Erden Topoğlu, E. (2022). Academic motivations of preservice music teachers. International Online Journal of Education and Teaching (IOJET), 9(2). 903-918. Received : 12.01.2022 Revised version received : 23.03.2022 Accepted : 25.03.2022 ACADEMIC MOTIVATIONS OF PRESERVICE MUSIC TEACHERS Research Article Evin Erden Topoğlu (https://orcid.org/0000-0002-6731-5790) Aydın Adnan Menderes University, Turkey evinerden@hotmail.com Biodata: Evin Erden Topoğlu is an assistant professor at Music Education Department in Adnan Menderes University, Turkey. Her research interests are on music education, music psychology and early child music education. Copyright © 2014 by International Online Journal of Education and Teaching (IOJET). ISSN: 2148-225X. Material published and so copyrighted may not be published elsewhere without written permission of IOJET. mailto:evinerden@hotmail.com http://orcid.org/xxxx Erden Topoğlu 904 ACADEMIC MOTIVATIONS OF PRESERVICE MUSIC TEACHERS Evin Erden Topoğlu evinerden@hotmail.com Abstract The purpose of the present study is to determine the difference between preservice music teachers’ levels of academic motivations and their genders, their high schools, lessons that they were failed, lessons that they were failed for the reason of absenteeism, and their career choice. Also, the relationship between the preservice music teachers’ academic motivations and their instrument scores was investigated in the study. A total of 349 students who receive education from Faculty of Education Music Teaching Departments in Aydın, Denizli, İzmir, and Muğla attended the study. The data was gathered in the 2017-2018 academic year. The Academic Motivation Scale which was developed by Vallerand et al. (1992) and translated into Turkish by Karagüven (2012) was used in order to determine the levels of academic motivations of the participants. Six significant results were found in the study. There are significant differences between participants’ academic motivations and their genders, their states of absenteeism, their high schools, the number of lessons they have failed, and their career choice. Also, positive significant but weak relationships were found between the participants’ academic motivations and their instrument scores. The results were discussed in the light of the literature. Keywords: Academic motivation, music education, preservice music teachers, motivation. 1. Introduction One of the fundamental concerns of social science is how human behaviors are shaped, how individuals make decisions, and in which direction they take these decisions. Motivation is one of the key concepts that aims to determine what moves individuals in different circumstances and what are the underlying reasons for them to take action. Since motivation is a substantial notion for students as well as all individuals, it is one of the leading concepts that educational psychologists and researchers have been focusing on for a while. Although motivation and its interactions with miscellaneous variables were enquired and discussed in a vast number of studies, some educators and researchers accent and discussed the relationship between academic achievement and motivation concerning the assessment of learning processes. Significant relationships between academic achievement and motivation indicate that motivation is a crucial factor in terms of academic achievement. From a narrow point of view, the scores that are got from educational institutions or different educational achievement tests are interpreted as academic achievement, but academic achievement is a broader term that involves competencies such as linguistic, mathematical, social science, science, thinking skills of students so that these competencies enable them to succeed in school and society (Lindholm Leary & Borsato, 2006). In a similar vein, Deci & Ryan (2000) have suggested that students’ other progress like psychological growth and wellness are way more important than academic achievement and its outcomes. There is a wide range of motivation definitions from distinct standpoints in the literature. In a broader sense motivation can be described as to be moved to do something (Ryan & Deci, 2000). Pintrich & Schunk (2002) described motivation as a process of an individual which regulates his/her behaviors toward a specific goal. In this regard, academic motivation can be mailto:evinerden@hotmail.com International Online Journal of Education and Teaching (IOJET) 2022, 9(2), 903-918. 905 characterized as the intrinsic processes which promote and orient the behaviors in order to reach specific academic goals (Pintrich & Zusho, 2002). The concept of motivation was discussed and tried to be defined by a number of theories and approaches that aims to identify human behavior (drive theory, conditioning theory, cognitive consistency theory, humanistic theory, attribution theory, expectancy-value theory, self-determination theory, self-efficacy theory, self-regulation theory, achievement goal theory, future time perspective, etc.). Therefore, there are scales that are developed in order to assess academic motivation, based on differing theoretical fundamentals (Amrai et al., 2011; Fortier, Vallerand, & Guay, 1995; Komarraju, Karau, & Schmeck, 2009; Turner, Chandler, & Heffer, 2009). In this study, motivation was discussed in the light of self-determination theory (SDT) which was first exposed by Deci & Ryan with their book titled “Self-Determination and Intrinsic Motivation in Human Behavior" (1985). SDT differs from the other motivation theories by claiming that motivation is not single structured. In self-determination theory’s taxonomy of motivation, motivation is grouped as intrinsic motivation, extrinsic motivation, and amotivation. In this taxonomy, there is a linear internalization from extrinsic motivation to intrinsic motivation (Ryan & Deci, 2020). The intrinsic motivation which can be described as taking action without any external demand is related to the behaviors of an individual for its own sake and the interest and satisfaction towards learning itself. Individuals are supposed to follow the rules due to their socialization from the beginning of the time they were born thus, they take action to the issues that they are not sincerely interested in. According to SDT, these controlled behaviors form the basis of extrinsic motivation and can be internalized in time (Deci et al. 1991, Deci & Ryan, 2000) Conversely, amotivation is the state of an individual’s lack of motivation towards his/her behaviors. Unlike in the drive theories, according to SDT, needs are not learned, they are innate. Also, SDT gives priority to psychological needs such as interpersonal relations and managing the physical and social environment. SDT asserts that individuals have three basic needs which are autonomy, competence, and relatedness. Preventing one of these basic needs of the individual damages his/her motivation and wellness. Autonomy is to prefer one’s choices independently from external effects. If an individual has the initiative on his/her own behaviors, the individual takes the responsibility to reach goals and regulate his/her life. Competence relates to the use and enhancement of one's abilities whereas relatedness relates to one’s need for close social relations (Deci & Ryan, 1985; Ryan & Deci, 2000). Intrinsic motivation is weakened or strengthened depending on these needs are met (Deci & Ryan, 2000). According to Ryan & Deci (2020) autonomy is supported by value and interest experiences, competence is supported by structured environments which provide optimal difficulties, positive feedback, and development opportunities whereas, relatedness is supported by transferring respect and care. According to SDT, motivation is regulated by a number of factors. External regulation is the state of extrinsic motivation in which the behavior of individuals is externally controlled. Individuals undertake tasks in anticipation of reward or avoidance of punishment. In the introjection dimension, individuals focus on approval from the outside or by themselves. Identification is the individual’s state of recognizing and accepting the underlying value of behavior however, the behavior is still extrinsic because it is not originated from the individuals’ own desire and satisfaction. Integration is the complete form of internalization. The motivational perspective of SDT has led to a wide range of studies in social sciences not only in the psychology field but also in educational sciences. Many studies have discussed the relationship and the difference between motivation and various variables to determine the interaction of these variables with motivation. In several studies, it is determined that there is a significant difference between variables such as gender, grade, major, university, and Erden Topoğlu 906 academic motivation, which is one of the substantial predictors of academic achievement (Atay, 2018; Erdem, 2019; Gömleksiz & Serhatlıoğlu, 2013; Yılmaz, Taşkesen & Taşkesen, 2016). On the contrary, some studies indicate no significance between academic motivation and gender, grade, level of income, and homeland variables (Şeker, 2016; Deniz, 2020). In this regard, it is important to make new studies via different scales with different samples and to discuss the findings in the literature. Also, it is essential to assess preservice music teachers’ academic motivations and to reveal which sub-dimensions and variables it differs, in order to enhance the quality of the learning processes in the schools. The purpose of the present study is to determine the difference between preservice music teachers’ levels of academic motivations and their genders, their high schools, lessons that they were failed, lessons that they were failed for the reason of absenteeism, and their career choice. Also, the relationship between the preservice music teachers’ academic motivations and their instrument scores was investigated in the study. 2. Methods This is a descriptive study that aims to investigate the preservice music teachers’ academic motivations towards several variables. The study group, data collecting tools, and data analysis techniques of the research were explained below. 2.1. Study Group The study group consists of preservice music teachers who gather education from the universities in the Aegean Region of Turkey. These universities are Adnan Menderes University (26.3%), Dokuz Eylül University (20.3%), Pamukkale University (34.6%), and Muğla Sıtkı Koçman University (18.9%). A total of 349 students who receive education from Faculty of Education Music Teaching Departments attended the study. 200 of these students were female (57.3%) and 149 of them were male (42.7%). Participants’ ages range from 17 to 29 (M=20.8, SD=1.65). The data was gathered in the 2017-2018 academic year. 2.2. Data Collecting Tools 2.2.1. Personal Information Form The Personal Information Form which was developed by the researcher was used in order to reveal the participants’ genders, high schools they were graduated from, lessons that they were failed, lessons that they were failed for the reason of absenteeism, and their career choice. 2.2.1. Academic Motivation Scale The scale was developed by Vallerand et el. (1992) and translated into Turkish by Karagüven (2012). The Cronbach alpha coefficients for sub-scales range between .67 and .87. Cronbach alpha coefficient for the whole scale is .87. The scale which has seven subscales consists of 28 items. Three of these seven subscales are aimed to assess three types of intrinsic motivation, the other three are aimed to assess three types of extrinsic motivation, and the last subscale is aimed to assess motivation. The seven subdimensions are Intrinsic Motivation to Know (IMTK), Intrinsic Motivation to Accomplish (IMTA), Intrinsic Motivation to Experience Stimulation (IMES); Extrinsic Motivation External Regulation (EMER), Extrinsic Motivation Introjected Regulation (EMIN), Extrinsic Motivation Identified Regulation (EMID) and Amotivation (AMOT). The scores of the subscales range from 4 and 28. The subscales are evaluated separately and higher scores indicate high levels of motivation concerning the related subscale. International Online Journal of Education and Teaching (IOJET) 2022, 9(2), 903-918. 907 2.2. Data Analysis For the purposes of the study, several tests were applied in order to decide whether parametric or non-parametric tests will be used. Since the gender, absenteeism, and high school variables have two groups, skewness and kurtosis values were investigated to specify if the groups were distributed normally. For the gender variable, the skewness and kurtosis values were between +1.226 and -.990, the skewness and kurtosis values were between +1.127 and - 1.055 for the absenteeism variable, and values for the high school variable were between +1.146 and -1.145. According to Tabachnick & Fidell (2007), if the values are between +3 and -3 for the skewness and kurtosis variables, the groups are normally distributed. In this regard, t-test for independent samples were applied since the groups were normally distributed for the gender, absenteeism, and high school variables. Homogeneity of variances tests were applied in order to determine whether parametric or non-parametric tests to apply for the failed lessons and career choice variables. For the failed lessons variable, it was clarified all the subscales were homogeneous except AMOT subscale (p<.05), and for the career choice variable, IMTA, IMES, EMIN, and EMID subscales were homogeneous contrary to this, IMTK, EMER, and AMOT subscales were not homogeneous (p<.05). In this sense, for the subscales that were homogeneous one-way analysis of variance tests (ANOVA) were applied while for the subscales that were not homogeneous Kruskal-Wallis tests were applied. Since the number of failed lessons variable has three groups and the career choice variable has four groups, Bonferonni correction was performed by using the significance/number of groups formula (Miller, 1981). In this sense, a significance level of .0166 was accepted for the number of failed lessons variable and .0125 was accepted for the career choice variable. Also, the relationship between the preservice music teachers’ academic motivations and their instrument scores was investigated by Pearson Moments Correlation. 3. Results In order to determine the difference between participants’ academic motivations and their genders, a t-test for independent samples was performed. The results are presented in Table 1. Table 1. t-test results on participants’ academic motivations and their genders Academic Motivation Gender N Sd t df p IMTK Female 200 21.93 5.10 2.05 290.99 .041 Male 149 20.69 5.91 IMTA Female 200 17.16 5.72 -.00 347 .999 Male 149 17.16 6.42 IMES Female 200 17.94 5.55 1.923 294.03 .056 Male 149 16.69 6.34 EMER Female 200 23.24 4.49 3.53 347 .000 Male 149 21.30 5.23 EMIN Female 200 16.90 5.33 1.27 347 .204 Male 149 16.12 6.00 EMID Female 200 22.15 4.56 2.87 347 .004 Male 149 20.65 5.12 AMOT Female 200 9.31 5.94 -3.35 290.87 .001 Male 149 11.67 6.90 As seen in Table 1, female participants ( =21.93, sd=5.10) have significantly higher scores than male participants ( =20.69, sd=5.91) on IMTK subscale (t290.99= 2.05, p=.041). Female participants ( =23.24, sd=4.49) have significantly higher scores than male participants ( X X X X X Erden Topoğlu 908 =21.30, sd=5.23) on EMER subscale (t347= 3.53, p=.000). Also, female participants ( =22.15, sd=4.56) have significantly higher scores than male participants ( =20.65, sd=5.12) on EMID subscale (t347= 2.87, p=.004). On the other hand, male participants ( =11.67, sd=6.90) have significantly higher scores than female participants ( =9.31, sd=5.94) on AMOT subscale (t290.87= -3.35, p=.001). The difference between male ( =17.16, sd=6.42) and female participants’ ( =17.16, sd=5.72) IMTA subscale scores are not significant (t347= -.00, p=.999). There is no significant difference between male participants’ ( =16.69, sd=6.34) and female participants’ ( =17.94, sd=5.55) IMES subscale scores (t294.03= 1.923, p=.056). Also, no difference was found between the male ( =16.12, sd=6.00) and the female participants’ ( =16.90, sd=5.33) EMIN subscale scores (t347= 1.27, p=.204). In order to determine the difference between the participants’ academic motivations and whether they were failed a lesson for the reason of absenteeism, a t-test for independent samples test was performed and the result are presented in Table 2. Table 2. t-test results on participants’ academic motivations and whether they were failed a lesson for the reason of absenteeism Academic Motivation absenteeism N Sd t df p IMTK No* 242 22.07 5.10 4.23 319 .000 Yes** 79 19.20 5.48 IMTA No 242 17.62 5.88 3.24 319 .001 Yes 79 15.17 5.74 IMES No 242 18.13 5.71 3.93 319 .000 Yes 79 15.19 5.92 EMER No 242 23.08 4.58 4.59 319 .000 Yes 79 20.30 4.93 EMIN No 242 16.71 5.54 1.68 319 .094 Yes 79 15.50 5.45 EMID No 242 21.82 5.01 2.16 319 .032 Yes 79 20.47 4.28 AMOT No 242 9.35 5.95 -3.91 115.12 .000 Yes 79 12.84 7.18 p<.05 *No= Participants who have no lessons that they were failed for the reason of absenteeism. **Yes= Participants who have one or more lessons that they were failed for the reason of absenteeism. According to the results in Table 2, there are significant differences between the participants’ states of absences and their IMTK subscale scores (no =22.07, sd=5.10, yes =19.20, sd=5.48, t319= 4.23, p=.000), IMTA subscale scores (no =17.62, sd=5.88, yes =15.17, sd=5.74, t319= 3.24, p=.001), IMES subscale scores (no =18.13, sd=5.71, yes =15.19, sd=5.92, t319= 3.93, p=.000), EMER subscale scores (no =23.08, sd=4.58, yes =20.30, sd=4.93, t319= 4.59, p=.000), EMID subscale scores (no =21.82, sd=5.01, yes =20.47, sd=4.28, t319= 2.16, p=.032), and AMOT subscale scores (no =9.35, sd=5.95, yes =12.84, sd=7.18, t115.12= -3.91, p=.000). No significant difference was found between the participants states of absences and their EMIN subscale scores (no =16.71, sd=5.54, yes =15.50, sd=5.45, t319= 1.68, p=.094). To determine the difference between the participants' academic motivations and the high schools they were graduated from, a t-test for independent samples was applied and the results are presented in Table 3. X X X X X X X X X X X X X X X X X X X X X X X X X International Online Journal of Education and Teaching (IOJET) 2022, 9(2), 903-918. 909 Table 3. t-test results on participants’ academic motivations and the high schools they were graduated from Academic Motivation High school N Sd t df p IMTK FAHS* 288 21.23 5.54 -1.32 343 .189 Others 57 22.28 5.30 IMTA FAHS 288 17.01 6.05 -.84 343 .403 Others 57 17.74 5.94 IMES FAHS 288 17.31 5.93 -.44 343 .658 Others 57 17.69 5.99 EMER FAHS 288 22.47 4.98 .80 343 .423 Others 57 21.89 4.59 EMIN FAHS 288 16.86 5.58 2.09 343 .037 Others 57 15.16 5.88 EMID FAHS 288 21.93 4.65 3.13 343 .002 Others 57 19.75 5.31 AMOT FAHS 288 10.49 6.53 1.45 88.10 .150 Others 57 9.26 5.67 p<.05 *Fine Arts High School According to the results shown in Table 3, participants who were graduated from fine arts high schools ( =16.86, sd=5.58) have significantly higher scores than the participants who are graduated from other high schools rather than fine arts high schools ( =15.16, sd=5.88) on EMIN subscale scores (t343=2.09, p=037). Also, there is a significant difference between the participants’ high schools and their EMID subscale scores (FAHS =21.93, sd=4.65, others =19.75, sd=5.31, t343=3.13, p=.002). According to the results there is no difference between the participants’ high schools and their IMTK subscale scores (FAHS =21.23, sd=5.54, others =22.28, sd=5.30, t343=-1.32, p=.189), IMTA subscale scores (FAHS =17.01, sd=6.05, others =17.74, sd=5.94, t343=-.84, p=.403, IMES subscale scores (FAHS =17.31, sd=5.93, others =17.69, sd=5.99, t343=-.44, p=.658), EMER subscale scores (FAHS =22.47, sd=4.98, others =21.89, sd=4.59, t343=.80, p=.423, AMOT subscale scores (FAHS =10.49, sd=6.53, others =9.26, sd=5.67, t88.10=1.45, p=.150). To reveal the difference between the participants’ academic motivations and the lessons they have failed a one-way analysis of variance test (ANOVA) was applied. The results are presented in Table 4. X X X X X X X X X X X X X X X Erden Topoğlu 910 Table 4. ANOVA results on participants’ academic motivations and the number of lessons they have failed p<.016 According to Table 4 there are significant differences between the participants’ IMTK subscale scores (F (2-319) = 7.397, p = .001), IMTA subscale scores (F (2-319) = 4.164, p = .016), EMER subscale scores (F (2-319) = 9.529, p = .000), and the number of lessons they have failed. According to the Tukey test that was performed in order to reveal the cause of difference, the participants who are successful on all the lessons they get, have significantly higher IMTK subscale scores, IMTA subscale scores, and EMER subscale scores than participants who have failed on three or more of their classes. However, there is no significant difference between the participants’ academic motivations and their IMES subscale scores (F (2-319) = 4.071, p = .018), EMIN subscale scores (F (2-319) = .931, p = .395), and EMID subscale scores (F (2-319) = 1.576, p = .208). Since the variances were not homogeneous, a Kruskal-Wallis test was performed in order to investigate the difference between the participants’ AMOT subscale scores and the number of lessons they have failed. The results are presented in Table 5. Subscales Source of variance Sum of Squares df Mean Square F p Cause of significance IMTK Between groups 405.28 2 202.64 7.397 .001 0>3and+ Within Groups 8739.02 319 27.40 Total 9144.30 321 IMTA Between groups 288.72 2 144.36 4.164 .016 0>3and+ Within Groups 11058.06 319 34.67 Total 11346.78 321 IMES Between groups 278.89 2 139.45 4.071 .018 Within Groups 10927.66 319 34.26 Total 11206.55 321 EMER Between groups 417.26 2 208.63 9.529 .000 0>3and+ Within Groups 6984.11 319 21.89 Total 7401.37 321 EMIN Between groups 58.08 2 29.04 .931 .395 Within Groups 9952.25 319 31.20 Source of variance 10010.33 321 EMID Between groups 74.57 2 37.28 1.576 .208 Within Groups 7544.35 319 23.65 Source of variance 7618.92 321 International Online Journal of Education and Teaching (IOJET) 2022, 9(2), 903-918. 911 Table 5. Kruskal-Wallis test results on participants’ amot subscale scores and the number of lessons they have failed p<.016 According to Table 5, there is a significant difference between participants’ AMOT subscale scores and the number of lessons they have failed (x2 (df=2, n=322) = 21.861; p= .000). A number of Mann-Whitney U tests were applied in order to determine the cause of the difference. According to the Mann-Whitney U tests, the difference between AMOT subscale scores and the number of lessons participants have failed, was derived from the participants who were successful on all their lessons and participants who were failed on 1 or 2 lessons and 3 and more lessons. In addition, there is a significant difference between participants who were failed on 1 or 2 lessons and 3 and more lessons, regarding AMOT subscale scores. In order to determine whether there is a difference between the participants’ academic motivations and their career choice, a one-way analysis of variance test (ANOVA) was applied. The results are presented in Table 6. Table 6. ANOVA results on participants’ academic motivations and their career choice p<.012 According to Table 6, there is a significant difference between the participants IMTA subscale scores (F (3-344) = 14.662, p = .000), IMES subscale scores (F (3-344) = 7.572, p = .000), and EMIN subscale scores (F (3-344) = 4.403, p = .005). In order to determine the cause of the difference, a Tukey test was applied. According to the Tukey test, IMTA subscale scores of participants who want to be academicians are significantly higher than those who want to be a fine arts high school teacher, a music teacher in the Ministry of National Education, and those who plan to do another job than being a music teacher. Also, the participants who want to be a music teacher have higher IMTA subscale scores than those who plan to do another job than being a music teacher. IMES subscale scores of participants who want to be academicians are significantly higher than those who want to be a fine arts high school teacher, a music teacher in the Ministry of National Education, and those who plan to do another job than being a music teacher. Also, EMIN subscale scores of participants who want to be academicians are Lessons failed N Mean Rank X2 df p Cause of Significance 0 132 136.42 21.861 2 .000 0<1-2 1-2 95 163.56 0<3 and + 3 and + 95 194.29 1-2<3 and + Subscales Source of variance Sum of Squares df Mean Square F p Cause of significance IMTA Between groups 1429.30 3 476.43 14.662 .000 acad.>FAHT, acad.>music t., acad.>others, music t.>others Within Groups 9573.89 344 32.50 Total 10485.50 347 IMES Between groups 755.83 3 251.94 7.572 .000 acad.>FAHT, acad.>music t., acad.>others, Within Groups 11446.15 344 33.27 Total 12201.98 347 EMIN Between groups 407.49 3 135.83 4.403 .005 acad.>music t., acad.>others, Within Groups 10612.15 344 30.85 Total 11019.64 347 EMID Between groups 39.77 3 13.26 .558 .643 Within Groups 8167.72 344 23.74 Total 8207.49 347 Erden Topoğlu 912 significantly higher than those who want to be a music teacher in the Ministry of National Education, and those who plan to do another job than being a music teacher. There was no significant difference found between participants’ EMID subscale scores and their career choices (F (3-344) = .558, p = .643). Due to the variances were not homogeneous for IMTK, EMER, and AMOT subscales, a Kruskal-Wallis test was performed in order to reveal the difference between participants’ IMTK subscale scores, EMER subscale scores, and AMOT subscale scores and their career choices. The results are presented in Table 7. Table 7. Kruskal-Wallis test results on participants’ academic motivations and their career choice p<.012 According to the results presented in Table 7, there is a significant difference between the participants’ IMTK subscale scores (x2 (df=3, n=348) = 29.136; p=.000), EMER subscale scores (x2 (df=3, n=348) = 21.995; p=.000), AMOT subscale scores (x2 (df=3, n=348) = 35.477; p=.000) and their career choices. Multiple Mann-Whitney U tests were performed to reveal the cause of the difference. The results of the Mann-Whitney U tests have shown that IMTK subscale scores of participants who want to be an academician are significantly higher than those who want to be a fine arts high school teacher and those who want to be a music teacher in the Ministry of National Education, and those who plan to do another job than being a music teacher. Also, the participants who plan to do another job than being a music teacher have significantly lower IMTK subscale scores than those who want to be a fine arts high school teacher and those who want to be a music teacher in the Ministry of National Education. The participants who want to be an academician in the future have significantly higher EMER subscale scores than those who want to be music teachers in the Ministry of National Education and participants who plan to do another job than being a music teacher have significantly lower EMER subscale scores than those who want to be an academician, those who want to be a fine arts high school teacher and those who want to be a music teacher in the Ministry of National Education. In addition, the participants who plan to do another job than being a music teacher have significantly higher AMOT subscale scores than those who want to be academicians, a fine arts high school teacher, a music teacher in the Ministry of National Education. Also, the participants who want to be music teachers in the Ministry of National Education have higher Career choice N Mean Rank X2 df p Cause of Significance IMTK Academician 121 210.68 29.136 3 .000 acad.>FAHT, acad.>music t., acad.>others, FAHT>others music t.>others Fine arts Teacher 63 169.32 Music Teacher 105 160.41 Others 59 130.92 EMER Academician 121 201.65 21.995 3 .000 acad.>music t., acad.>others, FAHT>others, music t.>others Fine arts Teacher 63 181.90 Music Teacher 105 163.64 Others 59 130.25 AMOT Academician 121 148.94 35.477 3 .000 acad.