategies that can help master a new language.

The main objective of this work was to assess the construct validity of a Language Learning Strategy Use (LLS) Inventory Instrument, when applied to Information Technology (IT) students in Thailand.

Method

The participants in the study were 214 undergraduate IT students from a university in Thailand, 133 subjects (62.15%) female, 79 (36.92%) male, 2 (0.93%) declined to state their gender. 205 (95.79%) were Year 1 students, 18 to 24 year olds (M = 18.86, SD = .99). The English LLS questionnaire was translated into the Thai language by one of the authors - Khampirat and one expert in English. The original LLS questionnaire contained 6 strategies (90 items), namely: 1) Listening Strategy Use - 5 indicators (26 items) 2) Vocabulary Strategy Use - 4 indicators (18 items) 3) Speaking Strategy Use - 3 indicators (18 items) 4) Reading Strategy Use - 2 indicators (12 items) 5) Writing Strategy Use - 3 indicators (10 items) 6) Translation Strategy Use - 2 indicators (6 items) Each item was rated on a four-point Likert scale (1-4) from 1, standing for: this strategy doesn’t fit for me to 4, standing for: I often use this strategy and like it. To assess internal consistency reliability of the LLL questionnaire, Cronbach’s alpha coefficient was employed, Cronbach’s alpha for the English LLS for in the Thai version were ranging from 0.86 to 0.92, which exceed the guidelines for adequate reliability in terms of internal consistency (Nunnally, 1978), and confirmed that the scales could be used to measure the LLL skills with confidence. Statistical analysis involved computing and analyzing means (M) and standard deviations (SD), determining Pearson correlation coefficient as a measure of the relationship between pairs of indicators. Confirmatory Factor Analyses (CFA) was used to examine the unidimensionality of a measurement model of English LLS, which is used to compare between the hypothesized model and the sampled data set. The goodness-of-fit for the LLS models was evaluated, In order to test the construct validity, various fit indices were employed, e.g. chi-square goodness of fit, chi-square per degree of freedom (chi-square/df), comparative fit index (CFI), the Tucker-Lewis index (TLI), a.o. The significance of factor loadings are greater than 0.50 with p < .05, the factorial validity and convergent validity at the indicator level is confirmed (Hair, Black, Babin, & Anderson, 2010). The correlation coefficients between the strategies were statistically significant (p < .01) and positively related, values ranged from poor (.61) to high (.75). The Kaiser-Meyer-Olkin (KMO) index, was .91, and Bartlett's test of sphericity, was 897.60 (p = .00). These statistical values supported the use of CFA in this study.

Expected Outcomes

This study evaluated the construct and factorial validity of the LLS model using CFA. Initially, Model 1, the original LLS measurement model with six strategies did not yield confirmed model fit. The standardized factor loading (standardized regression weight) of “Translation Strategy Use” had the value very low and less than .50 (B = .228). to improve the model, the Translation Strategy was dropped out of this study. The revised LLS measurement model (Model 2, 5 strategies) was performed. The chi-square test of goodness-of-fit suggests that the revised LLS model fits well to the data (chi-square goodness of fit (4) = 5.605, p = .0.231, chi-square per degree of freedom = 1.401). The other fit indices also confirmed that the hypothesized revised LLS model was consistent with observed data obtained from IT students in Thailand and support the accuracy and applicability of the model. Based on the present statistical analyses, this study can conclude that the construct of the measurement model of the revised English LLS with five strategies, as developed by Cohen, Oxford, and Chi (2009; Kappler, Cohen, & Paige, 2009), from Center for Advanced Research on Language Acquisition (CARLA) at University of Minnesota. is valid, and applicable when applied to Information Technology (IT) students in Thailand. “Speaking Strategy Use” and “Listening Strategy Use” were confirmed to represent the most important strategy and vital skills to have and to develop. The authors consider that this systematically tested LLS measurement model 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, which is the target of every educational institution. Other important findings will be discussed in detail in the conference.

References

1. Ardasheva , Y., Tretter, T.R. (2013). Strategy Inventory for Language Learning–ELL Student Form: Testing for Factorial Validity, The Modern Language Journal, 97, 2. 2. Bremner S. (2000). Language Learning strategies and language proficiency: investigating the Relationship in Hong-Kong, Canadian Modern Language Review, Vol. 55, No. 4, p. 490-514. 3. Cohen, A. D., Oxford, R. L., & Chi, J. C. (2009). Language strategy use inventory. Minneapolis, MN: University of Minnesota, Center for Advanced Research on Language Acquisition (CARLA). Retrieved from http://carla.umn.edu/maxsa/documents/LanguageStrategyInventory_MAXSA_IG.pdf. 4. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. 5. Hair, Jr., J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Pearson Prentice Hall. 6. Holmes, K. P., Rutledge, S., & Gauthier, L. R. (2009). Understanding the cultural-linguistic divide in American classrooms: Language learning strategies for a diverse student population. Reading Horizons, 49(4), 285-300. 7. Hsiao, T–Y., Oxford, R.L. (2002). Comparing Theories of Language Learning Strategies: A Confirmatory Factor Analysis, The Modern Language Journal, Volume 86, Issue 3, p. 368–383. 8. Kline, P. (1994). An easy guide to factor analysis. London: Routledge. 9. Munro, B. H. (2005). Statistical methods for health care research. Philadelphia: Lippincott Williams & Wilkins. 10. Murray, B. (2010). Students’ language learning strategy use and achievement in the Korean as a foreign language classroom, Foreign Language Annals, Volume 43, Issue 4, Winter 2010, p. 624–634. 11. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). NY: McGraw Hill. 12. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw Hill. 13. Oxford, R.L. (1990). Language Learning Strategies: What every teacher should know. Boston: Heinle. 14. Riazi, A. (2007). Language Learning Strategy Use: Perceptions of Female Arab English Majors, Foreign Language Annals, v40 n3 p. 433-440. 15. Rudzinska, I. & Khampirat, B. (2015). Learning Motivation Orientation And Learning Strategies In Thailand And Latvian Students, ECER 2015, Budapest. The European Conference on Educational Research „Education and Transition, Contributions from Educational Research”. 16. Rudzinska, I. & Khampirat, B. (2016). Factors Promoting and Impeding Qualitative Foreign Language Learning in Thai and Latvian HEI Students, ECER 2016, Dublin, Leading Education: The Distinct Contributions of Educational Research and Researchers. 17. Rudzinska, I. (2011). Quality Management in the Formation of Student Professional Foreign Language Competence, PhD Thesis, University of Latvia.

Author Information

Ieva Rudzinska (presenting / submitting)
Latvian Academy of Sport Education
Rīga
Buratin Khampirat (presenting)
Suranaree University of Technology
Institute of Social Technology
Nakhon Ratchasima

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