The application of conceptual metaphors to teaching idioms to enghlish majored students at thu dau mot university m a

VIETNAM NATIONAL UNIVERSITY – HO CHI MINH CITY UNIVERSITY OF SOCIAL SCIENCES AND HUMANITIES FACULTY OF ENGLISH LINGUISTICS & LITERATURE THE APPLICATION OF CONCEPTUAL METAPHORS TO TEACHING IDIOMS TO ENGLISH-MAJORED STUDENTS AT THU DAU MOT UNIVERSITY A thesis submitted to the Faculty of English Linguistics & Literature in partial fulfillment of the Master’s degree in TESOL By PHẠM THÁI BẢO NGỌC Supervised by TÔ MINH THANH, Assoc Prof Dr HO CHI MINH CITY,i NOVEMBER 2015 STATEMENT OF AUTHORSHIP I certify that this thesis entitled “THE APPLICATION OF CONCEPTUAL METAPHORS TO TEACHING IDIOMS TO ENGLISH-MAJORED STUDENTS AT THU DAU MOT UNIVERSITY” is my own work This thesis has not been submitted for the award of any degree or diploma in any other institution Ho Chi Minh City, November 20, 2015 Phạm Thái Bảo Ngọc i RETENTION AND USE OF THE THESIS I hereby state that I, Phạm Thái Bảo Ngọc, being the candidate for the degree of Master in TESOL, accept the requirements of the University relating to the retention and use of Master’s Theses deposited in the Library In terms of these conditions, I agree that the original copy of my thesis deposited in the Library should be accessible for purposes of study and research in accordance with the normal conditions established by the Library for the care, loan and reproduction of theses Ho Chi Minh City, November 20, 2015 Phạm Thái Bảo Ngọc ii ACKNOWLEDGEMENT The appearance of only my name on the cover of this thesis does not mean that it is an individual effort In fact, the thesis was accomplished with the help of many individuals to whom I will always be grateful My deepest gratitude is to my supervisor, Assoc Prof Dr Tô Minh Thanh I have been particularly fortunate to have a supervisor who allowed me great freedom to make discoveries on my own, and at the same time gave me unflagging support whenever my steps wavered I am also thankful to her for careful proof-reading and line-by-line comments on my writing Her patience and guidance helped me weather many a crisis and finish this thesis I hope that one day I would become as good a mentor to my students as Ms Thanh has been to me My sincere thanks also go to Dr Lê Hoàng Dũng, Dr Nguyễn Hoàng Tuấn, Dr Nguyễn Thu Hương, Dr Đặng Tấn Tín, Dr Phó Phương Dung, and Dr Nguyễn Thị Kiều Thu for numerous discussions and lectures on related topics that helped me broaden my knowledge and sharpen my arguments for the thesis I am also deeply indebted to Dr Lý Quyết Tiến, the Dean of the Faculty of Foreign Languages at Thu Dau Mot University, for providing me with optimum conditions to conduct my research at this site I would like to acknowledge the academic staff, especially Mr Trịnh Huỳnh Chấn, and my colleagues at the faculty as well for their assistance and encouragement during the process of conducting and writing this thesis I also owe sincere thanks to my students, who are an inspiration to me, for their active participation in the study Without their support, my thesis would never have been accomplished Last but not least, I would like to dedicate this thesis to my beloved parents for always being there for me as a constant source of love, support and strength all these years Thanks to them, my dreams are born, nurtured and fulfilled I am blessed to be their child, as always iii ABSTRACT Contrary to the traditional view of idioms, cognitive linguists have demonstrated that the nature of idioms is not arbitrary and rote memorization is not the only way to learn them The discovery that several figurative idioms are semantically motivated by a common conceptual metaphor has opened up a path to more systematic and insightful learning However, it is still unclear to what extent the elaboration of conceptual metaphors could facilitate learners’ reception and production of idioms over time Besides, their attitudes towards the employment of conceptual metaphors have yet to be thoroughly explored This study is an attempt to fill in these gaps in the literature To address the issues, a quasi-experiment with the pre-test – post-test non-equivalent group design and an attitudinal survey were conducted on a sample of 69 Englishmajored students at Thu Dau Mot University The results of the study reveal that the explanation of conceptual metaphors was especially beneficial for the students’ reception of idioms over time, and to a lesser extent for their production of these idioms As compared to the traditional instruction, the effectiveness of applying conceptual metaphors to teaching was not particularly outstanding in the short term However, this cognitive approach showed its relatively long-lasting value, especially weeks after the instruction, in terms of the students’ idiom reception and production The employment of conceptual metaphors in teaching idioms also received positive feedback from the students, though the instruction itself exposed some shortcomings that need to be dealt with In view of these findings, the study discussed implications of the adoption of conceptual metaphors as an additional channel for idiom acquisition for EFL learners, teachers as well as syllabus and textbook designers Keywords: idioms, conceptual metaphors, CM-inspired instruction, reception, receptive knowledge, production, productive knowledge, motivation iv TABLE OF CONTENTS Statement of authorship i Retention and use of the thesis ii Acknowledgement iii Abstract iv Table of contents v List of abbreviations .ix List of tables x List of figures xiii Chapter Introduction 1.1 Background of the study 1.2 Context of the study 1.3 Aims of the study 1.4 Research questions and hypotheses 1.5 Significance of the study 1.6 Outline of the thesis Chapter Literature review 2.1 Overview of idioms and teaching idioms in EFL contexts 2.1.1 Definitions and features of idioms 2.1.2 Importance of teaching idioms to EFL learners 13 2.1.2.1 Language proficiency 13 2.1.2.2 Efficiency and richness in language use 14 2.1.2.3 Cultural understanding 16 2.1.3 Aspects of idiomatic competence 16 2.1.3.1 Reception and production 17 2.1.3.2 Recognition and recall 18 2.1.3.3 Comprehension and use 19 2.1.4 Explicit and implicit idiom instruction 20 2.1.5 Traditional and cognitive linguistic views of idioms and idiom teaching 23 2.1.5.1 Traditional view of idioms and idiom teaching 23 2.1.5.2 Cognitive linguistic view of idioms and idiom teaching 23 2.2 The Conceptual Metaphor Theory 27 v 2.2.1 Conceptual metaphors 27 2.2.2 The working mechanism of conceptual metaphors 27 2.2.3 The experiential basis of conceptual metaphors 29 2.3 The application of conceptual metaphors to teaching idioms 30 2.3.1 Theoretical support for applying conceptual metaphors to teaching idioms 30 2.3.2 Recent research on applying conceptual metaphors to teaching idioms 31 2.3.3 Issues yet to be resolved 38 2.4 Theoretical and empirical guidelines for the study 39 2.5 Summary 40 Chapter Methodology 41 3.1 Research design 42 3.2 Research site 45 3.3 Pilot study 45 3.4 Participants 46 3.5 Teaching materials 50 3.5.1 Selection of the target conceptual metaphors and idioms 50 3.5.1.1 Rationale for the selected topics 50 3.5.1.2 Selection of the target conceptual metaphors 52 3.5.1.3 Selection of the target idioms 52 3.5.2 Design of teaching materials 53 3.6 Research instruments 56 3.6.1 The Quick Placement Test 56 3.6.2 The Idiom Knowledge Test 57 3.6.2.1 Overview of the Idiom Knowledge Test 58 3.6.2.2 Test-item designing 59 3.6.2.3 Piloting and test reliability 60 3.6.2.4 Test administration and scoring 63 3.6.3 Attitudinal questionnaire 65 3.6.3.1 Design and construct 65 3.6.3.2 Piloting and reliability 68 3.7 Data collection procedure 69 3.8 Data analysis procedure 72 3.9 Summary 75 vi Chapter Results and discussion 76 4.1 Results 76 4.1.1 Preconditions of ANOVAs and Independent Samples T-Tests 76 4.1.2 Results of the Receptive Idiom Knowledge Test over time 79 4.1.2.1 Within-group comparison 79 4.1.2.2 Between-group comparison 83 4.1.3 Results of the Idiom Productive Knowledge Test over time 87 4.1.3.1 Within-group comparison 87 4.1.3.2 Between-group comparison 91 4.1.4 Results from the attitudinal questionnaire 96 4.1.4.1 General opinions about teaching and learning idioms 96 4.1.4.2 Reflection on the application of the CM-inspired instruction 101 4.1.4.3 Suggestions for further improvement 106 4.2 Discussion 107 4.2.1 Idiom reception over time 107 4.2.1.1 Within-group comparison 107 4.2.1.2 Between-group comparison 108 4.2.2 Idiom production over time 111 4.2.2.1 Within-group comparison 111 4.2.2.2 Between-group comparison 112 4.2.3 Attitudes towards the CM-inspired instruction 115 4.2.4 Possible ways to improve the CM-inspired instruction 122 4.3 Summary 124 Chapter Conclusions 125 5.1 Summary and contributions 125 5.2 Pedagogical implications 126 5.3 Limitations of the study 128 5.4 Recommendations for further study 129 References 131 Appendices 143 Appendix Interpretations of Research Questions and 144 Appendix 146 Appendix 2A Course syllabus – Writing (Vietnamese version) 147 vii Appendix 2B Course syllabus – Writing (English version) 152 Appendix SPSS output of the QPT results 157 Appendix Ten conceptual metaphors selected for the experiment 158 Appendix Sixty idioms selected for the experiment 164 Appendix Integration of the experiment into the Writing course 167 Appendix Quick Placement Test (version 2) 168 Appendix The Idiom Knowledge Test and how to design it 177 Appendix 8A The Idiom Knowledge Test (IKT) 178 Appendix 8B Detailed description of the IKT and how to design it 183 Appendix 8C General guidelines for test item formats 189 Appendix Questionnaires 190 Appendix 9A Control group – Questionnaire (English version) 191 Appendix 9B Control group – Questionnaire (Vietnamese version) 193 Appendix 9C Experimental group – Questionnaire (English version) 195 Appendix 9D Experimental group – Questionnaire (Vietnamese version) 199 Appendix 10 Students’ Handouts 203 Appendix 10A Control group – Students’ Handout (Week – ANGER) 204 Appendix 10B Experimental group – Students’ Handout (Week – ANGER) 209 Appendix 10C Control group – Students’ Handout (Week – LIFE) 214 Appendix 10D Experimental group – Students’ Handout (Week – LIFE) 219 Appendix 11 Lesson plans 224 Appendix 11A Control group – Lesson plan (Week – ANGER) 226 Appendix 11B Experimental group – Lesson plan (Week – ANGER) 229 Appendix 12 SPSS outputs of the tests of normality 233 Appendix 13 Result analysis of the IKT results for the CG 234 Appendix 14 SPSS output of within-group comparison 238 Appendix 14A SPSS output of the IKT results for the CG 239 Appendix 14B SPSS output of the IKT results for the EG 243 Appendix 15 SPSS output of between-group comparison 247 Appendix 15A SPSS output of the Receptive Idiom Knowledge Test results 248 Appendix 15B SPSS output of the Idiom Productive Knowledge Test results 249 Appendix 16 Pictorial illustration for ANGER AS HEATED FLUID IN A CONTAINER 251 viii LIST OF ABBREVIATIONS CG control group CM conceptual metaphor CMs conceptual metaphors CMT Conceptual Metaphor Theory EFL English as a Foreign Language EG experimental group IKT Idiom Knowledge Test L1 first language L2 second language M.A Master of Arts QPT Quick Placement Test SPSS Statistical Package for the Social Sciences TDMU Thu Dau Mot University ix overall statistically significant difference among the mean ranks of the CG in the three testing administrations (χ2(2) = 68.000, p = 0.000) The results presented in Table 7, however, only indicate the overall statistically difference in the means of three test administrations, but specifically where those differences arose was still uninformed To fill this lack of information, the Bonferroni post hoc test was used to find out which specific pairs of means differed Table Significance level in the Wilcoxon signed-rank tests regarding the CG’s results in the Productive Idiom Knowledge Test over time Z Asymp Sig (2-tailed) Post-test – Pretest -5.092b Idiom Productive knowledge Test - Test Statisticsa Strict marking Less strict marking Post-test Post-test Post-test Post-test Post-test 2 – Pre– Post-test – Pre– Post-test – Pre-test test test b c b b -5.096 -5.113 -5.096 -5.094 -5.126c 000 000 000 000 000 000 a Wilcoxon Signed Ranks Test b Based on negative ranks c Based on positive ranks As Table shows, three contrasts were performed in each case of marking using Wilcoxon tests with the Bonferroni correction, resulting in a significance level set at p < 017 Since the calculated value for each pair was, indeed, lower than 017, the null hypothesis of no difference found in the mean ranks of each pair was rejected In other words, there was a statistical significant difference between the pre-test and the immediate post-test (strict marking: Z=-5.092, p=.000; less strict marking: Z=-5.096, p=.000), the pre-test and the delayed post-test (strict marking: Z=-5.096, p=.000; less strict marking: Z=-5.094, p=.000), and the immediate post-test and the delayed post-test (strict marking: Z=-5.113; p=.000; less strict marking: Z=-5.126, p=.000) In sum, the scores of three test administrations for the control group were significantly different from one another 237 APPENDIX 14 SPSS OUTPUT OF WITHIN-GROUP COMPARISON 238 APPENDIX 14A SPSS OUTPUT OF THE IKT RESULTS FOR THE CG Receptive Idiom Knowledge Test Repeated-Measures ANOVA Within-Subjects Factors Measure: score time Dependent Variable RePre RePost1 RePost2 Descriptive Statistics Mean Receptive Knowledge Pre-test Receptive Knowledge Post-test Receptive Knowledge Post-test 5.15 24.38 18.00 Std Deviation 3.295 3.660 3.861 N 34 34 34 Mauchly's Test of Sphericitya Measure: score Within Mauchly's Subjects Effect W time Approx ChiSquare 928 2.408 df Sig 300 Epsilonb Greenhouse-Geisser Huynh-Feldt 932 986 Lower-bound 500 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix a Design: Intercept Within Subjects Design: time b May be used to adjust the degrees of freedom for the averaged tests of significance Corrected tests are displayed in the Tests of Within-Subjects Effects table Tests of Within-Subjects Effects Measure: score Source Type III Sum of Squares df Mean Square Sphericity Assumed 6527.196 3263.598 Greenhouse-Geisser 6527.196 1.865 3500.130 Huynh-Feldt 6527.196 1.972 3309.605 Lower-bound 6527.196 1.000 6527.196 48.137 48.137 48.137 48.137 66 61.540 65.083 33.000 729 782 740 1.459 time Sphericity Assumed Greenhouse-Geisser Error(time) Huynh-Feldt Lower-bound 239 F 4474.65 4474.65 4474.65 4474.65 Sig Partial Eta Squared 000 993 000 993 000 993 000 993 Tests of Within-Subjects Contrasts Measure: score Source time time Error(time) Type III Sum of Squares 2808.368 3718.828 30.132 18.005 Linear Quadratic Linear Quadratic df Mean Square 1 33 33 2808.368 3718.828 913 546 F Sig 3075.635 6815.996 000 000 Partial Eta Squared 989 995 Estimates Measure: score time Mean Std Error 5.147 24.382 18.000 95% Confidence Interval Lower Bound Upper Bound 3.997 6.297 23.105 25.659 16.653 19.347 565 628 662 Pairwise Comparisons Measure: score (I) time (J) time Mean Difference (I-J) Std Error -19.235* -12.853* 19.235* 6.382* 12.853* -6.382* Based on estimated marginal means * The mean difference is significant at the 05 level b Adjustment for multiple comparisons: Bonferroni 184 232 184 203 232 203 Sig.b 000 000 000 000 000 000 95% Confidence Interval for Differenceb Lower Bound Upper Bound -19.700 -18.770 -13.437 -12.268 18.770 19.700 5.871 6.893 12.268 13.437 -6.893 -5.871 Idiom Productive Knowledge Test 2.1 Strict marking N Productive Knowledge Pretest - Strict marking Productive Knowledge Posttest - Strict marking Productive Knowledge Posttest - Strict marking 34 Descriptive Statistics Std Mean Minimum Maximum Deviation 25th Percentiles 50th (Median) 75th 06 239 00 00 00 34 21.91 3.980 12 28 20.00 22.00 25.00 34 13.85 3.669 19 11.75 15.00 16.25 Friedman Test Ranks Productive Knowledge Pre-test - Strict marking Productive Knowledge Post-test - Strict marking Productive Knowledge Post-test - Strict marking Mean Rank 1.00 3.00 2.00 240 Test Statisticsa N Chi-Square df Asymp Sig a Friedman Test 34 68.000 000 Wilcoxon Signed Ranks Test Ranks N Mean Rank Sum of Ranks Negative Ranks 0a 00 00 34b 17.50 595.00 Productive Knowledge Post-test ( Strict marking) - Positive Ranks Productive Knowledge Pre-test (Strict marking) Ties 0c Total 34 Negative Ranks 0d 00 00 Productive Knowledge Post-test (Strict marking) Positive Ranks 34e 17.50 595.00 Productive Knowledge Pre-test (Strict marking) Ties 0f Total 34 Negative Ranks 34g 17.50 595.00 h Positive Ranks 00 00 Productive Knowledge Post-test (Strict marking) Productive Knowledge Post-test (Strict marking) Ties 0i Total 34 a Productive Knowledge Post-test - Strict marking < Productive Knowledge Pre-test - Strict marking b Productive Knowledge Post-test - Strict marking > Productive Knowledge Pre-test - Strict marking c Productive Knowledge Post-test - Strict marking = Productive Knowledge Pre-test - Strict marking d Productive Knowledge Post-test - Strict marking < Productive Knowledge Pre-test - Strict marking e Productive Knowledge Post-test - Strict marking > Productive Knowledge Pre-test - Strict marking f Productive Knowledge Post-test - Strict marking = Productive Knowledge Pre-test - Strict marking g Productive Knowledge Post-test - Strict marking < Productive Knowledge Post-test - Strict marking h Productive Knowledge Post-test - Strict marking > Productive Knowledge Post-test - Strict marking i Productive Knowledge Post-test - Strict marking = Productive Knowledge Post-test - Strict marking Test Statisticsa Productive Knowledge Productive Knowledge Productive Knowledge Post-test (Strict marking) Post-test (Strict marking) Post-test (Strict marking) - Productive Knowledge - Productive Knowledge - Productive Knowledge Pre-test (Strict marking) Pre-test (Strict marking) Post-test (Strict marking) Z -5.092b -5.096b -5.113c Asymp Sig (2-tailed) 000 000 000 a Wilcoxon Signed Ranks Test b Based on negative ranks c Based on positive ranks 2.2 Less strict marking N Productive Knowledge Pretest (Less strict marking) Productive Knowledge Posttest (Less strict marking) Productive Knowledge Posttest (Less strict marking) Descriptive Statistics Std Mean Minimum Maximum Deviation 25th 34 06 239 34 23.03 3.896 34 14.53 4.308 241 Percentiles 50th (Median) 75th 00 00 00 13 29 21.00 24.00 25.50 23 12.00 15.00 18.25 Friedman Test Ranks Mean Rank Productive Knowledge Pre-test - Less strict marking 1.00 Productive Knowledge Post-test - Less strict marking 3.00 Productive Knowledge Post-test - Less strict marking 2.00 Test Statisticsa N Chi-Square df Asymp Sig a Friedman Test 34 68.000 000 Wilcoxon Signed Ranks Test Ranks N Mean Rank Sum of Ranks Negative Ranks 0a 00 00 Productive Knowledge Post-test (Less strict Positive Ranks 34b 17.50 595.00 marking) - Productive Knowledge Pre-test (Less strict Ties 0c marking) Total 34 Negative Ranks 0d 00 00 Productive Knowledge Post-test (Less strict Positive Ranks 34e 17.50 595.00 marking) - Productive Knowledge Pre-test (Less strict Ties 0f marking) Total 34 Negative Ranks 34g 17.50 595.00 Productive Knowledge Post-test (Less strict Positive Ranks 0h 00 00 marking) - Productive Knowledge Post-test (Less i Ties strict marking) Total 34 a Productive Knowledge Post-test - Less strict marking < Productive Knowledge Pre-test - Less strict marking b Productive Knowledge Post-test - Less strict marking > Productive Knowledge Pre-test - Less strict marking c Productive Knowledge Post-test - Less strict marking = Productive Knowledge Pre-test - Less strict marking d Productive Knowledge Post-test - Less strict marking < Productive Knowledge Pre-test - Less strict marking e Productive Knowledge Post-test - Less strict marking > Productive Knowledge Pre-test - Less strict marking f Productive Knowledge Post-test - Less strict marking = Productive Knowledge Pre-test - Less strict marking g Productive Knowledge Post-test - Less strict marking < Productive Knowledge Post-test - Less strict marking h Productive Knowledge Post-test - Less strict marking > Productive Knowledge Post-test - Less strict marking i Productive Knowledge Post-test - Less strict marking = Productive Knowledge Post-test - Less strict marking Test Statisticsa Productive Knowledge Productive Knowledge Post-test (Less strict Post-test (Less strict marking) - Productive marking) - Productive Knowledge Pre-test Knowledge Pre-test (Less (Less strict marking) strict marking) b Z -5.096 -5.094b Asymp Sig (2-tailed) 000 000 a Wilcoxon Signed Ranks Test b Based on negative ranks c Based on positive ranks 242 Productive Knowledge Post-test (Less strict marking) - Productive Knowledge Post-test (Less strict marking) -5.126c 000 APPENDIX 14B SPSS OUTPUT OF THE IKT RESULTS FOR THE EG Receptive Idiom Knowledge Test Repeated-Measures ANOVA Within-Subjects Factors Measure: score time Dependent Variable RePre RePost1 RePost2 Descriptive Statistics Mean Std Deviation Receptive Knowledge Pre-test 4.86 3.362 Receptive Knowledge Post-test 25.20 3.376 Receptive Knowledge Post-test 23.91 3.364 N 35 35 35 Mauchly's Test of Sphericitya Measure: score Within Subjects Effect Epsilonb Greenhouse-Geisser Huynh-Feldt Lower-bound time 918 2.839 242 924 975 500 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix a Design: Intercept Within Subjects Design: time b May be used to adjust the degrees of freedom for the averaged tests of significance Corrected tests are displayed in the Tests of Within-Subjects Effects table Mauchly's W Approx Chi-Square df Sig Tests of Within-Subjects Effects Measure: score Source time Error(time) Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound Sphericity Assumed Greenhouse-Geisser Huynh-Feldt Lower-bound Type III Sum of Squares 9084.362 9084.362 9084.362 9084.362 25.638 25.638 25.638 25.638 df 1.848 1.949 1.000 68 62.821 66.270 34.000 243 Mean Square 4542.181 4916.634 4660.747 9084.362 377 408 387 754 F 12047.241 12047.241 12047.241 12047.241 Sig .000 000 000 000 Partial Eta Squared 997 997 997 997 Tests of Within-Subjects Contrasts Measure: score Source time time Error(time) Linear Quadratic Linear Quadratic Type III Sum of Squares 6355.557 2728.805 15.943 9.695 df Mean Square 1 34 34 6355.557 2728.805 469 285 F Sig 13553.966 9569.581 000 000 Partial Eta Squared 997 996 Estimates Measure: score time Mean Std Error 4.857 25.200 23.914 95% Confidence Interval Lower Bound Upper Bound 3.702 6.012 24.040 26.360 22.759 25.070 568 571 569 Pairwise Comparisons Measure: score (I) time (J) time Mean Difference (I-J) Sig.b Std Error -20.343* 147 * -19.057 164 20.343* 147 1.286* 127 19.057* 164 * -1.286 127 Based on estimated marginal means * The mean difference is significant at the 05 level b Adjustment for multiple comparisons: Bonferroni 95% Confidence Interval for Differenceb Lower Bound Upper Bound -20.714 -19.971 -19.469 -18.645 19.971 20.714 966 1.605 18.645 19.469 -1.605 -.966 000 000 000 000 000 000 Idiom Productive Knowledge Test 2.1 Strict marking N Productive Knowledge Pretest (Strict marking) Productive Knowledge Posttest (Strict marking) Productive Knowledge Posttest (Strict marking) Descriptive Statistics Std Mean Minimum Maximum Deviation 25th Percentiles 50th (Median) 75th 35 03 169 00 00 00 35 21.29 3.494 16 29 19.00 21.00 24.00 35 15.86 2.982 11 23 14.00 16.00 18.00 Friedman Test Ranks Mean Rank 1.00 3.00 2.00 Productive Knowledge Pre-test (Strict marking) Productive Knowledge Post-test (Strict marking) Productive Knowledge Post-test (Strict marking) 244 Test Statisticsa N Chi-Square df Asymp Sig 35 70.000 000 a Friedman Test Wilcoxon Signed Ranks Test Ranks N a Mean Rank Sum of Ranks 00 00 18.00 630.00 Negative Ranks Positive Ranks 35b Ties 0c Total 35 Negative Ranks 0d 00 00 Productive Knowledge Post-test (Strict marking) - Positive Ranks 35e 18.00 630.00 Productive Knowledge Pre-test (Strict marking) Ties 0f Total 35 Negative Ranks 35g 18.00 630.00 h Positive Ranks 00 00 Productive Knowledge Post-test (Strict marking) i Productive Knowledge Post-test (Strict marking) Ties Total 35 a Productive Knowledge Post-test (Strict marking) < Productive Knowledge Pre-test (Strict marking) b Productive Knowledge Post-test (Strict marking) > Productive Knowledge Pre-test (Strict marking) c Productive Knowledge Post-test (Strict marking) = Productive Knowledge Pre-test (Strict marking) d Productive Knowledge Post-test (Strict marking) < Productive Knowledge Pre-test (Strict marking) e Productive Knowledge Post-test (Strict marking) > Productive Knowledge Pre-test (Strict marking) f Productive Knowledge Post-test (Strict marking) = Productive Knowledge Pre-test (Strict marking) g Productive Knowledge Post-test (Strict marking) < Productive Knowledge Post-test (Strict marking) h Productive Knowledge Post-test (Strict marking) > Productive Knowledge Post-test (Strict marking) i Productive Knowledge Post-test (Strict marking) = Productive Knowledge Post-test (Strict marking) Productive Knowledge Post-test (Strict marking) Productive Knowledge Pre-test (Strict marking) Test Statisticsa Productive Knowledge Productive Knowledge Post-test (Strict marking) Post-test (Strict - Productive Knowledge marking) - Productive Pre-test (Strict marking) Knowledge Pre-test (Strict marking) Z -5.165b -5.167b Asymp Sig (2-tailed) 000 000 a Wilcoxon Signed Ranks Test b Based on negative ranks c Based on positive ranks Productive Knowledge Post-test (Strict marking) - Productive Knowledge Post-test (Strict marking) -5.374c 000 2.2 Less strict marking N Productive Knowledge Pretest (Less strict marking) Productive Knowledge Posttest (Less strict marking) Productive Knowledge Posttest (Less strict marking) Descriptive Statistics Std Mean Minimum Maximum Deviation 25th Percentiles 50th (Median) 75th 35 03 169 00 00 00 35 23.37 3.255 17 29 21.00 24.00 26.00 35 18.29 3.885 11 26 16.00 18.00 21.00 245 Friedman Test Ranks Productive Knowledge Pre-test (Less strict marking) Productive Knowledge Post-test (Less strict marking) Productive Knowledge Post-test (Less strict marking) Mean Rank 1.00 3.00 2.00 Test Statisticsa N Chi-Square df Asymp Sig a Friedman Test 35 70.000 000 Wilcoxon Signed Ranks Test Ranks N Mean Rank Sum of Ranks Negative Ranks 0a 00 00 Productive Knowledge Post-test (Less strict b Positive Ranks 35 18.00 630.00 marking) - Productive Knowledge Pre-test (Less c Ties strict marking) Total 35 Negative Ranks 0d 00 00 Productive Knowledge Post-test (Less strict Positive Ranks 35e 18.00 630.00 marking) - Productive Knowledge Pre-test (Less Ties 0f strict marking) Total 35 Negative Ranks 35g 18.00 630.00 Productive Knowledge Post-test (Less strict Positive Ranks 0h 00 00 marking) - Productive Knowledge Post-test (Less i Ties strict marking) Total 35 a Productive Knowledge Post-test (Less strict marking) < Productive Knowledge Pre-test (Less strict marking) b Productive Knowledge Post-test (Less strict marking) > Productive Knowledge Pre-test (Less strict marking) c Productive Knowledge Post-test (Less strict marking) = Productive Knowledge Pre-test (Less strict marking) d Productive Knowledge Post-test (Less strict marking) < Productive Knowledge Pre-test (Less strict marking) e Productive Knowledge Post-test (Less strict marking) > Productive Knowledge Pre-test (Less strict marking) f Productive Knowledge Post-test (Less strict marking) = Productive Knowledge Pre-test (Less strict marking) g Productive Knowledge Post-test (Less strict marking) < Productive Knowledge Post-test (Less strict marking) h Productive Knowledge Post-test (Less strict marking) > Productive Knowledge Post-test (Less strict marking) i Productive Knowledge Post-test (Less strict marking) = Productive Knowledge Post-test (Less strict marking) Test Statisticsa Productive Knowledge Post- Productive Knowledge Posttest (Less strict marking) test (Less strict marking) Productive Knowledge PreProductive Knowledge Pretest (Less strict marking) test (Less strict marking) Z -5.167b -5.164b Asymp Sig (2-tailed) 000 000 a Wilcoxon Signed Ranks Test b Based on negative ranks c Based on positive ranks 246 Productive Knowledge Posttest (Less strict marking) Productive Knowledge Posttest (Less strict marking) -5.201c 000 APPENDIX 15 SPSS OUTPUT OF BETWEEN-GROUP COMPARISON 247 Appendix 15A SPSS OUTPUT OF THE RECEPTIVE IDIOM KNOWLEDGE TEST RESULTS Receptive Knowledge Pre-test Receptive Knowledge Post-test Receptive Knowledge Post-test Group Statistics N Mean 34 5.15 35 4.86 34 24.38 35 25.20 34 18.00 35 23.91 Group CG EG CG EG CG EG Std Deviation 3.295 3.362 3.660 3.376 3.861 3.364 Std Error Mean 565 568 628 571 662 569 Independent Samples Test Levene's Test for Equality t-test for Equality of Means of Variances F Receptive Knowledge Pre-test Receptive Knowledge Post-test Receptive Knowledge Post-test Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed 036 059 1.045 Sig .849 809 310 t 95% Confidence Sig (2Mean Std Error Interval of the Difference tailed) Difference Difference Lower Upper df 362 67 719 290 802 -1.310 1.890 362 66.994 719 290 801 -1.310 1.890 67 338 -.818 847 -2.509 874 -.964 66.202 339 -.818 848 -2.511 876 67 000 -5.914 871 -7.653 -4.176 -6.776 65.200 000 -5.914 873 -7.657 -4.171 -.965 -6.790 248 APPENDIX 15B SPSS OUTPUT OF THE PRODUCTIVE IDIOM KNOWLEDGE TEST RESULTS Pre-test N Productive Knowledge Pre-test (Strict marking) Productive Knowledge Pretest (Less strict marking) Group Descriptive Statistics Mean Std Minimum Maximum Deviation 25th Percentiles 50th (Median) 75th 69 04 205 00 00 00 69 04 205 00 00 00 69 1.51 504 1.00 2.00 2.00 Mann-Whitney Test Ranks Group CG Productive Knowledge Pre-test (Strict marking) EG Total CG Productive Knowledge Pre-test (Less strict marking) EG Total N 34 35 69 34 35 69 Test Statisticsa Productive Knowledge Pre-test (Strict marking) Mann-Whitney U Wilcoxon W Z Asymp Sig (2-tailed) a Grouping Variable: Group Productive Knowledge Pre-test (Less strict marking) 577.000 577.000 1207.000 1207.000 -.612 -.612 541 541 249 Mean Rank Sum of Ranks 35.53 1208.00 34.49 1207.00 35.53 34.49 1208.00 1207.00 Immediate and Delayed Post-test Group Statistics Group N Mean Std Deviation Std Error Mean Productive Knowledge Post-test CG 34 21.91 3.980 683 (Strict marking) EG 35 21.29 3.494 591 Productive Knowledge Post-test CG 34 23.03 3.896 668 (Less strict marking) EG 35 23.37 3.255 550 Productive Knowledge Post-test CG 34 13.85 3.669 629 (Strict marking) EG 35 15.86 2.982 504 Productive Knowledge Post-test CG 34 14.53 4.308 739 (Less strict marking) EG 35 18.29 3.885 657 Independent Samples Test Levene's Test for t-test for Equality of Means Equality of Variances Productive Knowledge Post-test (Strict marking) Productive Knowledge Post-test (Less strict marking) Productive Knowledge Post-test (Strict marking) Productive Knowledge Post-test (Less strict marking) Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed F Sig t 223 638 695 413 1.483 243 523 df 95% Confidence Sig (2- Mean Std Error Interval of the tailed) Difference Difference Difference Lower Upper 67 490 626 901 -1.172 2.424 694 65.356 490 626 903 -1.176 2.429 67 693 -.342 863 -2.065 1.381 -.395 64.249 694 -.342 866 -2.071 1.387 67 015 -2.004 804 -3.609 -.400 -2.486 63.541 016 -2.004 806 -3.615 -.393 67 000 -3.756 987 -5.726 -3.800 65.848 000 -3.756 988 -.396 228 -2.493 624 -3.806 250 1.786 -5.730 1.783 APPENDIX 16 PICTORIAL ILLUSTRATION FOR ANGER AS HEATED FLUID IN A CONTAINER (The picture was edited by the researcher via Photoshop to illustrate the concept of anger described as heated fluid in a container The original picture can be found at http://www.commongunsense.com/2013/10/domestic-arguments-and-gun-deaths.html) 251 ... demonstrated that the nature of idioms is not arbitrary and rote memorization is not the only way to learn them The discovery that several figurative idioms are semantically motivated by a common conceptual. .. application of conceptual metaphors facilitate TDMU English -majored students? ?? reception of the target idioms immediately after the teaching stage? (1b) To what extent does the application of conceptual. .. production of the target idioms immediately after the teaching stage? (2b) To what extent does the application of conceptual metaphors facilitate TDMU English -majored students? ?? production of the target