the impacts of English LLS and meaningful to be considered for Factor Analysis Test of Strategy Use Factors because the figures satisfy the four requirements of the test (see Tables 3.5, 3.6, 3.7, and 3.8 for Factor Analysis):
(1) KMO value is 0.898 (between 0.5 and 1.0)
(2) Barlett Sig. is 0.000 which is lower than 5%, this means that the figures are relevant to the analysis.
(3) The cumulative eigenvalues are 68.4 % (higher than 50%)
(4) Factor loading values are all higher than 0.3
Table 3.5. KMO and Bartlett's Test
.898 | ||
Bartlett's Test of Sphericity | Approx. Chi-Square | 636.195 |
df | 15 | |
Sig. | .000 |
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The use of language learning strategies in English reading at Doan Ket secondary school - An investigation - 8 -
The Research Objectives And Research Questions -
The use of language learning strategies in English reading at Doan Ket secondary school - An investigation - 10 -
Students’ Learning Strategy Use Synthesized From The Questionnaires -
The use of language learning strategies in English reading at Doan Ket secondary school - An investigation - 13 -
The use of language learning strategies in English reading at Doan Ket secondary school - An investigation - 14
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Table 3.6. Communalities
Initial | Extraction | |
Memory Strategy | 1.000 | .569 |
Cognitive Strategy | 1.000 | .705 |
Compensation Strategy | 1.000 | .689 |
Metacognitive Strategy | 1.000 | .787 |
Affective Strategy | 1.000 | .725 |
Social Strategy | 1.000 | .628 |
Extraction Method: Principal Component Analysis.
Table 3.7. Total variance explained
Initial Eigenvalues | Extraction Sums of Squared Loadings | |||||
Component | Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % |
1 | 4.104 | 68.405 | 68.405 | 4.104 | 68.405 | 68.405 |
2 | .572 | 9.538 | 77.943 | |||
3 | .448 | 7.469 | 85.411 | |||
4 | .346 | 5.773 | 91.184 | |||
5 | .307 | 5.116 | 96.301 | |||
6 | .222 | 3.699 | 100.000 |
Table 3.8. Component matrixa
Component | |
1 | |
Metacognitive Strategy | .887 |
Affective Strategy | .851 |
Cognitive Strategy | .840 |
Compensation Strategy | .830 |
Social Strategy | .793 |
Memory Strategy | .755 |
Extraction Method: Principal Component Analysis (a.1 components extracted.)
CORRELATION ANALYSIS
This study analyzed the mean size coefficients among LLS to identify if there was any of six independent variables - strategies of language learning strategies correlated with or without correlations with the dependent variable - English proficiency, then decided to run Multiple Regression for this further analysis or to conclude whether the LLS employed by the sixth graders met this study or not. Surprisingly, correlation appeared to be the strongest among LLS
altogether in case of LLS combination, but only one of the six variables had a slight correlation with students’ English proficiency – Compensation strategy (see Table 3.9. and Table 3.10. for Correlation Analysis). The variation of variables in direct or inverse proportion is not significant, but in what ways the students apprehend English language.
Table 3.9. Correlations among students’ LLS
Memory Strategy | Cognitive Strategy | Compensation Strategy | Metacognitive Strategy | Affective Strategy | Social Strategy | ||
Memory Strategy | Pearson Correlation | 1 | .540** | .630** | .577** | .541** | .496** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | |
Cognitive Strategy | Pearson Correlation | .540** | 1 | .637** | .741** | .652** | .578** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | |
Compensation Strategy | Pearson Correlation | .630** | .637** | 1 | .688** | .599** | .564** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | |
Metacognitive Strategy | Pearson Correlation | .577** | .741** | .688** | 1 | .737** | .629** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | |
Affective Strategy | Pearson Correlation | .541** | .652** | .599** | .737** | 1 | .674** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | |
Social Strategy | Pearson Correlation | .496** | .578** | .564** | .629** | .674** | 1 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 |
**. Correlation is significant at the 0.01 level (2-tailed).
Table 3.10. Correlations between students’ LLS and English scores
Memory Strategy | Cognitive Strategy | Compensation Strategy | Metacognitive Strategy | Affective Strategy | Social Strategy | English Marks | ||
Memory Strategy | Pearson Correlation | 1 | .540** | .630** | .577** | .541** | .496** | .090 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .233 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 | |
Cognitive Strategy | Pearson Correlation | .540** | 1 | .637** | .741** | .652** | .578** | .133 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .080 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 | |
Compensation Strategy | Pearson Correlation | .630** | .637** | 1 | .688** | .599** | .564** | .160* |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .034 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 | |
Metacognitive Strategy | Pearson Correlation | .577** | .741** | .688** | 1 | .737** | .629** | .134 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .075 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 | |
Affective Strategy | Pearson Correlation | .541** | .652** | .599** | .737** | 1 | .674** | -.007 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .929 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 | |
Social Strategy | Pearson Correlation | .496** | .578** | .564** | .629** | .674** | 1 | .047 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .534 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 | |
English Marks | Pearson Correlation | .090 | .133 | .160* | .134 | -.007 | .047 | 1 |
Sig. (2-tailed) | .233 | .080 | .034 | .075 | .929 | .534 | ||
N | 176 | 176 | 176 | 176 | 176 | 176 | 176 |
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
MULTIPLE REGRESSION ANALYSES
The result of the questionnaires was affirmed by multiple regression analysis. First, after analyzing the Coefficient Correlation (R) as the association there was one independent variable left with the dependent variable, and the square multiple regressions (R2=0.026) was seen lower than 0.5 (this made difficulties as the other indicators were excluded out of the analysis process, thus inferring at an acceptable level but not 100% of assertion). Second, the researcher needed a mixture between the research hypotheses and the fact of changes in measuring the simultaneous correlation of LLS. Third, the researcher measured secondary school students’ English reading performance (via the scores in English course without separating language skills due to lack of school conditions) to see the partial effect of every LLS use, particularly just noted the impact of reading strategies on their English proficiency (see Tables 3.11., 3.12., 3.13, and 3.14 on Multiple Regression Analyses).
Table 3.11. Model summaryb in multiple regression analyses
R | R Square | Adjusted R Square | Std. Error of the Estimate | Durbin- Watson | |
1 | .160a | .026 | .020 | 1.4525 | 1.697 |
a. Predictors: (Constant), Compensation Strategy
b. Dependent Variable: English Marks
Table 3.12. ANOVAb for multiple regression analyses
Sum of Squares | df | Mean Square | F | Sig. | ||
1 | Regression | 9.634 | 1 | 9.634 | 4.566 | .034a |
Residual | 367.113 | 174 | 2.110 | |||
Total | 376.747 | 175 |
a. Predictors: (Constant), Compensation Strategy
b. Dependent Variable: English Marks
Table 3.13. Coefficientsa for multiple regression analyses
Unstandardized Coefficients | Standardized Coefficients | t | Sig. | Collinearity Statistics | ||||
B | Std. Error | Beta | Tolerance | VIF | ||||
1 | (Constant) | 6.433 | .459 | 14.010 | .000 | |||
Compensation Strategy | .287 | .134 | .160 | 2.137 | .034 | 1.000 | 1.000 |
a. Dependent Variable: English Marks
Table 3.14. Residuals statistics for multiple regression analyses
Minimum | Maximum | Mean | Std. Deviation | N | |
Predicted Value | 6.720 | 7.868 | 7.386 | .2346 | 176 |
Residual | -4.0814 | 2.4778 | .0000 | 1.4484 | 176 |
Std. Predicted Value | -2.838 | 2.054 | .000 | 1.000 | 176 |
Std. Residual | -2.810 | 1.706 | .000 | .997 | 176 |
a. Dependent Variable: English Marks
Based on the general descriptive statistics of LLS across participants, this study was focused more in LLS and reading strategy instructions for students’ English proficiency, especially low proficient learners. However, the multiple regressions analysis (R) was unable to run in joints because of its unexplainable predictors and limitation of research time without repeating the factors analysis. Consequently, the presentation of results was collected from the focus interviews and the comparison between total mean coefficient and students’ scorecards in English course as a replacement of this multiple regressions analysis. Therefore, the unexplainable indicators in this study were considered absurd factors as expressed in the abstract.
3.7. Timeline for the study
The investigation was started at the beginning of the school year (September 2019). It took a nine-month span to finish the investigation at the end of the school year (July 2020, an exceptional time of COVID-19 pandemic inclusive) through Questionnaire, Interviews, and Document research as mentioned above.
Table 3.15. Timeline for the Study
Timing | |
Learning plan | August 2018 |
Draft of research proposal | December 2019 |
Complete research proposal | March 2020 |
Initial seminar | March 2020 |
Submit Research Methodology | August 2020 |
Data collection | September 2019 – July 2020 |
Submit Results of Questionnaire | August 2020 |
Submit Results of Interview | August 2020 |
Submit Discussion | September 2020 |
Submit Literature Review | September 2020 |
Submit Revision of Literature Review -Research Methodology - Research Results - Discussion | November 2020 |
Submit Introduction - Conclusion | November 2020 |
Draft thesis | December 2020 |
Submit final thesis | April 2021 |
3.8. Chapter summary
This chapter restated the research objectives and research questions, presented the approach to the research - research methodology. The chapter also described research setting, research sites and participants. It provided the procedures of data collection including samples collection and instruments for data collection, justified the process of data analysis which characterize the trustworthiness of the study and language strategy use inventory. Finally, the chapter sketched the timeline for the study.
The approach to this investigation was from DK students’ LLS use. The mixed methodology design was used to collect data (quantitative and qualitative). The research setting, research sites and participants were described to understand the current situation of Doan Ket Secondary School. The samples were collected in a simple way as convenient samples, and the instruments for collecting data included questionnaires, focus interviews, and students’ scores in English course. Questionnaires were used to assess the 6-grade students’ opinions on the English LLS used in class when the interviews carried on through the researcher’s observations were used to explore what deep meanings behind participants’ responses on English LLS. Students’ scores in English course representing students’ English learning achievement indicated its correlation with students’ LLS use, especially these students’ reading strategy use. A description of data analysis was begun with the trustworthiness of the study including credibility, dependability, confirmability, and transferability to augment this thesis validation. The study ended with the timeline visualizing an overall research.
The next chapter presents and discusses the results obtained from students through questionnaires and interviews.