Examining the achievement goal orientation levels of Turkish pre-service music teachers

Abstract

Achievement goal orientation (AGO) might help music teacher candidates make their learning processes more effective by revealing how they are motivated towards the learning tasks. In this respect, the purpose of this study was to examine the levels of achievement goal orientation of pre-service music teachers according to eight variables. The participants of the study consisted of 1250 undergraduate students studying in the departments of music education during the academic year 2013–2014 in Turkey. The data were collected through an Information Form and the Achievement Goal Orientation Scale (AOS). The results of the study revealed that gender, grade level, students’ achievement level and willingness had small effects on students’ learning goal orientation. Practice time in music, students’ evaluation of their own achievement levels among their peers, the extent to which students found themselves skilled in music and pursuing another profession had a medium effect on learning goal orientation. Informing students about the achievement goal orientation and the effects of these goals on the teaching and learning process may help students with their achievement goal orientations towards the desired direction.

Keywords

achievement goal orientation learning goal orientation performance-approach goal orientation performance-avoidance goal orientation pre-service music teacher

Introduction

During instruction, teachers realize that their students adopt different achievement goal orientations (AGOs). This can be observed in students’ approaches towards competence, their purposes in learning tasks, and the ways they succeed. For instance, while the teacher might observe that the student named “Oya” does the given learning tasks to ensure she fully comprehends the subject matter, they might also observe that another student named “Mehmet” pays no attention to learning and only fulfills learning goals because he is anxious to get a good grade. On the other hand, the teacher might also observe that another student named “Ali” is avoiding the learning tasks because he is neither enthusiastic about learning nor anxious about getting a good grade. In the example mentioned above, Oya is internally motivated for learning. In this regard, while fulfilling the learning tasks, there is a personal satisfaction, and the difficulty of the task does not discourage her. However, Mehmet and Ali are mostly motivated for learning externally; therefore, they consider the learning tasks as performance oriented. The difference between Mehmet and Ali is that Mehmet wants others to think that he is successful, and therefore, avoids showing his performance. Whereas, what Ali wants is not to feel humiliated in front of his peers and teachers. Therefore, he avoids displaying performance due to possible embarrassment after failing. These examples given are reflections of students’ AGOs.

Achievement goal orientation theory was developed to understand students’ adaptive and maladaptive responses that change according to their achievement difficulties. As seen in Figure 1, there are two basic AGOs. These are learning goal orientation (called mastery goal or task goal) and performance goal orientation (called ability goal or ego goal). Learning goal orientation is concerned with fulfilling learning tasks for one’s own development and competence. However, in performance goal orientation individuals are concerned with being compared to others and aiming to look better (Dweck, 1986; Nicholls, 1984). Thus, learning orientation is about gaining competence whereas performance orientation is concerned with judgment of ability. The main difference between these two goals is whether learning reflects an internal or external goal (Meece, Blumenfeld, & Hoyle, 1988). This dual model was further expanded to include the distinction between approach and avoidance. According to this distinction, while approach goals emphasize the attempt to obtain positive results, avoidance goals emphasize the attempt to avoid negative results. Following this dual model, a trichotomous achievement model was designed to measure reasons for achievement and self-reported progress. Within this model, performance goal orientation was divided into performance approach goal and performance avoidance goal (Elliot & Church, 1997; Midgley et al., 1998). Then, the 2 x 2 AGO model, where learning goal orientation was divided into learning approach and learning avoidance goals, was developed (Elliot & McGregor, 2001). Following these improvements, an increase in the number of studies based on these achievement models was observed. The trichotomous AGO model has been the subject of much research in music (e.g., Lacaille, Koestner, & Gaudreau, 2007; Matthews & Kitsantas, 2012; Nielsen, 2008; Smith, 2005). However, other studies (e.g., Harackiewicz, Barron, Pintrich, Elliot, & Thrash, 2002) suggest that the 2 x 2 AGO model would be more beneficial than the dual and trichotomous models. Yet, the results of some studies applying the 2 x 2 AGO model in music (e.g., Miksza, Tan, & Dye, 2016) revealed that this theoretical framework may not work in music as it worked in other academic fields and sports. For example, Miksza, Tan, and Dye (2016) assumed that 2 x 2 AGO would be more appropriate for data analysis. Considering these views, this study used a trichotomous AGO model (Figure 2) to examine the AGO levels of pre-service music teachers.

Figure 1.

Achievement goal orientation models.

Figure 2.

Achievement goal orientation model based on research.

This model is designed to examine relationships among variables that affect achievement behaviors among students. In the model, where AGO was based on a trichotomous structure, learning goal orientations (also known as mastery goals or process goals) included the desire to reach proficiency by acquiring additional information or mastering skills. In this respect, learning goal orientation reflects “the need for excellence for its own sake, without regard for any external rewards that one’s accomplishments might bring” (Ormrod, 2004, p. 438). Thus, in related literature, learning goal orientation is associated with positive learning outcomes.

Performance-approach goal orientation reflects the effort of students in demonstrating their competence, whereas in performance-avoidance goal orientation students try to “avoid the demonstration of incompetence” (Midgley et al., 2000, p. 10). Negative characteristics of performance goal orientations are mostly attributed to performance-avoidance goal orientation. Elliot and Church (1997) stated that accepting a performance goal may cause easy or extremely difficult task choices, giving up or not enjoying the task when facing failure. It appears that both learning orientation and performance-approach goal orientation promote learning behaviors appropriate for high achievement compared to performance-avoidance goal orientation. In general, performance goal orientation shifts the focus of the individual from giving complete attention to the learning task, to anxieties about social limitations. This shift accounts for the use of shallow learning strategies, such as low attention towards learning, disorder and repetition, especially for the performance-avoidance goal orientation (Elliot, McGregor, & Gable, 1999).

Achievement goal orientation has an important role in students’ learning processes. Studies show that students who have learning oriented courses have high evaluation levels, and students with high performance goal orientation have lower evaluation levels (Barron & Harackiewicz, 2003). Similarly, Ames and Archer (1988) suggested that the students who perceived the importance of learning goal orientation within the classroom used more effective strategies, preferred more difficult tasks, displayed a more positive attitude towards the class, and had a stronger belief that success emerges as a result of the effort shown by a person. However, it was also found that students who perceived the performance goals as tempting were more inclined to focus on their own skills by evaluating them negatively and to attribute failure to lack of skill. Church, Elliot, and Gable (2001) tested the perceived classroom environment and achievement goal variables as predictors of performance and intrinsic motivation, and the results also clearly showed that the perceived classroom environment affected the AGO.

Focusing on AGO in music education, Matthews and Kitsantas (2012) put forward the role of a conductor’s goal orientation and the use of shared performance cues in orchestra members’ motivational beliefs and performances. They found that participants in the mastery goal orientation condition reported higher levels of collective- and self-efficacy beliefs and assigned the success or failure of the ensemble usually to the rehearsal strategies of the conductor. Self-efficacy reflects students’ beliefs about their capabilities to produce the levels of performance required. Miksza (2011) examined the relationships between undergraduate brass and woodwind instrumentalists’ music practices and their AGOs. He found no significant differences in performance achievement as a function of goal orientations. Miksza et al. (2016) examined the AGOs of students who received instrumental music education in the United States and Singapore by applying the 2 x 2 achievement goal framework. Their findings revealed that the 2 x 2 achievement goal framework in instrumental music contexts may not work as well as it does in other fields. Nielsen (2008) also worked on the relationships between AGOs, learning strategies and instrumental performance and determined that the learning goal orientation of music students was high. Similarly, Smith (2005) aimed to assess the relationship between university students’ motivational beliefs and their self-reported musical studying behaviors, and the compatibility of their academic motivation with their music field. Smith (2005) found that students using more learning strategies scored higher on the learning orientation. Schatt (2011), on the other hand, synthesized the literature on achievement motivation using a sample of musicians. There have been few studies addressing music education as a whole, and hence this study tries to fill this gap in the field of training music teachers.

Researchers proposed that determining the AGOs of students studying in teacher training programs would provide benefits in terms of both their own learning processes and the learning processes of their future students. This assertion has provided the starting point of this study. Among teacher training programs, the departments of music play an important role in preparing teachers with an artistic personality. Undergraduate music education programs aim to help pre-service music teachers acquire competences desired by the profession and thus to build their professional identities. Pre-service music teachers must become competent in their professional fields through the classes in which they hear, talk and write musically, learn to play one or more musical instruments, and learn the essence of the profession. At this point, AGO might help in making learning processes more effective by revealing how students are motivated towards the learning tasks. Nevertheless, few studies have been conducted concerning musicians targeting AGO (e.g., Matthews & Kitsantas, 2012; Miksza, 2011; Nielsen, 2008; Schatt, 2011; Smith, 2005).

Purpose of the study

This study aimed to analyze the AGO levels of pre-service music teachers based on eight variables: gender, grade levels, grade point averages (GPAs), enrollment, practice time, evaluation of achievement, skill perception and pursuing another profession. The variables of the study were determined on the research literature in the field of music and other subjects. It is believed that exogenous variables may influence AGO levels of students. Achievement goal orientation was examined according to the gender variable in various studies (e.g., Aydın, 2014; Eyi, 2010; Küçükoğlu, Kaya, & Turan, 2010; Oral, 2012; Özkal, Demirtaş, Kasap Sucuoğlu, & Güzeller, 2014; Toğluk, 2009; Tutaş, 2011; Üzbe, 2013). These studies found differences between female and male students’ AGO levels.

In some studies, differences in AGO levels were discussed according to the grade level variable (e.g., Fouladchang, Marzooghi, & Shemshiri, 2009; Küçükoğlu et al., 2010). Differences created by academic achievement on AGO level became a subject of curiosity for researchers (e.g., Buluş, 2011; Coutinho, 2007; Elliot et al., 1999; Harackiewicz, Barron, Tauer, & Elliot, 2002; Nielsen, 2008). It is observed that the AGO scores vary according to grade levels.

We also examined the relationship between academic success and AGO. This study used self-reported high school GPAs from students. Primarily due to the difficulty and legality in obtaining official school records or documentation of such information, the study had to rely on students’ self-reported information. In the questionnaire, students were asked to mark their high school GPAs as low (30–52), average (53–75), high (76–98) or very high (99–100). Nielsen (2008) and Coutinho (2007) examined the relationships between AGOs and academic success. Harackiewicz, Barron, Tauer, and Elliot (2002) focused on the role of achievement goals and high school performance in predicting the future academic success of students during their university life. While Nielsen (2008) and Coutinho (2007) found a correlation between academic success and AGO, Harackiewicz, Barron, Tauer, and Elliot (2002) suggested that academic success did not predict learning orientation.

Reasons of enrollment were also a point of research. Whether students willingly attended the undergraduate program or not was examined (e.g., Aydın, Gürbüzoğlu Yalmancı, & Yel, 2014; Toğluk, 2009). It is observed that due to socio-economic constraints, students may have to enroll in undergraduate programs that they do not want to study. The university entrance examination in Turkey determines where students can enroll in higher education. A student’s score in the entrance exam combined with weights for his/her high school grade point average, and program choice determine a student’s placement. Access to tertiary education is limited and families exert an extraordinary effort to have their children placed in higher education since they see university as a privilege and as a door that opens to jobs. Students with a low socio-economic background are at a distinct disadvantage relative to other students taking private tutoring and special courses to improve exam scores. Students with limited means cannot retake the exam to increase their scores to be placed in a program they want to study. With the pressure from their families and society they unwillingly select a program requiring low entrance exam scores (World Bank, 2007). Thus, it seems that students involved in music with low scores reluctantly enroll in music education programs requiring low entrance exam scores that train music teachers. Actually they want to be accepted into the prestigious music education programs or be placed in conservatories that mostly train for performance and musical theory. Moreover, students going through the stressful exam preparation period for many years and getting low exam scores may prefer to enroll in a program instead of retaking the exam and going through the same process again the next year.

Some other studies, also found that when the practice time in the field increased, strategy usage increased as well (e.g., Aydıner Uygun & Kılınçer, 2012). The study also examined the out-of-class practice time of the students and their AGO. In out-of-class practice time, students practiced assigned pieces that were directly related to the curriculum content. The relationship between strategy usage and AGO has been the subject of research (e.g., Nielsen, 2008; Schraw, Horn, Torndike-Christ, & Bruning, 1995; Smith, 2005). While some studies found that students’ perceptions about their achievement level (e.g., Toğluk, 2009; Tutaş, 2011) affected AGO levels, some studies put forward that students’ perceptions about their level of competence (e.g., Goraya & Hasan, 2012; McCormick & McPherson, 2003; Tutaş, 2011) affected AGO levels. Also abandoning studies was related to AGO (e.g., Lacaille et al., 2007). However, the effect of these variables on the AGO levels of students studying music education was not examined. Studying all these variables may provide tangible data to students, teachers and researchers in the field by assessing the AGOs of students studying music education. Therefore, this study has attempted to answer the following research questions:

Do the AGO levels of pre-service music teachers differ according to:

gender?

current grade level?

achievement level in high school (self-reported high school grades)?

whether they willingly or unwillingly study in an undergraduate music education program?

out-of-class practice time in the last three days?

the evaluation of their own achievement levels among their classmates?

the extent to which they find themselves skilled in music?

whether they would consider choosing a profession other than music teaching after graduation?

Method

Participants

The scope of this study was limited to Turkish pre-service music teachers. While selecting the pre-service educators for the study, a simple random sampling method was used. Simple random sampling is applied in an equal probability of selection for all elements in the population (Ross, 2005).

The study was conducted at Turkish state universities providing music education. The target population (universe) included first-, second-, third- and fourth-year undergraduate students studying music education during the academic year 2013–2014. There were 22 music education departments in Turkey by the academic year 2013–2014 and the target population consisted of 2760 subjects. However, since some departments did not have students at every grade level due to recent opening, they were not included in the study. The required sample size was calculated as 337 using the following formula of power analysis:

n = \frac{{N t}^{2} p q}{d^{2} (N - 1) + t^{2} p q}

The study included 1250 participants in the study sample.

Instrumentation

Data were collected from the Personal Information Form and the Achievement Goal Orientations Scale. The Personal Information Form was designed by the researchers to acquire demographic information related to the study. The form consisted of eight demographic questions (e.g., gender, grade level, GPAs). The other data-collection tool used in the study was the Achievement Goal Orientations Scale (AOS). The scale was developed by Midgley et al. in 1998 (see Appendix A) and adapted into Turkish by Akın and Çetin in 2007 (see Appendix B). The original form of the scale was a five-point Likert-type scale, and had 18 items, with the first six items for determining learning goal orientation (LO), the second six items determining performance-approach goal orientation (PApO), and the last six items determining performance-avoidance goal orientation (PAvO).

Akın and Çetin (2007) analyzed the linguistic equivalence correlations of AOS. The correlations between the English and Turkish forms were found to be at .93 for LO, .90 for PApO, and .96 for PAvO. The factor loadings were between .47 and .92 for the three goal orientations (LO, PApO, and PAvO). The Cronbach’s alpha coefficients of internal consistency were predicted to be at .77 for LO, .79 for PApO, and .78 for PAvO. The test–retest reliability was found to be at .95 for LO, .91 for PApO, and .94 for PAvO.

Procedure

A paper-and-pencil format was used when giving out the questionnaires to the participants. The photocopied form and scale were given to the students in one session (45 minutes). The students filled in some background information about themselves, and they also mentioned their opinions on their AGOs. The students were asked to mark the most appropriate statement (never, seldom, sometimes, often, always) with an X. Trusting people is the presupposition in the study. Also, each of the questions in AOS elicits similar (though not the same) information in slightly different ways. For this reason, the students’ answers to the questions in the scale were regarded as truthful. In the study, the questionnaires that were not completed and were left blank were excluded from the evaluation.

Research design and data analysis

The study employed a survey model, one of the quantitative data-collection methods. In the survey model, there is no attempt to change or affect the subject field of the research (Karasar, 2009). The study tried to clarify the relationship between the AGOs of pre-service music teachers and the variables.

Before analyzing the data, several assumptions were tested. Initially, in order to determine whether or not the scores for LO, PApO, PAvO, and AOS showed normal distribution within each group of independent variables, the Kolmogrov–Smirnov test for normality was used and it was found that the data did not meet the normality assumptions. At the same time, homogeneity of variance assumption was tested and variances for each group were found to be unequal. Thus, non-parametric tests were used. The Mann–Whitney U test was used to test whether or not there was a significant difference according to the independent variables, for two groups (gender, willingness in attending the undergraduate program of music teaching). The Kruskal–Wallis test was used to test whether or not there was a significant difference according to the independent variables for more than two groups (grade levels, GPAs, out-of-class practice time, and pursuing another profession). To determine how effective the independent variable was on the dependent variable, eta-squared (η²) value was calculated. Eta-squared that represents the total variance size of independent variable on dependent variable varies between 0.00 and 1.00; and η² values at the levels .01, .06 and .14 are interpreted as small, medium and large respectively (Büyüköztürk, 2009; Cohen, 1988 cited in Stevens, 2002).

Results

In the present study, the AGO levels of pre-service music teachers in Turkey were examined according to eight variables. The Mann–Whitney U test and the Kruskal–Wallis test were performed on the appropriate scores to examine whether differences were significant in terms of gender, grade levels, GPAs, enrollment, practice time, evaluation achievement, skill perceptions and pursuing another profession. The results concerning the scores on these variables are presented below.

As seen in Table 1, the possible minimum score for the learning goal orientation was 6, and the maximum was 30. The mean score of the students for the learning goal orientation was found to be $\bar{X}$ = 23.73. The mean score of the students for the learning goal orientation was higher than the mean score they had on the scale, 18 ((6+30)/2). Thus, it could be suggested that the learning goal orientation scores of the students were high. It is also evident that the mean score of the students for the performance-approach goal orientation, $\bar{X}$ = 19.40, was higher than the mean score for the scale, 18 ((6+30)/2). So, it is suggested that the performance-approach goal orientation scores of the students were high. The mean score for the performance-avoidance goal orientation, $\bar{X}$ = 11.20, was found to be lower than the mean score for the scale, 15 ((5+25)/2). From these findings, it is understood that the performance-avoidance goal orientation scores of the students were low.

Table 1.

Students’ achievement goal orientation levels.

Achievement goal orientation	$\bar{X}$	Standard deviation	Variance	Minimum	Maximum	Range
LO	23.73	4.61120	21.263	6.00	30.00	24.00
PApO	19.40	6.32295	39.980	6.00	30.00	24.00
PAvO	11.20	5.39106	29.064	5.00	25.00	20.00

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

According to the findings in Table 2, a significant difference was found between the scores of female and male students in learning goal orientation. Regarding the eta-squared values, it is observed that gender variable had a small effect on students’ learning goal orientation and performance approach goal orientation.

Table 2.

Comparison of the students’ achievement goal orientation levels and gender.

Achievement goal orientation	Gender	N	Mean rank (MR)	Rank sum	U	p	η²
LO	Female	746	647.67	483161.00	1692.00	0.005 *	0.007
LO	Male	501	588.76	294967.00	1692.00	0.005 *	0.007
PApO	Female	746	642.22	479098.00	1733.00	0.029 *	0.004
PApO	Male	501	596.87	299030.00	1733.00	0.029 *	0.004
PAvO	Female	746	613.49	457660.50	1790.00	0.206
PAvO	Male	501	639.66	320467.50	1790.00	0.206

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

The eta-squared values in Table 3 reveal that the grade variable had a medium effect on students’ learning goal orientation and performance approach goal orientation.

Table 3.

Comparison of the students’ achievement goal orientation levels and their grade levels.

Achievement goal orientation	Grade level	N	Mean rank	SD	X²	p	Significant difference	η²
LO	GRADE 1	347	734.77	3	63.669	0.000 *	1–21–31–42–43–4	0.051
	GRADE 2	316	625.75
	GRADE 3	243	617.48
	GRADE 4	342	516.45
PApO	GRADE 1	347	712.96	3	40.307	0.000 *	1–21–31–42–43–4	0.032
	GRADE 2	316	628.98
	GRADE 3	243	611.78
	GRADE 4	342	539.64
PAvO	GRADE 1	347	604.00	3	3.510	0.319
	GRADE 2	316	634.84
	GRADE 3	243	655.43
	GRADE 4	342	613.76

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

Table 4 shows that the students with very high achievement had a mean score of 3.50–4.00, the students with high achievement had a mean score of 2.50–3.40 and the students with average achievement had a mean score of 1.50–2.40. The students with lower achievement had a mean score of 0.50–1.40. The eta-squared values in Table 4 show that the achievement level in high school had a small effect on students’ learning goal orientation.

Table 4.

Comparison of the students’ achievement goal orientation levels with self-reported high school grade point averages (GPAs).

Achievement goal orientation	High school GPAs	N	Mean rank	SD	X²	p	Significant difference	η²
LO	Very high	179	615.72	3	11.722	0.008 *	High–averageHigh–lowVery high–low	0.009
	High	546	649.37
	Average	486	599.91
	Low	29	451.36
PApO	Very high	179	632.32	3	1.879	0.598
	High	546	631.92
	Average	486	605.30
	Low	29	587.34
PAvO	Very high	179	616.65	3	5.497	0.139
	High	546	601.02
	Average	486	637.22
	Low	29	730.72

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

Table 5 illustrates that there was a significant difference between the learning goal orientation scores of the students attending the undergraduate music education program willingly and the students attending unwillingly. In this respect, whether students attended the undergraduate program willingly or not had a small effect on students’ learning goal orientation.

Table 5.

Comparison of the students’ achievement goal orientations and willingness to attend the music teaching program.

Achievement goal orientation	Willingly?	N	Mean rank	Rank sum	U	p	η²
LO	Yes	1197	628.90	752787.50	2167.00	0.004 *	0.007
LO	No	48	475.99	22847.50	2167.00	0.004 *	0.007
PApO	Yes	1197	624.51	747537.50	2692.00	0.459
PApO	No	48	585.36	28097.50	2692.00	0.459
PAvO	Yes	1197	620.03	742175.00	2517.00	0.143
PAvO	No	48	697.08	33460.00	2517.00	0.143

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

Table 6 shows that greater amounts of practice time were associated with higher learning goal orientation scores. According to the eta-squared values, practice time in music outside courses had a medium effect on students’ learning goal orientation and small effect on students’ performance avoidance goal orientation. There was a significant difference between the students’ performance-avoidance goal orientation scores according to their out-of-class practice time in the last three days.

Table 6.

Comparison of the students’ achievement goal orientation levels and out-of-class practice time.

Achievement goal orientation	Practice time	N	Mean rank	SD	X²	p	Significant difference	η²
LO	Less than 1 hour	212	488.95	4	50.463	0.000 *	Less than 1 hour–1–3 hoursLess than 1 hour –4–6 hoursLess than 1 hour –7–9 hoursLess than 1 hour –10 or more1–3 hours–4–6 hours1–3 hours–10 or more4–6 hours–10 or more7–9 hours–10 or more	0.041
	1–3 hours	526	610.74
	4–6 hours	342	676.27
	7–9 hours	90	653.99
	10 or more	69	769.96
PApO	Less than 1 hour	212	562.46	4	8.270	0.082
	1–3 hours	526	633.03
	4–6 hours	342	640.36
	7–9 hours	90	587.13
	10 or more	69	639.38
PAvO	Less than 1 hour	212	633.41	4	9.728	0.045 *	Less than 1 hour –7–9 hours4–6 hours–7–9 hours	0.008
	1–3 hours	526	620.28
	4–6 hours	342	646.59
	7–9 hours	90	530.98
	10 or more	69	561.01

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

The eta-squared values in Table 7 revealed that students’ evaluation of their own achievement levels among their peers had medium effect on students’ learning goal orientation, performance approach goal orientation and performance avoidance goal orientation.

Table 7.

Comparison of the students’ achievement goal orientation levels according to their evaluation of their own achievement levels among their peers.

Achievement goal orientation	Achievement level evaluation	N	Mean rank	SD	X²	p	Significant difference	η²
LO	Top	489	698.59	2	48.961	0.000*	Top–middleTop–lowMiddle–low	0.039
	Middle	699	585.02
	Low	55	410.97
PApO	Top	489	664.55	2	15.692	0.000*	Top–middleTop–lowMiddle–low	0.013
	Middle	699	602.03
	Low	55	497.46
PAvO	Top	489	574.93	2	14.823	0.001*	Top–middleTop–low	0.012
	Middle	699	649.22
	Low	55	694.62

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

As for the skill perception variable results, the eta-squared values in Table 8 showed that the extent to which students found themselves skilled in music had a medium effect on students’ learning goal orientation and performance approach goal orientation.

Table 8.

Comparison of the students’ achievement goal orientation levels and their skill perception.

Achievement goal orientation	Skill	N	Mean rank	SD	X²	p	Significant difference	η²
LO	Low	48	361.98	2	33.539	0.000 *	Low–averageLow–high	0.027
	Average	768	602.79
	High	411	664.37
PApO	Low	48	417.48	2	20.301	0.000 *	Low–averageLow–high	0.016
	Average	768	605.31
	High	411	653.19
PAvO	Low	48	675.80	2	2.362	0.307
	Average	768	618.32
	High	411	598.71

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

The eta-squared values in Table 9 on pursuing another profession showed that whether or not students consider going into another profession other than music teaching had a medium effect on students’ learning goal orientation and a small effect on students’ performance-avoidance goal orientation.

Table 9.

Comparison of the students’ achievement goal orientation levels and pursuing another profession.

Achievement goal orientation	Another profession	N	Mean rank	SD	X²	p	Significant difference	η²
LO	Never	486	692.56	4	37.815	0.000 *	Never–seldomNever–sometimesNever–oftenNever–always	0.030
	Seldom	301	605.63
	Sometimes	253	590.43
	Often	102	498.24
	Always	103	549.06
PApO	Never	486	643.19	4	3.918	0.417
	Seldom	301	623.01
	Sometimes	253	614.10
	Often	102	579.91
	Always	103	592.21
PAvO	Never	486	585.50	4	11.044	0.026 *	Never–sometimesNever–oftenNever–always	0.009
	Seldom	301	627.55
	Sometimes	253	647.67
	Often	102	664.60
	Always	103	684.83

LO = learning goal orientation; PApO = performance-approach goal orientation; PAvO = performance-avoidance goal orientation.

p < 0.05.

Discussion

This study examined the AGO levels of pre-service music educators in Turkey with respect to eight variables. The results of the study on students’ AGO levels are consistent with the results of the study conducted by Nielsen (2008), where he examined the relationships between AGOs, the use of learning strategies and the academic achievement of 130 students from The Norwegian Academy of Music. Nielsen (2008) found that the first-year music students were oriented towards learning goal orientations and the performance-approach goal orientation and not towards the performance-avoidance goal orientation. Thus, the music students gave importance to demonstrating higher competence and self-improvement than to outperforming other students or losing in competition. Our results on learning goal orientation are consistent with those of Chan (2008); however, our performance-approach goal orientation results differ from his findings. In his study, Chan examined the AGOs of 1041 gifted Chinese students living in Hong Kong. The results obtained from this study showed that they were directed towards learning goal orientation instead of performance-approach or performance-avoidance goal orientations. In the related studies, it is seen that the detrimental consequences of performance goals are often attributed to performance-avoidance goals, making a distinction between performance-approach and performance-avoidance orientations (Chan, 2008).

Achievement goal orientation levels and gender

An analysis was conducted to examine whether the gender variable had an effect on students’ AGO levels. The scores of female students for the learning goal orientation and performance-approach goal orientation were found to be higher than the scores of male students. However, there was no difference between the performance-avoidance goal orientation scores of female and male students. According to the results on Achievement Orientation Levels in grades, higher levels of students’ scores for the learning goal orientation and performance-approach goal orientation were associated with higher grade levels. The difference found might be because predominantly female students enrolled in the department of teaching in general, and specifically in the department of music teaching. It is thought that the difference between the AGO levels of female and male students depended on the characteristics of individual students. In addition, the results obtained from Davis, Pastor, and Barron (2004) seem to support this view. They suggested that the differences in AGOs could be partially accounted for by the characteristics of the students enrolled in that department. In other studies comparing female and male students’ AGO levels, however, it was found that the learning goal orientation and performance-approach goal orientation levels of female students were higher than those of the male students. There was no difference between their performance-avoidance goal orientation levels (Küçükoğlu, Kaya, & Turan, 2010; Oral, 2012). Aydın (2014), on the other hand, found that while the AGO levels of female students were higher, performance-avoidance goal orientation levels were higher in male students. Tutaş (2011) also focused on gender and found that the AGOs of female students were higher in all three levels. In some other gender studies, significant differences were found only in one level of the AGO. In these studies, the learning goal orientation levels of female students were higher than the male students’ levels (Özkal et al., 2014; Toğluk, 2009) or performance-approach goal orientation (Eyi, 2010). The AGO levels of male students in performance-avoidance goal orientation (Üzbe, 2013) were found to be higher than those of the female students. From the related studies, it could be concluded that the relatively positive AGO was attributed mostly to female students, and the relatively negative mostly to male students.

Achievement goal orientation levels and grades

The present research also focused on the grade variable. According to the results, there was no significant difference between the performance-avoidance goal orientation scores of the students. Similar findings were found by Fouladchang et al. (2009). They examined the AGO levels of Iranian undergraduate students, and revealed that the learning orientation scores of students were in favor of the fourth-year students. Küçükoğlu et al. (2010) investigated the achievement levels of primary school teachers and their findings revealed a different result. There was a significant difference between the learning orientation and performance-approach goal orientation levels of the students in favor of the first-year students.

Achievement goal orientation levels and GPAs

The present study examined the effect of academic success in high school on the AGOs of pre-service educators. The findings on achievement levels in high school showed that the GPAs were not associated with the performance-approach goal and performance-avoidance goal scores of the students. However, there was a significant difference between the learning goal orientation scores according to their achievement levels in high school. The results revealed that achievement levels in high school were associated with a higher level of scores for learning goal orientation. From this finding, it could be concluded that students’ achievement levels obtained prior to university affect their learning orientation levels. This finding is consistent with the findings of Coutinho (2007). In Coutinho’s study, while the students’ performance goal orientations were not found to be related to their academic success, it was suggested that the students with a learning orientation reaped the benefits of academic success. Similarly, Buluş (2011) determined that the relationship between learning orientation and academic achievement was positive.

Our findings on achievement levels in high school are consistent with the results of Elliot et al. (1999). They found that learning orientation was the indicator of deep processing, persistence and effort, and performance-approach goal orientation was the indicator of shallow processing, persistence, effort and test achievement. Hence, they suggested that performance-avoidance goal orientation was the indicator of shallow processing rather than deep processing and test achievement.

The results of Harackiewicz, Barron, Tauer, and Elliot’s study (2002) were contrary to the findings of the current study. They found that learning orientation predicted sustained attention in the field, and thus high school performance predicted academic success but did not predict sustained attention in the field. However, Nielsen (2008), found a significant relationship between the AGO levels of music students and academic success.

Achievement goal orientation levels of students and willingness to attend the music teaching program

The current study also focused on the relationship between AGO levels and the reasons for enrollment, that is, whether students enrolled in the music department willingly or due to socio-economic factors. While no significant difference was found between the students’ performance-approach and performance-avoidance goal orientation scores, a significant difference was found between the scores for the learning orientation according to this variable. In the study, the learning orientation scores of the students enrolling willingly were found to be higher than the scores of the students studying unwillingly. The results show that the students willingly studying in an undergraduate music education program are more eager to learn. Therefore, they exert more effort in learning. This emphasizes the importance of the introduction to the profession. Our result is consistent with the results of other studies examining the relationships between AGOs and preference for professions other than music teaching (e.g., Aydın et al., 2014; Toğluk, 2009).

Achievement goal orientation levels and students’ out-of-class practice

In the music field, it is believed that out-of-class practice time might have a positive effect on academic achievement. The out-of-class practice time for the last three days might give insight into whether or not co-curricular studies are regularly sustained. Accordingly, study results showed that the scores of the students for the learning orientation increase as the out-of-class practice time during the last three days increases. Students’ practice times outside their classes might provide us with an understanding of how much effort they exert for learning and how willing they are to learn. In this study, students who had a limited practice time outside classes had high scores on the performance-avoidance goal orientation. This shows that these students did not have enough desire for learning and did not exert enough effort to learn.

Students’ out-of-class practice times might suggest their use of learning strategies. Thus, in a study by Aydıner Uygun and Kılınçer (2012), where they examined the use of learning strategies in learning the piano repertoire, it was found that as the time allocated by the students for the piano increased, their usage level of learning strategies increased as well. The results of the related studies document the effect of out-of-class practice time on the usage level of learning strategies and the effect on the AGO.

Our results are in line with those of Schraw et al. (1995), who examined the effects of the AGOs of undergraduate students on their use of strategy and metacognition levels. They found that students with high scores on the learning goal orientation had more metacognitive knowledge and used more strategies. Similarly, Nielsen (2008) showed that students who reported the use of learning strategies more often were more oriented to learning. He suggested that the students of music who were interested in learning, personal development and mastery of difficult music were more inclined towards learning music in cognitive, metacognitive and social terms. However, it was less likely for the students who adopted the performance-avoidance goal orientation to use the cognitive, metacognitive and social learning strategies during their practices. Smith (2005) also found that the students who reported using more learning strategies more often had higher learning orientation levels. The results from the study by Üzbe (2013) also support this view. Üzbe found that the tendency to self-handicap of the students who adopted the performance-avoidance goal orientation was higher, whereas the tendency to self-handicap of the students who adopted the learning orientation was lower.

Achievement goal orientation levels and students’ evaluation of their own achievement levels among their classmates

Our results on the effect of students’ perceptions on AGO levels revealed that higher levels of students’ scores for the learning goal orientation and performance-approach goal orientation were associated with higher levels of students’ perception of their achievement among their peers. We also found that the performance-avoidance goal orientation scores of the students who assessed their achievement levels in the top group were lower than the scores for performance-avoidance goal orientation of the students who evaluated themselves as being in middle and low achievement groups. From these results, it could be concluded that learning goal orientation and performance-approach goal orientation have a positive effect on students’ evaluation of their own achievement levels among their classmates. No significant difference was found between the students’ performance-avoidance goal orientation scores according to how skilled they found themselves in music. These findings are consistent with previous research on the effect of students’ evaluation of their own achievement levels among their classmates. For instance, Zusho, Pintrich, and Schnabel (2002) showed that the perceptions of self-efficacy of those who focused on the goals of learning the task given showed a better performance than others. Similarly, Toğluk (2009) found that while the learning-oriented students perceived themselves as successful, the performance-avoidance-oriented students perceived themselves as only moderately successful. Tutaş (2011) showed that the undergraduate students with high perceived academic achievement adopted the learning orientation more than students with a poorly perceived academic achievement. The results seem to show that students’ self-efficacy beliefs account for their achievement goal orientations.

Achievement goal orientation levels and skill perceptions of students in music

As for the skill perceptions, the scores of the students who found themselves moderately or highly skilled in music for the learning goal orientation and performance-approach goal orientation were higher than the scores of the students who found themselves poorly skilled in music. These results are consistent with previous research. For instance, Goraya and Hasan (2012) revealed that the learning orientation, performance-approach goal orientation and perceived skill levels of the undergraduate students with high achievement levels were higher than the levels of the students with a moderate and low achievement level. Tutaş (2011) found that the students with a high perceived skill level adopted the learning orientation more often than the students with a low perceived skill level. She suggested that compared to the students with high perceived skill, the students with a low perceived skill level more often adopted the performance-avoidance goal orientation. Moreover, McCormick and McPherson (2003) emphasized that the self-efficacy perception of the student is a significant predictor of his or her test performance. The results obtained from the study showed that the self-efficacy perceptions of students of their skills had an important role in predicting their actual performance in the music exam.

Achievement goal orientation levels and students’ consideration of going into another profession other than music

The results of the current study showed that the learning orientation scores of the students who never thought of a profession other than music were higher than the scores of the students who seldom, sometimes, often or always thought of another profession. The performance-avoidance goal orientation scores of the students who never thought of going into another profession other than music were found to be lower than the scores of the students who sometimes, often or always thought of going into another profession. However, no significant difference was found between the students’ performance-approach goal orientation scores according to whether they thought of taking another profession other than music. These results could be better accounted for through establishing a connection with the results of Lacaille et al. (2007). They found that the students with learning orientation reported that they showed better performance, had greater satisfaction after the performance and had less intention of leaving their disciplines. However, the students with a performance-avoidance goal orientation reported significantly lower satisfaction after this important event and higher intention levels of leaving their disciplines. Along with interpreting the results of the present study, it could be suggested that it was not surprising that the learning orientation levels of the students who did not think of a different profession were higher, and the performance-avoidance goal orientation levels of the students who thought of a profession other than music teaching were higher.

Conclusion

The results of the present study indicate that while in learning orientation and performance-approach goal orientation scores of students’ achievement orientation were high, students’ performance-avoidance goal orientation scores were found to be low. Within this range, it can be said that students’ scores for performance orientation that are associated with positive characteristics are high. In related studies, while the performance-approach goal orientation is often associated with positive learning outcomes, the performance-avoidance goal orientation is related to negative variables. The performance-approach goal orientation in the current study was also found to be related to some variables that could be considered as positive. In this regard, through experimental method, it may be beneficial to suggest strategies, methods and techniques that can be effective in directing AGOs of students towards the learning goal orientation.

When all findings from the present study are interpreted as a whole, it is seen that the learning goal orientation levels of pre-service music teachers show significant differences according to the variables of high school achievement, out-of-class practice time, and perception of achievement and skill level. Based on these results, it is considered important to inform students about AGOs and their effects on teaching and learning practices, as it would make them aware of their own AGOs. This understanding might enable them to manage their own AGOs. It might also be encouraging to inform class teachers about the possible effects of AGOs. Thus, raising students’ and teachers’ awareness of AGOs may help to create a desired teaching and learning environment. Other variables positively related to learning orientation include variables such as, enrolling to the department willingly and not pursuing another profession after graduation. It could be suggested that these findings emphasize the importance of introduction to the profession. Giving students opportunities at a young age to test themselves in various professional fields might have a positive effect on their AGOs. In other words, this effort might help them to choose fields in which they could be happy and successful. Moreover, music schools could conduct an assessment to determine whether students really planned to study music education and to help them adapt in the program.

In the present study, the AGOs of pre-service music teachers were discussed within a general framework. In future studies, the AGOs of students studying in departments of music education could be discussed separately under headings such as instrumental training, vocal training, and training for musical theory. In order to implement this examination, some scales measuring the AGOs specific to the field of music education could be designed. In addition, researchers could examine the relationship of AGOs with variables other than those addressed in this study. The AGO scale administered in this study made it possible to reach numerically strong data by including more subjects in the study. However, subjects assessing their own achievement orientations based on their own perceptions is a limitation. The researchers might collect the data first hand by examining pre-service music teachers’ AGOs through interviews and observations. Thus, pre-service music teachers’ AGOs could be examined within a qualitative framework.

Footnotes

Appendix

Appendix B.

Achievement goal orientation scales.

	Learning goal orientation	Never	Seldom	Sometimes	Often	Always
1	I like school work that I’ll learn from, even if I make a lot of mistakes.
2	An important reason why I do my school work is because I like to learn new things.
3	I like school work best when it really makes me think.
4	An important reason why I do my work in school is because I want to get better at it.
5	I do my school work because I’m interested in it.
6	An important reason I do my school work is because I enjoy it.
	Performance-approach goal orientation	Never	Seldom	Sometimes	Often	Always
7	I would feel really good if I were the only one who could answer the teachers’ questions in class.
8	It’s important to me that the other students in my classes think that I am good at my work.
9	I want to do better than other students in my classes.
10	I would feel successful in school if I did better than most of the other students.
11	I’d like to show my teachers that I’m smarter than the other students in my classes.
12	Doing better than other students in school is important to me.
	Performance-avoidance goal orientation	Never	Seldom	Sometimes	Often	Always
13	An important reason I do my school work is so that I don’t embarrass myself.
14	The reason I do my school work is so my teachers don’t think I know less than others.
15	The reason I do my work is so others won’t think I’m dumb.
16	One reason I would not participate in class is to avoid looking stupid.
17	One of my main goals is to avoid looking like I can’t do my work.

Adapted from Midgley et al., (1998) into Turkish by Akın and Çetin (2007).

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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