Learning Through Music - Free Paper Example

Learning English through Songs

Title:

Using songs to learn English as a foreign language by University students, a study on students in King Faisal University

Description:

This research seeks to understand the effectiveness of using songs to learn English as a foreign language among university students. A literature review shows that many teachers are using songs to teach new languages, and the method has been effective. Therefore, this study will put this notion to test to gather primary data crucial in making correct conclusions and recommendations.

Tools & Methodology:

The research will involve a study on a group of 20 students, 10 males and 10 females, currently learning English as a foreign language. The participants will have different countries of origin and different first languages. Therefore, the research tools that the researcher will use to gather data will include observation, questionnaires, and in-depth interviews.

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2.3 Previous Research

Studies have shown that learning and thinking visually instead of verbal which is the traditional culture of learning, has improved the rate of understanding and mastering a language. Thus a change in teaching strategy should be required in the Malaysian curriculum. Educators need to concentrate more on teaching visually hence students will learn visually which will create a long term memory. In terms of mathematics, students don’t just watch the teacher, they practically do the mathematics which improves their mathematical prowess (West, 1997). The strategy concentrates on learning through interactive visual music. An ideas is first settled in the mind and then words are absorbed later (West, 1997). This shows that if a teacher just teaches a language through visual music, a student first gets the idea of what English language is all about and then gets the specific words that may be explained. If a teacher just teaches without imagery or audio music a student might also not grasp the words or message the teacher is conveying,

Previous research have shown that teaching using music in English lessons improves learning but with different level of success. Ana (2016) shows how music affects students who may have varying level of prior knowledge of the English language as they acquire descriptive and procedural knowledge. When prior knowledge of English is low, use of music whether audio or visual, is better for understanding facts that are descriptive than lessons undertaken by the use of written texts only. However, understanding facts that are procedural does not indicate any difference between the use of music and written texts. Students whose prior knowledge level is high, show a significant improvement in both procedural and descriptive knowledge when music is used compared to written texts only (Ana, 2016). Shen’s et al. (2009) research showed that learners with varying levels of prior knowledge perform differently to different teaching presentations for attaining learning tasks. They argued that there is a meaningful interconnection between the influence of visual design and prior knowledge of students in regard to learning in a situation where visual music is used. If the motions in the visual music are inconsistent, it might distract the learning process of a student and in such a case audio music will be better. Another research indicated that, Giving out visual control of music improves learning, specifically in males (Claudia, 2002).

Kleinman et al. (1999) assessed the effects of certain visual properties in improving learning. They found out that visual music which is graphically colored created more effect on the learning process of a student than black and white visuals. Although, Myatt et al. (1999) found out that quite a number of participants prefer colored visuals, but there is no compelling comparison between the quantity or quality of learning and understanding not unless color is correlated to the content to be taught. The research goes ahead to indicate that young students prefer visuals which are simple while older students prefer visuals which are complex. Regardless of the age group, simple visuals are always more effective than complex visuals (Myatt et al., 1999). The types of visuals students prefer to view do not necessarily facilitate their learning process.

Mayer et al. (1996) differentiated the application of summarized interactive media consisting of a series of defined demonstrations describing the sequence in a procedure, with a summarized text comprising of 600 words. The knowledge retained and transferred in different quantity of texts and multimedia summary was also analyzed. The conclusion indicates that verbal is less productive than multimedia. The results show that shortened summaries are more effective specifically when words and demonstrations through visuals are used together. The participants in this research had inferior standard of prior knowledge of the lesson. The researchers believed that the results would be different if experienced learners had participated. This research shows that, music is more effective in inexperienced students in a specific subject. It also shows that, incorporating both visual and verbal illustration method simplifies mental intermediaries in learning.

Alex (2016) acknowledged the cognitive styles applied by learners and their experience in language. The research compared the use of texts and visuals only and use of text only teaching materials. Inexperienced learners with lingual cognitive styles performed best when text and visuals were used simultaneously. The inexperienced learners with imagery cognitive styles performed best with the use of texts only. The outcomes were different with the expected findings. However, generally learners portrayed better performance in test scores when using text and visual simultaneously. Moreover, inexperienced learners from both learning approaches classifications portrayed greater performance in test results than skilled learners. The comparison in results between inexperienced learners and experienced learners correlate with findings form a research carried out by Chanlin (1998).

Difference in the types of visuals used in teaching were studied by Simone (2016) found out that there is no significance difference in accomplishments by learners exposed by various visual mapping methods. Although the duration in which learners were exposed to the respective visual embellished instructional treatments influenced learning results. Learners who were given the opportunity to learn according to their own speed performed better than those who were stipulated the specific time to learn.

Previous research finds out that use of optic components in educating and understanding produce positive outcomes. For learners to benefit from visual enhancements, teachers should have skills that involve imagery language and techniques of visual teaching. Therefore, teachers should be guided on the appropriate ways to use visuals music and audio which will be effective in learning. Outcomes of the effect of optic articulacy in English lessons can be studied further through educators assessing and evaluating their modern use of music and comparing the music content of lessons and academic achievements of the students. More study to establish mechanisms that quantify a person’s level of music articulacy, constituting the ability to create and interpret optic communication and expression which is fundamental in assessing the general effect on student’s education. Moreover, the labeling of probable interconnections among other variables such as demographic traits and educational approach is required for an extensive research of the idea of music optic and audio articulacy.

2.4 Theoretical Framework

The table below shows the theoretical framework of this research. The sequence will be indicated from top to bottom.

Dual Coding Theory

Independent Variables: Music

Dependent Variables: English Language

Krashen’s Monitor Model

Figure 2.4.1: Theoretical Framework

This research has adopted Dual Coding theory. Dual Coding theory indicates that oral and visual information are each prepared adversely undergoing exclusive methods with the brain establishing contrasting models for information prepared in each channel. This theory is a linking framework for both speaking and reading. When learners comprehend the written information, dual coding theory claims that the learners access phonological and orthographic information to identify words in the texts.

In terms of variables, there are two variables which are independent and dependent variables. In this research visual and audio music is the independent variable while using music in teaching and learning English is the dependent variable. Music can portray the culture of a certain language in the recent history (Clara, 2016). Music does not only improve teaching, but it also enhances learning. Aristotle one of the Greek philosophers stated that, thinking is impossible without image (Benson, 1997). This is in the case of visual music. Images with meaning resulted into characters in alphabets (West, 1997).

This research adopts the monitor model of Krashen. The monitor model of Krashen has depicted five hypotheses (Krashen, 1983). The first hypothesis is the Learning or Acquisition hypothesis which claims that there are two absolute processes of development of the second language: the learned order and acquired order. The second one, is the Natural order hypothesis which states that the acquirement of grammatical anatomy follows a natural order which can be predicted. The third one is the Monitor hypothesis which suggests that the correlation between learning and acquisition and explains the influence of learning on acquisition. The fourth is the Input hypothesis which explains how the student obtains a second language. It just defines the process of second language acquisition by a learner. The fifth is the Affective hypothesis which represents Krashen’s opinion that a few affective variables which play a useful but deliberate character in acquisition of second language. These variables comprise of: anxiety, self confidence and motivation.

2.5 Summary

Teaching is not as easy as conveying and imparting knowledge to learners. In the teaching career, teachers encounter many students with contrasting learning styles, academic requirements and characteristics on daily basis. Therefore, in consideration of teachers’ personalization, individualization and localization of their teaching, so that it can harmonize with every student, various abilities and expertise in teaching and a lot of classroom experiences are required.

Students participation and engagement is the main aspect in attaining the teaching itself (Clara, 2016). Due to this, tools and strategies adopted to help in teaching play a key role in creating an interest of students in learning. They will engage actively in teaching and learning process if they are attracted to the English lesson.

Using music in English lessons is one strategy to attract student’s attentiveness. In accordance to dual coding theory, when information is double coded, the chances of being retrieved, memorized and applied are high. Dual coding theory also hypothesizes that that images and words activate the mental processing in various ways. Moreover, some of the research such as the ones undertaken by Kleinman (1999) and Mayer (1996) authenticated the positive impact created by Dual Coding Theory. With all the assertions, it is now certain that the of music whether visual or audio enhance English teaching and learning which the Malaysian curriculum should adopt for better communication and understanding of the language.

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Chapter 4 - Prototype

4.1 Introduction

In this chapter, the researcher will discuss the making of the music. The music was copied in a digital versatile disc (DVD). During the study, the researcher has to distribute six DVDs as the students will seat in groups throughout the teaching and learning process. The teaching aid constituted four parts. The first category is the setting, the second category is the characters, the third category is the plot summary, and the fourth part is comprised of all the exercises which can combine what the students had learned before.

4.1.1 Setting

The type of music played will be a narrative music. There are four settings in the narrative music. The researcher distributes two B3 manila cards. The students have to write the settings (narrative music) down because they will also watch the concept of the story by being demonstrated in the visual music. There are three descriptions in each setting. After they had completed, the teacher will confirm whether the students have given the correct match.

4.1.2 Characters

The characters are just the same as the settings. There narrative music is comprised of six characters. Each character will have four descriptions. The method of using visual music is the same as articulated in the setting part.

4.1.3 Plot Summary

For the summary part, the same narrative music is watched by all the students. The students just have to watch and write down what the narrative in the sequence portrayed in the narrative music.

4.1.4. Reinforcement Exercises

In the last part, there are three exercises given. The first one is to narrate the story as stipulated in the music. The second one is True and False statement. The last one is the objective questions.

Chapter 5 - Data analysis

5.1 Introduction

This chapter focuses on data collected by the researcher. The data acquired is then analyzed to decide whether the hypothesis made is declined or acknowledged and the range to which the research had reached its objectives well.

5.2 Demographic Analysis

This study is carried out in a secondary school in Selangor region- S.M.K Jugra. Participants of this research study were form four students. The participants are then separated into two clusters: the control cluster and the experimental cluster. The control and experimental clusters comprise of 30 students each.

Gender	4S (Control Group)	Percentage	4T (Experimental Group)	Percentage	Number of Participants
Male	18	60	13	43	31
Female	12	40	17	57	29
Total	30	100	30	100	60

Table 5.1 Background of the Participants

As shown in the table above, there were two classes which participated in this research: 4S and 4T. 4S is the control cluster while 4T is the experimental cluster. In the control cluster, there are 17 male students (57%) and 13 female students (43%). In the experimental cluster, there were 14 male participants (47%) and 16 female participants (53%). In total there were 31 male participants and 29 female participants in this study. The bar graph below will indicate the number of participants based on the group and gender.

The y-axis represents the number of participants.

Group

This research took two weeks. There are five lessons each week. Each lesson took 35 minutes. Attendance of every lesson is perceived as a means of examining and determining the effect of conciseness towards the result of the study. The results attained by the control and experimental clusters in the prior-test and after-test were compiled and converted into grade A, B, C, D, and E. After that, the results would be differentiated to confirm whether there are any comparisons in the results between the control and experimental cluster.

5.3 Presentation of Results

In this research, scores were graded into: A, B, C, D, and E. Grade A, B, C, and D are regarded as pass while grade E is regarded as failed. The rating scale below will indicate the marks and grades for the pre-test and post-test.

Marks Grade

76-100 A

61-75 B

51-60 C

46-50 D

0-45 E

Figure 5.2: Marking scale for both the Prior-test and After-test

5.3.1 Prior-test and After-test scores for control cluster

No. Respondents Prior-Test After-Test

MarksGradeMarksGrade

1. Control 1 49 D 61 B

2. Control 2 38 E 51 C

3. Control 3 58 C 72 B

4. Control 4 51 C 64 B

5. Control 5 56 C 69 B

6. Control 6 28 E 51 C

7. Control 7 40 E 60 C

8. Control 8 34 E 53 C

9. Control 9 50 D 75 B

10. Control 10 50 D 70 B

11. Control 11 48 D 62 B

12. Control 12 59 C 75 B

13. Control 13 56 C 72 B

14. Control 14 45 E 52 C

15. Control 15 57 B 64 B

16. Control 16 67 B 75 B

17. Control 17 32 E 52 C

18. Control 18 48 D 61 B

19. Control 19 59 C 72 B

20. Control 20 59 C 75 B

21. Control 21 45 E 61 B

22. Control 22 63 B 75 B

23. Control 23 61 B 74 B

24. Control 24 51 C 66 B

25. Control 25 45 E 61 B

26. Control 26 39 E 61 B

27. Control 27 45 E 60 C

28. Control 28 48 D 64 B

29. Control 29 55 C 70 B

30. Control 30 75 B 88 A

Figure 5.3: Scores in prior-test and after-test for control group.

In accordance to the above table, 30 students participated in the prior-test and after-test. The lowest score is 28% in the prior-test for the control group. The lowest score is 51% in the after-test of the control cluster. The highest mark is 75% in the in the prior-test of the control cluster while the highest score in the after-test of the control cluster is 88%.

5.3.2 Prior-test and After-test results for the Experimental Cluster

The table below will indicate the marks and grade attained by each student in the experimental group. They are marks and grades obtained from the pre-test and post-tests study. Lowest marks and the highest marks will be analyzed. It will show evidence of the hypothesis highlighted in this paper.

No. Respondents Pre-Test Post-test

MarksGradeMarksGrade

1. Experimental 1 72 B 89 A

2. Experimental 2 50 D 77 A

3. Experimental 3 61 B 79 A

4. Experimental 4 75 B 91 A

5. Experimental 5 59 C 74 B

6. Experimental 6 41 E 60 C

7. Experimental 7 52 C 70 B

8. Experimental 8 49 D 69 B

9. Experimental 9 50 D 62 B

10. Experimental 10 60 C 81 A

11. Experimental 11 41 E 62 B

12. Experimental 12 59 C 72 B

13. Experimental 13 48 D 66 B

14. Experimental 14 51 C 64 B

15. Experimental 15 60 C 78 A

16. Experimental 16 59 C 75 B

17. Experimental 17 53 C 78 A

18. Experimental 18 60 C 75 B

19. Experimental 19 46 D 69 B

20. Experimental 20 59 C 74 B

21. Experimental 21 46 D 61 B

22. Experimental 22 49 D 64 B

23. Experimental 23 60 C 74 B

24. Experimental 24 49 D 61 B

25. Experimental 25 46 D 65 B

26. Experimental 26 60 C 81 A

27. Experimental 27 59 C 73 B

28. Experimental 28 50 D 75 B

29. Experimental 29 54 C 69 B

30. Experimental 30 49 D 60 C

Figure 5.4: Prior-test and after-test scores for the experimental Cluster.

In accordance to the table above, 30 students participated in both the prior-test and after-test. The lowest mark is 41% in the in the prior-test of the experimental cluster. Lowest mark is 58% in the post-test of experimental group. The highest mark is 75% in the prior-test of the experimental cluster. The highest mark is 91% in the after-test of the experimental cluster.

5.3.3 Analysis of the result between the control and experimental Cluster

Control Cluster					Experimental Cluster
Grade	Prior-test		After-test		Grade	Prior-test		After-test
	Number of Participants	%	Number of Participants	%		Number of Participants	%	Number of Participants	%
A	0	0	1	3	A	0	0	8	27
B	5	17	23	77	B	3	10	20	67
C	9	30	6	20	C	14	47	2	6
D	6	20	0	0	D	11	37	0	0
E	10	33	0	0	E	2	6	0	0
Total	30	100	30	100	Total	30	100	30	100

Figure 5.5: Prior-test and After-test scores for Control and Experimental clusters

Table 5.5 indicates the performance of the students in the prior-test and after-test of the control and experimental cluster ranked established on grades. It shows the composition or number of students in each grade. The analysis certainly indicated that there was performance improvement among the participants based on the grades from prior-test to after-test for control and experimental clusters.

For the control group, none of the students attained grade A in the pre-test. Though 1 student (3%) scored grade A in their post test. 5 students (17%) scored grade B in their pretest and the number increased to 23 students (77%) in the post-test. 9 students (30%) attained grade C in their prior-test and reduced to 6 (20%) in the after-test. 6 students (20%) scored D in their prior-test and no one got a D in their after-test. 10 participants (33%) got E in their prior-test and no one got an E in their after-test.

For the control group the highest improvement in the grade attained is grade B, which rose from 17% to 77%. Students who scored grade A had escalated from 0% to 3%. Students who scored grade C decreased by 10% from the prior-test to the after test. Students who scored grade D decreased by 20%. Students who scored grade E decreased by 33%.

For the experimental group, none of the students scored grade A in their pre-test. Though, 8 students (27%) attained grade A in their post-test. 3 students (10%) obtained grade B in their pre-test and this number rose to 20 students (67%) in the post-test. 14 students (47%) scored grade C in their pre-test and this number diminished to 2 students (6%) in the post-test. There are 11 students (37%) who scored grade D in their prior-test and no one got D in their after-test. 2 students (6%) obtained grade E in their prior-test and no one attained E in their after-test.

In the pre-test, the experimental cluster is slightly weaker than the control cluster. However, the experimental cluster was able to achieve greater improvement in the post-test. 8 students scored grade A in the experimental cluster and only 1 participant from the control cluster. The greatest improvement based on grades is from grade D to A and the experimental group had achieved it.

Grade B is the greatest improvement in the grade attained for the experimental group which escalated from 10% to 67%. Students who scored grade A had risen from 0% to 27%. Participants who had obtained grade C decreased by 41% and the participants who obtained grade D decreased by 37%. Also the students who scored grade E decreased by 6%.

The performance for the experimental group is indicated in the chart below. The chart will also portray the difference between the control and experimental cluster in the prior-test.

Figure 5.6: Comparison between the experimental and control cluster in the prior-test

The y-axis shows the number of students. In accordance to figure 5.6, there wasn’t any major distinction between the results for the control cluster and experimental cluster in the prior-test. It indicates that the students had more or less understanding of the English language. Most of the students attained grades C, D, and E in their pre-test prior any teaching and learning was carried out.

The chart below will show the performance difference between the control cluster and the experimental cluster in the after test.

Figure 5.7: Distinction between the control and experimental cluster in the after test.

The y-axis represents the number of students. Figure 5.7 above shows that the experimental cluster participants achieved better than the control cluster participants. 8 students from the experimental group scored grade A, while only 1 participant from the control cluster achieved grade A in their post-test. Even though most students who scored grade B in the after-test were from the control cluster, the mean grade for the control group is between B and C. But for the experimental group, the mean grade is between A and B. Definitely the experimental group had greater performance than the control group.

5.3.4 Analysis of students’ interest and learning satisfaction by using music in English Lessons.

A questionnaire with ten questions about the participants’ interest and learning satisfaction had been administered to the students for the experimental group after the post-test. The data had been compiled, assessed and evaluated to acquire the mean score. The mean score interpretation is as indicated in the table below:

Average Score	Perception
0-1.26	Very Bad
1.27-2.51	Bad
2.52-3.26	Affirmative
3.27-4.20	Very Affirmative

Table 3.4: Interpretation of the mean score

	Statements	1 Strongly Contend	2 Contend	3 Doubtful	4 Accept	5 Strongly Accept	Mean
1.	Music is a suitable tool for English learning	3 (10%)	2 (6.7%)	8 (26.7%)	14 (46.7%)	3 (10.0%)	3.40
2.	Music can facilitate the process of English learning	1 (3.3%)	3 (10.0%)	6 (20.0%)	10 (33.3%)	10 (33.3%)	3.83
3.	The music brings a lot of information and material alive	4 (13.3%)	9 (30.0%)	8 (26.7%)	5 (16.7%)	4 (13.3%)	2.87
4.	I can learn better through Music	1 (3.3%)	4 (13.3%)	11 (36.7%)	9 (30.0%)	5 (16.7%)	3.43
5.	Music makes the lesson more fun for me	2 (6.7%)	0	10 (33.3%)	11 (36.7%)	6 (20.0%)	3.53
6.	Music makes the lesson more interesting	3 (10.0%)	7 (23.3%)	13 (43.3%)	2 (6.7%)	5 (16.7%)	2.97
7.	I feel comfortable when the teacher uses music in teaching	2 (6.7%)	5 (16.7%)	9 (30.0%)	10 (33.3%)	4 (13.3%)	3.30
8.	I can remember English semantics better if I learn through music	2 (6.7%)	5 (16.7%)	10 (33.3%)	5 (16.7%)	8 (26.7%)	3.40
9.	I can learn faster through music	2 (6.7%)	6 (20%)	16 (53.3%)	4 (13.3%)	2 (6.7%)	2.93
10.	I prefer learning English through the use of music in lessons	2 (6.7%)	0	2 (6.7%)	13 (43.3%)	13 (43.3%)	4.17

Figure 5.1 Respondents’ interest and learning satisfaction for experimental group

Figure 5.1 shows the students’ interest and learning satisfaction by use of music in learning English for the experimental cluster. The average score of the first statement is very positive which is 3.40. The researcher concluded that the students agreed that music is a favorable tool in English learning. The second statement showed a very positive mean score too which is 3.83. Hence the students accepted that music can facilitate English learning process.

The average score of both the third and fourth statement is 2.87 (positive) and 3.43 (very positive) respectively. It certainly indicated that the students concurred that music brings a lot of information and material alive and learn English better through music. The average score for both the fifth and sixth statement is 3.53 (very positive) and 2.97 (positive) respectively. This indicated that music makes the lesson more fun and interesting to the learners.

The seventh statement indicated a very positive average score which is 3.30 hence the researcher concluded that the students feel comfortable when the teacher uses music. The average score for both the eighth and ninth statement is 3.40 (very positive) and 2.93 (positive) respectively. Thus the researcher concluded that the students can learn faster through music and they can memorize the language through music.

The tenth statement indicates a very positive mean score which is 4.17 hence the researcher concluded that the students prefer learning English language through music. Music clearly draws student’s attention and helps them in learning.