The Effect of School Absenteeism on the Relationship between Amotivation and Academic Achievement: A Path Analysis

Annotation. This study examined whether school absenteeism has a mediating effect on the relationship between amotivation and academic achievement. The study sample consisted of 350 middle-school students in Turkey. A path analysis was created to test the relationships between the study variables. Results showed that amotivation had both a direct and indirect effect on students’ academic achievement. Absenteeism had a partial mediating effect on the relationship between amotivation and academic achievement.


Introduction
Regular school attendance is an important factor in the development of a student's personality, academic achievement, social and adaptive skills (Gump, 2005). School attendance is a multifaceted structure that includes positive behaviors such as behavioral participation, rule compliance, participation in school-related tasks, and participation in extracurricular activities. Love of school, interest in schoolwork, willingness to learn, adoption of the school culture, and regular school attendance are all characteristics of school and student relationships. Students' cognitive abilities and academic motivation are also influenced by regular school attendance (Archambault et al., 2009;Ricking & Schulze, 2019). Academic motivation is linked to behaviors that encourage students to learn and achieve academic achievement. However, a student's lack of school attendance can lead to inadequate behavioral patterns, low performance, superficial learning, school absenteeism, and even school dropout (Gleason & Dynarski, 2002;Janosz et al., 2008;Suh et al., 2007).
Inadequate school attendance can have a negative impact on learning and academic achievement, as well as future professional, sociological, and economic outcomes (Broadhurst et al., 2005;Kane, 2006;Lehr et al., 2004). Students who do not attend school on a regular basis are more likely to have behavioral issues, such as school alienation and the dropping out (Gottfried, 2014;Johnson, 2005). Individual delinquency and adult economic or social problems may be long-term consequences of dropout (Buitelaar et al., 1994;Hibbett & Fogelman, 1990). Attendance at school is an important core competency for future success, adaptation, well-being, and other factors (Rosenheim et al., 2002). Students who devote enough time to schoolwork and young people who complete secondary education are more likely to have a better life experience in the workplace, and other areas than young people who have little or no academic education. Students who are absent from school or who drop out before graduating, on the other hand, may face a variety of serious problems in adulthood (Kearney, 2016;Rumberger, 2011;US Census Bureau, 2012).
Absenteeism is defined as a deliberate or habitual absence from school, classroom, or campus environment without a valid excuse, other than illness or accident (Teixeira, 2013). Absenteeism is a serious problem area that poses a risk to students' school success, engagement, and graduation (Ansari & Purtell, 2018;Bauer et al., 2018). This leads to low self-esteem, guilt and an increased the likelihood of students dropping out. In many ways, absenteeism is a difficult and complex problem that can manifest itself in a variety of ways. A student may be absent from school entirely or may attend classes for a short or long period of time. It could also take the form of a school day delay, a lesson missed in another way or intentionally abandoned, or early school dismissal (Gottfried, 2009;Kearney, 2016). A variety of physical and psychiatric issues can contribute to frequent absenteeism. Psychiatric conditions associated with problematic school absenteeism may include a variety of factors such as school-related stress, family, peer pressure, school culture, social, and environmental factors, school activities, academic performance, and low achievement (Beekloven & Dekkers, 2005;Kearney, 2008).
School absenteeism begins with a decrease in students' academic interest and progresses to absenteeism by moving away from school, resulting in a decrease in academic achievement. Absenteeism has a negative impact on students' perceptions, attitudes, and behaviors toward school and teachers (Gottfried, 2009;McCoach & Siegel, 2003). Students who are absent from class may fall behind their peers in terms of overall academic achievement (DeSocio et al., 2007;Ford & Sutphen, 1996). When the student returns to the classroom, he or she may fail due to a lack of understanding of the subjects taught. Students who are frequently absent from school have, therefore, fewer opportunities to learn. In fact, students who are absent from school are less successful, because academic achievement is proportional to the amount of time spent at school and in the classroom (Kearney, 2016). Chronic absenteeism (absent for more than 10% of the school year; Kearney & Graczyk, 2014) causes serious problems such as inadequate attention to individual academic needs, low exam grades, lower literacy skills, and drop out (Calderon et al., 2009;Kearney, 2016).
Previous research has revealed that students who missed more school days were accompanied by emotional and social developmental risks as their academic achievement decreases (Eaton et al., 2008;Gottfried, 2010;Lehr et al., 2004;Ricking & Schulze, 2019). Absenteeism increases the likelihood of academic deterioration and academic achievement delays (Gottfried, 2015). Academic deterioration is primarily manifested by school absenteeism, poor academic performance, poor interpersonal relationships, misperception of academic competence, and amotivation, all of which lead to school dropout (Marı et al., 2008). Previous research showed that absenteeism has a negative relationship with academic achievement and can have serious academic consequences for students (Altınkurt, 2008;Bauer et al., 2018;Bostan & Karakaya, 2016;Egger et al., 2003;Elis, 2016;Hunt & Hopho, 2009;Özkan, 2018;Reid, 2011). For example, students who miss more than 10% of the school year may fall behind in their studies academically and lack necessary skills such as self-regulation and independent work (Gottfried, 2014). Aucejo and Romano (2014) found that ten days of absenteeism in the 3 rd -grade in the academic year resulted in a 2.5% decrease in the standard deviation of mathematics test scores among students compared to 8.8% in the 5 th grade. Henry (2007) examined the negative effects of absenteeism in 8th and 10th grade students who were absent from school for at least one day over a four-week period. Henry found that the strongest negative effects of absenteeism were poor test scores and low educational goals. Schwartz et al. (2009) observed that students who spend 12% of their school time absent in an academic year had poor class-performance and tended to be alienated from school.

Concept of Amotivation
Academic motivation plays an important role in students' regular attendance at school. Academic motivation is defined as a student's desire, effort, and persistence in achieving academic achievement. Academic motivation refers to the drive required to complete academic tasks and activities (Hanson et al., 2016;Vallerand et al., 1997). However, amotivation, or a lack of motivation, causes morale and dissatisfaction, as well as a reduction in cognitive productivity and emotional well-being . Self-determination theory (SDT) attempts to explain the dynamic motivations that lead to participation or non-participation in a task . In SDT, there are different types of motivation, each with unique characteristics and dynamics (Ryan & Deci, 2017). This theory assumes that human behavior in any task context can be intrinsically motivated, externally motivated, or amotivated behaviorally. Amotivation is defined as a lack of self-determination towards target behavior, which refers to both intrinsic and extrinsic lack of motivation. Amotivation is a type of motivation that occurs when a person has the least amount of self-efficacy and the least amount of autonomy and internal control over their behavior Ryan & Deci, 2017). It arises as a result of the individual's perception that he or she cannot control potential consequences through any action, or because the individual believes that he or she is incapable of performing the required actions effectively (Ryan & Deci, 2020). Amotivation describes how passive, ineffective, or purposeless an individual is in the context of any given task, or the lack of self-efficacy perceived in the performance of that task (Vansteenkiste et al., 2005). Ryan and Deci (2002) defined that amotivation arises from a lack of satisfaction with the need and occurs when an individual has no intention of participating in a particular activity. Amotivation is negatively correlated with educational outcomes such as low expectation and / or value (Wigfield et al., 2017), poor concentration and boredom in-class (Vallerand et al., 1993), low self-efficacy (Schunk & DiBenedetto, 2016), negative self-esteem (Director & Nuri, 2017), perceived stress related to school, low psycho-social self-preparation (Baker, 2004) and dropping out of school (Baker, 2004;Vallerand et al., 1997). Legault et al. (2006) developed and conceptually confirmed a systematic of the factors that cause general academic amotivation at school. This systematic evidence demonstrates that a lack of ability beliefs skills, a lack of effort beliefs, low values attributed to tasks, and unappealing characteristics of school tasks can lead to a sense of amotivation in students.

The Current Study
The current study examined whether school absenteeism had a mediating effect on the relationship between amotivation and academic achievement among middle school students in Turkey. The reason why absenteeism is identified as a mediator variable is that the amotivation triggered absenteeism (Allen-Meares et al., 2000) and absenteeism negatively affects students' academic achievement (Hoşgorur & Polat, 2015;Khalid, 2017;Onder, 2017;Pehlivan, 2016). In turn absenteeism, a decrease in the academic interest of students and a decrease in school success can be observed. Absenteeism is thought to play a mediating role in the relationship between amotivation and academic achievement in this regard. Although numerous theoretical and empirical studies in the literature have shown that both amotivation and absenteeism are related to academic performance or achievement, this study focused on the effects of amotivation and absenteeism on academic achievement in a sample of middle school students.
To better understand the processes involved in school participation and success in the transition to secondary education, it is critical to understand the effects of amotivation and absenteeism on academic achievement of middle school students. Because middle level education is a critical transition stage that reflects both academic achievement goals and students' competence skills, and because this stage serves as the foundation for students' secondary education level (Fidan & Eren, 2017) this is a performance-oriented period with more pronounced academic self-beliefs. When it comes to their middle level years, most students desire to demonstrate their autonomy and competencies through their behaviors, to engage in self-regulatory skills, to feel functional in success, to control and strengthen in order to think about schooling in terms of their future, and thus to establish themselves in a qualified school in secondary school (Ames, 1990;Karaman et al., 2020;Keating, 1990;Kesici, 2007). Students require more motivation, learning approaches, and academic support to succeed during this period because students may struggle with intrinsic motivation in academic tasks, difficulties interacting with other adolescents, exams for secondary school, and perceived competence and autonomy while performing complex tasks. Sharp drops in motivation can have a negative effect on student behavior, productivity, and academic development (Eccles et al., 1993;Ntoumanis, 2001;Midgley et al., 1995;Wentzel & Wigfield, 1998). When students experience repetitive failures in academic tasks, this leaves them vulnerable to amotivation and despair (Hidi & Harackiewicz, 2000;Reyes & Jason, 1993;Shen et al., 2010). Given that amotivation is characterized by a decrease in students' academic performance in the educational setting (Datu, 2017;Turner et al., 2009) it is expected that this situation will cause serious problems in the transition of middle school students to secondary education and their continuing education life. As a result, investigating the relationships between these variables in a single study that combines the variables of amotivation, absenteeism, and academic achievement can help to better understand the factors that influence middle school students' academic achievement. A better understanding of amotivation is also beneficial in understanding absenteeism and increasing academic achievement. The hypothesis of the model established for the purpose of this study is as follows: Hypothesis: School absenteeism would have a mediating effect on the relationship between amotivation and academic achievement among middle school students.

Research Design and Participants
A cross-sectional relational survey model was used for the current study. In the study, a hypothesis model was developed to investigate the effect of school absenteeism as a mediator or indirect effect on the relationship between amotivation and academic achievement. To investigate the hypothesized relationships between the study variables, the path analysis method was used. The universe of this study consisted of middle school students living in an urban area in Turkey. The study was carried out on a sample drawn from this population. The simple random sampling method was used to collect data from the study universe. Participants consisted of middle school students who were absent from school for at least one day during the second semester in the 2018-2019 school year. As the study aimed to investigate the mediating effect of school absenteeism on the relationship between amotivation and academic achievement, students who were not absent from school were not included. The sample of the study consisted of 350 middle school students from 6th, 7th, and 8th grades, 151 of whom were boys and 199 girls. Students were between 12, and 15 years of age and have an average age of 13.05.

Measures
Academic Amotivation Inventory (AAI) was used to assess the general academic amotivation levels of participants in this study. AAI was developed by Legault et al. (2006) and adapted to Turkish culture by İlter (2019). AAI is a 7-point Likert-type scale (from 1 = does not correspond at all to 7 = corresponds exactly) that includes 16 items. AAI has four items per its four subscales called "ability beliefs", "effort beliefs", "characteristics of the task", and "value placed on the task. Lack of ability beliefs, lack of effort beliefs, unattractive characteristics of the task and low values attributed to the task were conceptualized as complementary aspects of academic amotivation in the AAI Legault et al., 2006). Cronbach's alpha for the subscales of original AAI are α = .89 for the value placed on the task, α = .86 for the ability beliefs, α = .76 for the effort beliefs, and α = .87 for the characteristics of the task (Legault et al., 2006). Cronbach's alpha coefficients of four subscales of AAI-Turkish form were α = .81 for the value placed on the task, α =.75 for the characteristics of the task, α = .77 for the ability beliefs, and α = .72 for the effort beliefs (İlter, 2019). Exploratory factor analysis (EFA) was used to analyze the factor structure of AAI Turkish form. EFA results showed that four subscales of the AAI-Turkish form having eigenvalues higher than 1 and accounted for 52.12% of total item variance. Confirmatory factor analysis showed that 16 items of four factors provided a good fit to the data collected from Turkish middle school sample (χ2 = 1.30, RMSEA = .041, IFI = .95; CFI = .97, GFI = .92, IFI =. 94). In this study, the Cronbach Alpha coefficient of the AAI was calculated as .88. Absenteeism represented the total days that students who were absent from at least one day of school during the second semester in the 2018-2019 school year. These total days represent the combination of both excused and unexcused absences. Students' self-reported absenteeism rates ranged from 1 to 12 days (M = 5.01, SD = 5.28).

Process
A data collection booklet consisting of a personal information form and the AAI was prepared by the researcher (the author) in the study. The researcher personally administered data collection tools to all participants in the classroom settings. He informed participants about the purpose of this study, the criteria for filling in the data collection tools and the estimated duration of participation. During the administration, participants were informed that filling out the data collection booklet was voluntary. In this way, data was collected from a total of 408 students. SPSS 22 and AMOS 22.0 were used to analyze data in this study. Two methods were used for missing data in the measures. First, students who did not respond to 5 or more items in the AAI were excluded from the data set. In the literature, this is a widely accepted common approach to deal with missing data (Creswell, 2002). The data collection booklet for 32 students was removed from the data set and was not included in the analysis. Second, for students with 4 or less missing answers, mean values were assigned to replace the missing values in the items in the AAI (Creswell, 2002;Tabachnick & Fidell, 2007). As a result, 376 students' data were included in the data analysis.

Analysis of Data
Before the path analysis, it was examined whether the data set had a normal distribution. The Mahalanobis distance was used to examine whether any extreme values that showed normality and linearity assumptions were difficult (Büyüköztürk, 2014). The Mahalanobis distance value p for each participant is calculated using the items in the AAI. It was compared to the Chi-square value at the p < .001 level of significance (Tabachnick & Fidell, 2007) and 26 participants who were found to have multivariate extreme values were excluded from the data analysis. As a result, all statistical analyses were performed on data from 350 participants. For the normality assumptions of the study data, the skewness and kurtosis values for all variables were examined. The skewness coefficients for amotivation, absenteeism, and academic achievement were -.1.22, -.97, and -.83 respectively. Kurtosis coefficients were -.94, -.56, and .88 respectively. To investigate the relationships between amotivation, absenteeism, and academic achievement, the Pearson product-moment correlation coefficient was used. Path analysis was used to examine the role of absenteeism as a moderator on the relationship between amotivation and academic achievement. The data fit was evaluated using the following fit indexes: chi square (χ 2 ), GFI, CFI, TLI, and RMSEA. Values greater than .95 indicate very good fits. Also, RMSEA values ≤ 08, and, a non-significant χ 2 (p > .05), and χ 2 ratio below the suggested 2:1 ratio show acceptable model fit (Kline, 2005). The bootstrap method was used to test the indirect and mediating effect of absenteeism on the relationship between amotivation and academic achievement (Preacher & Hayes, 2008). The bootstrapping method evaluates the importance of direct and indirect effects in a proposed model (MacKinnon, 2009). The absence of a zero value between the upper and lower limits of the confidence interval (CI) was used to test the significance of the indirect effect (Hayes, 2013). The level of significance was taken as p= .05 in all statistical analyses.

Preliminary analysis: Correlations Between the Study Variables
The descriptive statistics and correlations between the study variables were examined. The results are shown in Table 1. As shown in Table 1, all variables were significantly correlated with each other. Amotivation was found to be positively correlated with absenteeism (r = .313, p < .001), and negatively correlated with academic achievement (r = -.415, p< .001). Absenteeism was found to be negatively correlated with academic achievement (r = -.352, p < .001).

Measurement Model
A measurement model in which all variables in the hypothesized model were modeled together was tested. First, CFA was used to validate the measurement model that demonstrated the relationships between observed and latent variables. The fit indices of the measurement model demonstrated good model fit (χ2/df = 2.27, CFI = .93, TLI = .93, GFI = .91, RMSEA = .061).

The Mediation Analysis
The mediation analysis procedure developed by Baron and Kenny (1986) was used to determine the mediation effect of absenteeism on the relationships between amotivation and academic achievement. A mediator variable can mediate any relationship in one of two ways: fully or partially. Baron and Kenny (1986) defined that mediation is established when the following conditions are met: (1) independent variable (amotivation) predicts dependent variable (academic achievement), (2) independent variable predicts mediator variable (absenteeism), (3) mediator variable predicts dependent variable, and (4) the effect of the independent variable on the dependent variable is reduced when a mediator variable is included in the model. The bootstrapping method was used to assess the indirect effects of amotivation on academic achievement through absenteeism. To test the indirect effects of amotivation, bias-corrected bootstrapping analysis (Preacher & Hayes, 2008) at 95% confidence interval (CI) by 2000 bootstrap resampling was used. As stated by Preacher and Hayes (2008), if when CIs do not include 0 and are in the expected direction, then the indirect relationship is accepted significantly.

Path Analysis and Bootstrapping
The hypothesized model of this study was tested by using path analysis in AMOS 22 0. Figure 1 shows the path analysis results for the hypotheses model of the study.

Discussion
In this study, it was tested whether school absenteeism had a mediating effect on the relationship between amotivation and academic achievement among middle school students. Results (1) showed that amotivation positively predicted students' absenteeism (2), negatively predicted students' academic achievement (3). Also, absenteeism negatively predicted among students' academic achievement. The mediation analysis showed that school absenteeism had a partial mediation effect on the relationship between amotivation and academic achievement. Amotivation was found to have a direct effect on academic achievement and to have an indirect effect on it through the mediation variable of absenteeism. This finding suggests that, as the general level of amotivation of students increases, the rate of absenteeism also increases; in turn, increasing both levels of amotivation and absenteeism rates significantly reduces academic achievement of students. Multidimensional amotivation was thought to be the reason why it predicted academic achievement both directly and through absenteeism in the study (Pelletier et al., 1999). Based on the SDT, amotivation defines three psychological requirements for individual adaptation and well-being: autonomy, competence, and relevance. These are the keys to psychological resilience, self-control, and self-efficacy, as well as a variety of positive outcomes. However, failure to meet them may result in a lower quality relationship, the perception of inability to perform required tasks, and poor compliance (Levesque et al., 2004). The lack of support for one of the three needs leads the student to amotivation (Deci & Ryan, 1985).
Amotivation is defined in SDT as the degree to which people are passive, ineffective, or aimless in relation to a specific sequence of actions (Ryan & Deci, 2017). Amotivation occurs when a person doubts self-efficacy, is unable to control a certain behavior, loses value in certain behaviors, or feels a lack of effort and capacity beliefs in the achievement of desired behavioral outcomes (Jackson-Kersey & Spray, 2015;Usán et al., 2019). Patrick et al. (1993) stated that amotivation can be expected in students when they feel low self-efficacy about school tasks, Deci and Ryan (2002) stated that the amotivated student would spend very little energy on learning activity, and would even give up the learning task completely. A sense of failure occurs as a result of the student perceiving that she/ he is unable to perform her/his learning task, or that her/his own abilities or efforts are insufficient to achieve her/his goals. This type of amotivation stems from a perceived lack of SDT competence (Ryan & Deci, 2017). Poor ability beliefs lead to low academic performance, low academic self-confidence, and absenteeism. On the other hand, the lack of desire and ability in making the effort required by academic behaviors can also have an impact on academic achievement, withdrawal from the environment is likely to lead to undesired academic behaviors (Legault et al., 2006;Linnenbrink & Pintrich 2002;Patrick et al., 1993). Therefore, when a student considers amotivation as a result of a lack of ability and effort beliefs, she/he spends less time studying. Previous research has shown that students who dropped out or were disconnected from school had little confidence in their academic abilities or describe the self-concept in their academic skills as poor or ambiguous (Balkis, 2018;Corville-Smith et al., 1998;Eccles et al., 1993). In a study examining the reasons for the failure of students who were absent from school conducted by Kearney (2016) found that students did not trust that they could maintain the necessary efforts to complete academic activities. As a result, amotivation due to poor ability beliefs and low effort beliefs is, therefore, a serious risk to academic achievement (Battin-Pearson et al., 2000). It may result in increased absenteeism due to low academic achievement (Jimerson et al., 2002).
Amotivation is also due to perceptions of competence in academic skills or concerns about autonomy; it is also due to lack of interest, relevance and value. This type of amotivation is the result of not valuing an activity (Ryan, 1995). In the Expectation Value Theory, values are defined as the key point in understanding academic behavior. According to this view, individual values placed in a learning task are one of the main determinants of participation in learning and expectation of success (Wigfield & Eccles, 2000). Avoidance behaviors can be observed when students do not have a meaning for themselves, particularly when they cannot make connections in meeting their needs. This can be observed even when the learner can act for behavior and the capacity to strive for behavior (Van-Petegem et al., 2015). In the SDT, it is stated that a student who does not believe that the values attributed to a task will give it any meaning, intrinsic value or gain will not participate in an activity (Boiche & Sarrazin, 2007;Ryan, 1995). Hence, being concerned and valuing are important factors that play a role in influencing behavioral processes and internalizing behavior (Ryan & Deci, 2017). At this point, it is expected that a task at school will be abandoned or neglected by the student by causing the student to be amotivated (Ainley et al., 2002) if the task is not of interesting or stimulating qualities or is perceived as boring, routine or challenging (Deci & Ryan, 2017;Renninger et al., 1992).
Researchers argue that when academic activities do not fit students' self-regulation, attention, and cognitive abilities, this situation will lead to a variety of undesired problems (Bigelow & Zhou, 2001;McEvoy & Welker 2000;Wigfield & Eccles, 1994). Legault et al. (2006) argued that although the majority of motivational deficiencies are due to students, many school practices are not inspiring or engaging enough to motivate students to perform. In this sense, in order to increase school attendance, students must experience the value, or pleasure and interest in school activities. If there is no internal acceptance of the activity, the student cannot integrate the activity with the way in which it is expressed by one's self (Boiche & Sarrazin, 2007;Renninger et al., 1992). Therefore, activities that are incompatible with self-expression are more difficult to sustain, and amotivation may be characteristic of school tasks that are not an expression of one's self or a value (Legault et al., 2006). In the literature, amotivation was found to be associated with poor performance, low engagement, or cognitive disconnection (Breva & Galindo, 2020;Karabıyık, 2020;Hagger & Chatzisarantis, 2008;Ntoumanis et al., 2004;Vallerand et al., 1993), academic anxiety (Weiser & Garibaldi, 2015), poor academic self-perception (Legault et al., 2006), maladaptive academic functioning (Datu et al., 2018), low self-efficacy beliefs (Karaman et al., 2020), absenteeism (Balkis, 2018;Ratelle et al., 2007) and intention to drop out (Balkis, 2018;Legault et al., 2006;Parr & Bonitz, 2015;Vallerand et al., 1997). All these results show that amotivation is a concern for regular school attendance, and academic achievement, and it is an important problem area that should be considered by teachers.

Conclusions
This study is important in that it is the first research to explore the relationships between the variables of amotivation, academic achievement and absenteeism in the sample of middle school students. Findings showed that amotivation acts as a potential source of risk that leads to absenteeism and indirectly reduces academic achievement through absenteeism. In other words, amotivation was found to continue its effect on academic achievement by the meditation of absenteeism. This also shows that school absenteeism has a significant effect on explaining the relationship between amotivation and academic achievement. The results provide a better understanding of the negative effects of amotivation and absenteeism on the students' academic achievement. Findings suggest that increasing the academic achievement of middle school students should not only reduce their absenteeism rates but also their amotivation levels in the educational setting. In order to support the academic achievement of students who are absent from school, first of all, intervention programs based on the reduction of the factors that cause amotivation are needed. Teachers should be encouraged to provide amotivated students more opportunities in the classroom so they are aware of the importance of dealing effectively with the factors that cause amotivation in the school setting. Teachers can increase their academic achievement by increasing their students' beliefs in their academic abilities and capacity for efforts in order to increase academic participation. This is due to the fact teachers have a strong impact on students' perceptions of autonomy and self-efficacy in terms of reducing amotivation.
Researchers suggest that academic interventions could be used to reduce absenteeism, increase engagement with the school activities, and increase students' expectations of achievement for students who are absent from school (Christenson et al., 2008;Suh et al., 2007). For example, Tier 2 one of the Response to Intervention Methods, sets out targeted prevention intervention strategies for students at risk who need additional support (Fuchs & Fuchs, 2006). Tier 2 focuses on increasing student participation and supporting student autonomy. It aims to improve academic and social skills in order to reduce school alienation and encourage participation in school-based practices. The practice can take the form of a mentoring practice based on monitoring and communication to target students' insistence on attending school and the development of academic and other skills (Christenson et al., 2008). The goal of the intervention is to increase the competencies and beliefs of students in their academic skills, as well as their belief in the ability to make an effort. Research may be conducted to identify the factors on the basis of self-determination that leads to amotivation. As confirmed by the model developed in this study, amotivation triggers absenteeism and in turn, academic achievement of students decreases.
Teachers can provide instant constructive feedback to amotivated students, thereby increasing self-efficacy. Alternatively, students may value the ability to strengthen their understanding of learning and to reflect it in teaching practice. Teachers can encourage amotivated students to communicate more clearly in the classroom and to participate in academic activities that demonstrate their skills and capacity for effort. Teachers must create positive learning environments that encourage active learning, reflective practices, and self-motivation. Teachers can plan activities with their students that are specific to their interests and achievement expectations, which can be considered valuable for students in the selection of academic activities. Students' self-efficacy and academic value beliefs can be positively influenced when teachers develop and share positive expectations about their students' ability to perform tasks. Developing students' beliefs about their abilities can help them improve their opportunities for achievement (Schunk & Miller, 2002;Slavin, 2003) and also help them set better achievement goals. When students fail, teachers can increase their students' academic motivation by giving them the opportunity to succeed in various school practices, giving them constructive notifications that they are sufficient in their abilities, that they can do more and be successful if they make an effort (Locke & Latham, 2002). In case of student failure, the teacher can emphasize self-determination variables such as ability perception, autonomy, relevance, and controllable factors. This can keep the student motivated to succeed.

Limitations and Implications for Future Studies
This study had some limitations that should be addressed in future studies. First, it was conducted with students who were absent from school for at least one day in a semester. Future research may provide better findings on the impact of these variables on academic achievement, particularly when chronic absenteeism is taken into account. Second, the use of a small sample size in the study is thought to have an impact on the generalizability of the findings. The findings have limited generalizability to similar cultures and age groups. Future research should focus on larger samples of schools in different classes and regions. Third, the gender, socio-economic status, and grade levels differences in the relationship between the general amotivation and academic achievement of the participants in this study were not examined. Future research should investigate the predictive effects on academic achievement by incorporating data from participants on these variables. Fourth, the total score of the AAI was taken as a basis for measuring participants' overall amotivation levels. Future research should examine in depth the effects of amotivation factors on academic achievement, taking into account the subscales of amotivation.