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ScienceDirect Procedia - Social and Behavioral Sciences 191 (2015) 597 – 604

WCES 2014

Cross-Cultural Adaptation And Psychometric Properties Of The Estonian Version Of MSLQ Katrin Saks a*, Äli Leijen a, Triin Edovald b, Kandela Õun a b

a University of Tartu, Tartu, Estonia NatCen Social Research, United Kingdom

Abstract Research has suggested that in order to improve learner's academic achievements and ability to self-regulate, it is highly important to measure their aptitude to self regulate (Boekaerts and Corno, 2005). The Motivated Strategies for Learning Questionnaire (MSLQ) is an 81-item self-report instrument that measures the use of learning strategies and the level of student motivation. The current paper describes the adaptation of the MSLQ for the use in Estonian context and explores the psychometric properties of the adapted questionnaire. The original English version of the MSLQ was translated into Estonian using translation/back-translation method. The semantic equivalence of the questionnaire items was assessed by nine native English speakers with substantive expertise in educational studies and/or research methods. A sample of university students (N = 295) in Estonia was used to pilot-test the questionnaire. A reliability analysis produced coefficient alphas which ranged from .34 to .90 for the scale scores and .92 as the overall score. Two exploratory factor analyses (EFA) were conducted to assess the content validity of the instrument. Results indicated a satisfactory fit to the data at the component level but less satisfactory at the subscale level. © Published by by Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license ©2015 2014The TheAuthors. Authors. Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and peer-review under responsibility of the Organizing Committee of WCES 2014. Selection and peer-review under responsibility of the Organizing Committee of WCES 2014

Keywords: Self-regulation; self-regulated learning; self-regulated learning skills; motivation; learning strategies; college students; exploratory factor analysis; internal validity; content validity

1. Introduction Self-regulated learning (SRL) has a growing importance in today’s educational discourse, that is why it needs to be unequivocally defined and precisely measured in the teaching-learning context (Winne and Perry, 2005; * Katrin Saks. Tel.: +37256159248 E-mail address: [email protected]

1877-0428 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and peer-review under responsibility of the Organizing Committee of WCES 2014 doi:10.1016/j.sbspro.2015.04.278

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Zimmerman, 2000). According to Pintrich (2000), SRL is an active, constructive process whereby learners set goals for their learning and attempt to monitor, regulate and control their cognition, motivation, and behaviour, guided and constrained by their goals and contextual features on the environment. The present research draws on the general cognitive view of motivation and learning strategies. Improving learner's academic achievement and ability to selfregulate requires measuring their aptitude to self-regulate as highly important (Boekaerts and Corno, 2005). This in turn enables to enhance students’ self-regulated learning skills. The most widely-used instrument for measuring learners’ self-regulated learning skills is the Motivated Strategies for Learning Questionnaire (MSLQ) by Pintrich (1991). The MSLQ is an 81-item Likert-scale self-report instrument with scales from 1-7 which was originally designed to assess college students’ motivational orientations and their use of different learning strategies. The MSLQ has two components: one of motivation and the other of learning strategies. The components are divided into 15 subscales. The MSLQ has been translated into more than 20 different languages and has undergone formal assessment of validity and reliability in several other languages such as Portuguese (McKeachie et al, 1995), Spanish (Ramirez-Dorantes et al., 2013) and Chinese (Rao and Sachs, 1999; Lee et al, 2010). Motivation and learning strategies being directly linked to students’ ability to self-regulate their learning activities, are not considered static traits of the learner but dynamic and contextually bound (Duncan and McKeachie, 2005). Previous research has shown that the internal consistency of the MSLQ was estimated relatively good (Pintrich et al, 1993). The majority of the Cronbach’s alphas for the individual scales were acceptable, ranging from .52 to .93. The two confirmatory factor analyses which were conducted in the test-period suggested reasonable factor validity (Pintrich et al., 1993). The subscales have shown promising predictive validity for academic performance (Khatib, 2010; Kitsantas et al, 2008; Sachs et al, 2001, Pintrich et al, 1993). However, the results reported by Pintrich (1993)have not been interpreted as positive by all researchers. Dunn et al have claimed that “those indices indicate that the original data fit the model poorly and the proposed latent structure was very problematic” (2011). Therefore, he insists that it is necessary to continue studying the factor structure of the MSLQ (e.g, based on exploratory factor analysis (EFA)) to find out whether and how the results depart from the hypothesised model (Dunn et al, 2011). The results of EFA and CFA conducted by Hamilton and Akhter did not confirm the original factor structure (2009). They suggest that some items in some subscales need revision (Hamilton and Akhter, 2009). Davenport (2003), who found satisfactory fit of the sample data to original model, also suggested that slight modifications to the model would still produce better fitting. Given the increasingly widespread idea in the educational context that it is the student who must set goals, monitor and evaluate their academic performance, in other words self-regulate their learning, and in the absence of valid and reliable instruments that would serve this purpose in Estonia, the aim of this research was to translate, adapt and explore the initial psychometric properties of the MSLQ. 2. Methods 2.1 Translating and adapting the instrument In the adaptation process of the MSLQ into Estonian, the method adapted from Guillemin and colleagues (1993) was used. The adapted process included the following steps: (1) translating the original instrument into Estonian by one translator, (2) linguistic editing by an Estonian language expert, (3) back-translation by another independent translator, (4) comparing and assessing semantic equivalence of the source and back-translated versions by nine native English speakers with expertise in educational studies and/or research methodology using a 5-point scale for assessing each statement, (5) semantic editing of the statements with an average score of 3 and below on the 5-point scale, (6) asking the respondents to assess the overall usability of the adapted instrument and the equivocalness of terms while collecting data.

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2.2 Participants To pilot-test the Estonian version of the MSLQ, data were collected from the students within 12 subject domains and 7 disciplines at the University of Tartu, from September to November 2013. The sample included 295 students, 80% of them being female and 20% male. 53% of the respondents were in the age group of 21-30, 27% under 20 and 20% over 31 years old. 74% of the people were undergraduates and 26% were doing their master studies. 60% were full-time students and 40% part-time open university students. 2.3 Data analysis Data analysis involved assessment of reliability, EFA and calculation of item-total correlations. The reliability index of Cronbach Alpha was estimated for each of the subscales and the overall scale. The descriptive statistics was used to describe the means and standard deviations of all 15 subscales and the whole instrument as well as for gender, 3 age groups and study forms. The structural relations of MSLQ subscales for motivational and learning strategies components were explored using EFA. All statistical analyses were performed using SPSS (Statistical Package for Social Sciences) for Windows, version 19. 3. Results As no significant outliers appeared in the course of analysis, there was no reason to remove any items. A couple of outliers appearing at the answer level were taken into consideration in the final analysis. 3.1 Descriptive statistics The respondents assessed the items on the scale of 1 (not at all true of me) to 7 (very true of me). The overall mean of the scale as estimated with the Estonian version of the MSLQ was 4.5, with a standard deviation of 1.7. The Task value subscale and Control of learning beliefs subscale resulted in the highest mean score (M=5.6, SD=1.2 and 1.4 respectively), whereas the subscale of Test anxiety resulted in the lowest mean score (M=3.6, SD=1.9). The mean scores and standard deviations of all 15 subscales for males and females, three age groups, and regular and open university students are shown in Table 1.

Table 1. The means and standard deviations of MSLQ subscales Subscale IG EG TV CB SE TA R E O CT MSR TS ER PL

Overall Mean (SD) 5.1 (1.4) 4.3 (1.8) 5.6 (1.2) 5.6 (1.4) 4.8 (1.3) 3.6 (1.9) 4.4 (1.7) 4.9 (1.6) 4.4 (1.9) 4.0 (1.7) 4.3 (1.7) 4.9 (1.8) 4.6 (1.8) 4.0 (1.7)

Gender Female Male 5.2 (1.4) 4.8 (1.4) 4.3 (1.8) 4.1 (1.7) 5.7 (1.2) 5.2 (1.3) 5.6 (1.4) 5.5 (1.5) 4.9 (1.3) 4.8 (1.3) 3.7 (1.9) 3.2 (1.8) 4.5 (1.7) 3.9 (1.6) 4.9 (1.6) 4.6 (1.5) 4.6 (1.8) 3.5 (1.8) 3.9 (1.7) 4.1 (1.6) 4.3 (1.7) 3.9 (1.7) 5.0 (1.8) 4.6 (1.7) 4.6 (1.8) 4.3 (1.6) 4.0 (1.5) 3.9 (1.7)

…-20 4.9 (1.3) 5.0 (1.6) 5.7 (1.1) 5.7 (1.3) 4.7 (1.3) 3.9 (1.8) 4.5 (1.7) 4.7 (1.6) 4.2 (1.9) 3.7 (1.6) 4.3 (1.6) 5.0 (1.7) 4.9 (1.6) 4.1 (1.7)

Age groups 21-30 5.0 (1.4) 4.0 (1.8) 5.4 (1.3) 5.5 (1.5) 4.8 (1.3) 3.4 (1.9) 4.2 (1.7) 4.8 (1.6) 4.2 (1.9) 4.0 (1.7) 4.1 (1.7) 4.8 (1.8) 4.5 (1.8) 3.9 (1.7)

Form 31-… 5.6 (1.3) 4.0 (1.7) 6.0 (1.1) 5.7 (1.4) 5.1 (1.2) 3.7 (1.9) 5.0 (1.6) 5.3 (1.5) 5.1 (1.8) 4.2 (1.8) 4.5 (1.8) 5.0 (1.9) 4.2 (2.0) 3.9 (1.8)

Regular 5.0 (1.4) 4.3 (1.7) 5.5 (1.2) 5.5 (1.4) 4.8 (1.3) 3.5 (1.8) 4.2 (1.7) 4.7 (1.7) 4.2 (1.9) 3.8 (1.6) 4.3 (1.7) 5.0 (1.7) 5.0 (1.5) 4.1 (1.7)

OU 5.2 (1.4) 4.2 (1.8) 5.7 (1.2) 5.7 (1.4) 4.9 (1.3) 3.7 (1.9) 4.7 (1.6) 5.1 (1.5) 4.7 (1.8) 4.2 (1.7) 4.3 (1.8) 4.8 (1.9) 3.9 (2.0) 3.7 (1.7)

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Katrin Saks et al. / Procedia - Social and Behavioral Sciences 191 (2015) 597 – 604 HS Overall

4.8 (1.7) 4.5 (1.7)

4.9 (1.7) 4.7 (1.7)

4.6 (1.6) 4.25 (1.6)

5.0 (1.6) 4.7 (1.6)

4.7 (1.7) 4.5 (1.7)

5.0 (1.5) 4.8 (1.7)

4.9 (1.6) 4.6 (1.6)

4.7 (1.7) 4.6 (1.7)

IG-Intrinsic goal orientation; EG-Extrinsic goal orientation; TV-Task value; CLB-Control of learning beliefs; SE-Self-efficacy; TA-Test anxiety; R-Rehearsal; E-Elaboration; O-Organization; CT-Critical thinking; MSR-Metacognitive self-regulation; TS-Time and study environment; EREffort regulation; PL-Peer learning; HS-Help seeking.

3.2 Reliability The Cronbach’s alpha coefficient of the total MSLQ was 0.92. The reliabilities ranged from 0.34 for help seeking to 0.90 for self-efficacy. Seven subscales out of fifteen remained below the acceptable level of .70 (Nunnally and Bernstein, 1994), all of them but time and study environment have a low number of items (3, 4). The other subscales were above .70. The time and study environment subscale also had many items (5 out of 8) with unacceptably low item-total correlations. The other subscales with the similar problem were help seeking (2 out of 3), effort regulation (2 out of 4) and metacognitive self-regulation (2 items out of 12). The big number of items with low item correlation arises the question of their suitability in the subscale and the necessity of dropping them. 3.3 Exploratory factor analysis Two EFAs were conducted focusing on two scales: (1) motivation and (2) learning strategies. Principal axis factoring, varimax rotation was conducted. According to the Kaiser rule of eigenvalues (Kaiser, 1960), up to a 7factor analysis could have been conducted in the case of motivation, and a 13-factor analysis for learning strategies. However, the 6- and 9-factor analysis were chosen (with eigenvalues of 1.09 and 1.22 respectively) with the purpose of checking the factor structures according to the division of Pintrich’s(1993) MSLQ classification. The majority of factor loadings were statistically significant rising above 0.4 (Appendices A.1 and A.2). Factor loadings for the 6factor structure of motivation greater than or equal to 0.4 accounted for over 62% of the variance that explains a little less than two thirds of the sub-components being represented by the items in the motivation scales of the MSLQ. The factors that formed can be distinguished by three components - value, expectancy and affect. The subscales are distinguishable for task value, self-efficacy for learning and performance, and test anxiety. The other groups that formed are combinations of different subscales. Factor loadings for the 9-factor structure of learning strategies greater than or equal to 0.4 accounted for over 55% of the variance explaining more than half of learning strategies scales of the MSLQ. The factors that formed are clearly distinguishable for components. The subscales loaded best for metacognitive self-regulation and time and study environment, other factors that formed reveal different combinations of metacognitive and cognitive strategies, and resource management strategies. 4. Discussion and conclusions The current paper describes the adaptation of the MSLQ for the use in Estonian context and explores the psychometric properties of the adapted questionnaire . The developers of the MSLQ claim that the coefficients for the scales are robust and demonstrate good internal consistency (Pintrich et al., 1993), even though several subscales have reliability values below .70. The results from the current study revealed that the Estonian version of the MLSQ contained adequate internal validity for describing most of the motivational and learning strategies. However, there were relatively low reliability values for 7 subscales which may be caused by the small number of items that form these subscales (4, 3). Similar problem has been detected in other studies as well (Purdie et al, 2000; Artino, 2005; Taylor, 2012). When compared the alphas to the data from the original assessment, there was consistency in the coefficient alphas for 5 out of 15 subscales. Of the areas of inconsistencies, the differences in values for coefficient alpha ranged from .03 to .23. The overall reliability value was .92 which is acceptable supporting previous studies with a similar consistent result (Barnard et al, 2009). However, this result would need to be interpreted with caution


601

as the relatively large number of items in the MSLQ can inflate the value of alpha in this analysis. In general terms, the majority results of internal consistency scores obtained in the analysis were acceptable and quite similar to those reported for the MSLQ. However, no attempt has been made to directly compare the results at the time of interpretation due the socio-economic and cultural differences among target populations of both studies. In brief, the EFAs used to test Pintrich’s 2-scale instrument MSLQ, provided a satisfactory fit to the data suggesting that MSLQ is a potentially suitable instrument for measuring motivation and self-regulation among Estonian university students. In the motivation scale the three components of value, expectancy and affect, load in separate factors, the subscales’ loadings are clearly distinguishable for Task value, Self-efficacy for learning and performance, and Test anxiety which form independent factors. In the learning strategies scale the general division was a little bit more cluttered. While the components are well distinguishable, the factors are formed of different combinations of subscales. Unlike the research results of Duncan and McKeachie (2005), the three general aspects of metacognition – planning, monitoring and regulating – did not load into one factor in our analysis. In general, it can be concluded that the MSLQ proved to be a satisfactory instrument for measuring motivation and somewhat satisfactory for measuring learning strategies within the context of the sample of the current study. Acknowledgements The present research was supported by the European Social Fund. Appendix A. Factor loadings of EFA-s A.1. Factor loadings for the 6-factor structure

27 task value 17 task value 23 task value 26 task value 22 intrinsic goal orientation 10 task value 12 self-efficacy 7 extrinsic goal orientation 20 self-efficacy 31 self-efficacy 21 self-efficacy 5 self-efficacy 6 self-efficacy 29 self-efficacy 15 self-efficacy 19 test anxiety 8 test anxiety 3 test anxiety 14 test anxiety 28 test anxiety 30 extrinsic goal orientation 1 intrinsic goal orientation 24 intrinsic goal orientation

1 ,842 ,841 ,781 ,734 ,718 ,699 ,550 ,428

,442

2

Component 3 4

,834 ,742 ,737 ,732 ,676 ,663 ,661

,500 ,536 ,783 ,725 ,701 ,678 ,670 ,541 ,612 ,541

5

6

602


13 extrinsic goal orientation 2 control of learning beliefs 18 control of learning beliefs 16 intrinsic goal orientation 4 task value 9 control of learning beliefs 25 control of learning beliefs 11 extrinsic goal orientation Eigenvalue

-,510

,440 ,444

,661 ,654 ,555 ,490 ,717 ,716 ,479

8,94 28,9

% variance

3,93 12,7

2,1 6,77

1,68 5,43

1,4 4,51

1,1 3,52

A.2. Factor loadings for the 9-factor structure

62 elaboration 66 critical thinking 81 elaboration 64 elaboratin 51 critical thinking 47 critical thinking 71 critical thinking 53 elaboration 61 MSR 69 elaboration 46 rehearsal 32 organisation 42 organisation 63 organisation 39 rehearsal 41 MSR 59 rehearsal 76 MSR 54 MSR 44 MSR 67 elaboration 72 rehearsal 78 MSR 36 MSR 56 MSR 49 organisation 55 MSR 79 MSR 60 effort regulation 37 effort regulation 80 time and study environment 33 MSR

1 ,741 ,738 ,712 ,696 ,661 ,616 ,614 ,534 ,509 ,495 ,416

,447

2

3

4

Component 5 6

,448 ,407 ,486 ,650 ,633 ,614 ,601 ,587 ,538 ,503 ,417 ,401 ,317

,439

,578 ,561 ,559 ,549 ,546 ,516 ,514 ,445 ,855 ,833 ,747 ,738

7

8

9

603

Katrin Saks et al. / Procedia - Social and Behavioral Sciences 191 (2015) 597 – 604 57 MSR 65 time and study environment 70 time and study environment 35 time and study environment 43 time and study environment 74 effort regulation 48 effort regulation 68 help seeking 75 help seeking 45 peer learning 50 peer learning 40 help seeking 34 peer learning 38 critical thinking 77 time and study environment 52 time and study environment 58 help seeking 73 time and study environment Eigenvalue

,525

11,58

3,55

2,92

2,60

2,04

1,59

1,39

1,28

% variance

22,70

6,96

5,73

5,10

4,00

3,11

2,72

2,50

,689 ,679 ,664 ,582 ,506 ,448 ,855 ,794 ,732 ,537 -,419 ,366 ,813 ,614 ,454 ,630 -,385 1,22 2,39

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