Academic Motivation and Alienation from Study as Predictors of Education Trajectory Choice

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Abstract

A large body of studies on the choice of educational trajectories is aimed at identifying the role of the family, socio-economic status, and place of residence. But the psychological patterns of preferences for educational trajectories have received less attention. Current study is aimed at identifying motivational predictors. The study presents an analysis of data obtained from 1914 schoolchildren studying in 9 classes, living in the urban (952 people) and rural areas (962 people) aged 14 to 16 years (M=15.33, SD=0.49), 57% - girls. As a result of the study, it was found that the orientation towards higher education is determined by both intrinsic and extrinsic motivation. Orientation to receive secondary vocational education is associated with amotivation and alienation from study. Schoolchildren living in rural areas tend to settle down and are more oriented towards education, both secondary vocational and higher.

General Information

Keywords: education trajectory choice; orientation to higher education; orientation to secondary vocational education; academic motivation; alienation from study; settled way of life

Journal rubric: Educational Psychology

Article type: scientific article

DOI: https://doi.org/10.17759/pse.2023280302

Received: 26.01.2023

Accepted:

For citation: Rudnova N.A., Gordeeva T.O., Kornienko D.S., Egorov V.A. Academic Motivation and Alienation from Study as Predictors of Education Trajectory Choice. Psikhologicheskaya nauka i obrazovanie = Psychological Science and Education, 2023. Vol. 28, no. 3, pp. 19–32. DOI: 10.17759/pse.2023280302.

Full text

Introduction

The formation of life plans       is a differentiating feature of early adolescence, however, modern school children face the problem of professional self-determination and choice of educational trajectory            quite early [24], and it is important to identify the factors that influence this choice.

Existing educational paths studies are mainly carried out in a sociological context, specifying the role of the family, socio-economic status, place of residence, etc. [for example, 2; 6], while the factors that reveal the psychological patterns behind the formation of       educational trajectories      preferences receive much less attention.

Despite the fact that a significant number of research papers are devoted to the educational motivation of school children, college and university students [for example, 9; 20; 30],       data on the role of motivational characteristics            in the selection of educational trajectories             is almost absent. This study focuses on identifying motivational predictors of an educational trajectory choice.

Educational trajectories and factors for  their choice

Various psychological and pedagogical approaches reflect the multiplicity of the definition of the term “educational trajectory”       [10]. However, more often, an educational trajectory is understood as a sequence of levels, forms, types and means of learning to obtain certain knowledge and skills that are built in a certain logic over time and in accordance with individual qualities, and this sequence must be implemented to achieve personal professional goals [25].

Modern school children are provided with ample opportunities for building educational trajectories. A child can stay at school until the 11th grade, and then go to an      institution of higher or secondary vocational education, or alternatively after       9th grade go to college, then       continue their studies at a university or start working [4]. A teenager can also choose a place of study - a place of residence, a native or neighboring region, or even another country [15; 32]. Thus, the trajectory of education after school is determined by two factors - the preferred educational level (secondary vocational or higher education) and orientation towards educational migration or a settled way of life.

The choice of educational trajectory       depends on ideological, political, socio-economic and personal factors [2]. If the first two groups of factors determine the educational system’s macro level [11], then socio-economic and personal factors are associated with a particular educational trajectory choice [18; 28].

According to the theories of maintained inequality [22], the choice of educational trajectory       is largely determined by the family’s socioeconomic status and by the place of residence. Thus, school children from families with a higher socio-economic status more often choose the trajectory “11 grades-university”. Students from less prosperous families, as well as rural schools’ graduates, mainly adhere to the trajectory “9 grades - college” [16]. At the same time, school graduates from rural areas tend to move to small and large cities, while school graduates from small and large cities - to the largest cities [4].

Despite the socio-economic factors' leading role, it has been established that motives are also significant in the choice of educational trajectories      [16]. It is known that higher education is associated with social and material motives - school children want to get a profession that will help them to find a job      which will be in demand [3; 34]. In the case of teenagers from rural areas, getting an education should help them move to the city for permanent residence, since there are more career opportunities [14]. The choice in favor of secondary vocational education is more often based on the family’s limited resources [13].

The research results of the school children’s educational trajectories choice peculiarities testify to some of its rationalization, as an orientation towards external factors (successful admission, further employment, etc.). It seems that the inner needs of the teenager’s personality are ignored in the course of this choice. The reason for this may be the researchers’ focus on socio-cultural and economic predictors [1; 7] and insufficient research of psychological factors. Since it was discovered that both the teenager and his/her parents strive for a balance between external and internal factors [5], it is important to identify the motivational factors' role in choosing educational trajectories.

The role of academic motivation and alienation from learning in the choice of educational trajectory

According to the self-determination theory by E. Deci and R. Ryan,      activity motivation is divided into intrinsic motivation, extrinsic motivation, and amotivation as the absence of a desire to be purposefully involved in an activity [8]. Intrinsic motivation is quite homogeneous and is defined by the desire for knowledge, achievement and self-development. The extrinsic motivation types line up as a continuum from the least frustration of the need for autonomy to the greatest: motivation in an activity’s secondary value (identified type), guilt, shame, and pride motivation (introjected type), and external control, reward, and punishment motivation (external type). Therefore, the      opposition between internal (based on interest in the learning activity itself) and external (based on the desire for rewards and incentives or based on avoiding negative consequences) academic motivation, previously present in psychology, is overcome.

A category close to amotivation is alienation from learning, which means experiencing the meaninglessness of the educational process, accompanied by feelings of boredom and dissatisfaction with studying, and leading to avoiding learning and to it     s conscious rejection [17]. The study, which involved a sample of students, showed that alienation is a significant predictor of emotional burnout, which in turn predicts poor academic performance and reduced subjective well-being [27].

International studies [for example, 33] demonstrate that students with educational trajectories      where academic demands are not high, demonstrate greater involvement in learning under external control. Other studies show that involvement in the educational process and conscious academic efforts are closely related to       admission to university [26; 31] and educational mobility [32]. Russian research on academic motivation in the context of educational trajectories is      carried out mainly on separate samples of university and college students. However, it has been established that students studying along the “school-college-university” trajectory have higher intrinsic motivation and independence [14], and students who got into the university under the influence of external factors while learning, demonstrate higher amotivation levels as well as alienation, disappointment in the profession [19].

Based on the the logic of the self-determination theory      and      available data, it can be assumed that internal academic motivation is a significant positive predictor, while amotivation and alienation from learning are significant negative predictors of orientation towards higher education, at the same time amotivation and alienation will be positive predictors for the preference of secondary vocational education     . The intention to stay in one's region (settling down) will be associated with low indicators of both external and internal motivation.

Method

The study was conducted within the All-Russian long-term     project "Growing Together". This paper presents an analysis of data obtained from 1914 school children studying in the 9th grade, aged 14 to 16 years (M=15.33, SD=0.49), 57% are female. Out of these, 962 people live in rural areas of the Republic of Sakha (Yakutia) and 952 people live in the city (Yakutsk). The study was conducted individually. The data collection procedure complies with the ethical standards of the Russian Psychological Society.

The questionnaire, focused on identifying preferred educational trajectories, included statements regarding the orientation towards obtaining a secondary vocational or higher education, as well as regarding the ideas about continuing education in a      hometown (region) i.e. settling down. There were 6 statements in total, which respondents rated on a 5-point Likert scale from 1 (“Disagree”) to 5 (“Agree”). Cronbach's alpha for the scale “Orientation towards secondary vocational education” is 0.78, for the scale “Orientation towards higher education" - 0.68, for the scale “Settling down” - 0.82.

The academic motivation scale (short version) [9] is aimed at identifying the following types of academic motivation: intrinsic cognitive motivation, self-development, introjected, external and amotivation. The questionnaire includes 20 questions that respondents are asked to rate on a 5-point Likert scale from 1 (“Not at all”) to 5 (“Quite appropriate”). Cronbach's alpha for the scales varies from 0.67 (for the Introjected motivation scale) to 0.90 (for the Self-development motivation scale).

The questionnaire of subjective alienation from learning [17] is focused on identifying a person's refusal to implement their own interests and achieve individual goals within educational activities. The scale consists of 16 items, which respondents rate on a 5-point Likert scale from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”). Cronbach's alpha in the present study is 0.92.

Research results

Psychometric indicators of the "Educational trajectories" questionnaire

To confirm the reliability of the obtained data, an analysis of the psychometric indicators of the "Educational trajectories" questionnaire was carried out. Six items of the questionnaire were used to obtain an exploratory factor structure that has good model fit indices: Bartlett's test of sphericity χ²=3071, df(15), p< .001; coefficient of KMO test – 0.54; values ​​of model fit indices are RMSEA = 0.023, TLI = 0.993, AIC = 54.25. The factor structure explains 69.6% of the variance (see Table 1).

Table 1. Factor structure of the "Educational trajectories" questionnaire statements

 

Factors

 

1

2

3

1. After school, I want to continue my studies at a technical school or college and get a secondary vocational education.

После школы я хочу продолжить обучение в училище, техникуме, колледже, получить среднее профессиональное образование

 

0.63

 

2. After school, I want to continue my studies at a university and get a higher education.

После школы я хочу продолжить обучение в университете (институте, академии)

 

 

0.52

3. My parents would like me to continue my studies at a technical school or college and get a secondary vocational education.

Мои родители хотели бы, чтобы я продолжил/-а обучение в училище, техникуме, колледже и получил/-а среднее профессиональное образование

 

0.99

 

4. My parents would like me to continue my studies at a university (institute, academy)     .

Мои родители хотели бы, чтобы я продолжил/-а обучение в университете (институте, академии)

 

 

0.99

5. After graduating, I would like to work in my hometown or home region.

После обучения в университете я бы хотел/-а работать в родном городе, моем регионе

0.69

 

 

6. I would like to study at a university in my hometown or home region.

Я бы хотел/-а учиться в университете в родном городе или моем регионе

0.99

 

 

Explained variance

0.25

0.24

0.21

The first factor included two statements regarding the desire to continue education in a      hometown (home region) and the desire to work in a      hometown (home region). This factor is called “Settling down”. The second factor included statements regarding the prospect of obtaining a secondary vocational education and the support of parents for      this prospect. This factor is called “Orientation towards secondary vocational education”. The third factor contained points regarding the prospects for continuing education at a university and parental support for this decision. The factor is called “Orientation towards higher education”. Further on each factor is considered as a separate scale.

The predictive role of academic motivation and alienation from learning in the choice of educational trajectories      

A correlation analysis with Pearson’s coefficient was run to identify the relations between variables. The place of residence (urban or rural), gender, and age were included in the analysis for control.

Table 2. Correlation analysis results

 

1

2

3

4

5

6

7

8

9

10

11

1. Gender

 

 

 

 

 

 

 

 

 

 

2. Age

-0.05*

 

 

 

 

 

 

 

 

 

3. Place of residence

0.04

0.07**

 

 

 

 

 

 

 

 

4. Orientation towards secondary vocational education

-0.07**

-0.01

-0.15***

 

 

 

 

 

 

 

5. Orientation towards higher education

0.14***

-0.03

-0.06**

-0.06**

 

 

 

 

 

 

6. Settling down

-0.24***

-0.03

-0.13***

0.23***

0.04

 

 

 

 

 

7. Alienation from learning

-0.02

0.02

0.12***

0.05*

-0.09***

-0.08***

 

 

 

 

8. Intrinsic cognitive motivation

-0.04

0.01

-0.15***

0.04

0.27***

0.22***

-0.48***

 

 

 

9. Self-development motivation

-0.10***

0.01

-0.10***

-0.03

0.24***

0.21***

-0.40***

0.81***

 

 

10. Introjected motivation

0.10***

-0.04

-0.03

0.04

0.24***

0.13***

0.08***

0.22***

0.18***

 

11. External motivation

0.06*

-0.04

0.03

0.05*

0.11***

0.05

0.40***

-0.16***

-0.14***

0.59***

12. Amotivation

-0.04

-0.02

0.09***

0.09***

-0.13***

0.03

0.64***

-0.37***

-0.27***

0.12***

0.44***

Note. * p < .05, ** p < .01, *** p < .001 Gender: 1 - male, 2 - female; Place of residence: 1 – rural area, 2 - city.

According to the results, “Orientation towards secondary vocational education” is positively associated with “Settling down” (r = 0.23, p <0.01), “Alienation” (r = 0.05, p <0.05), “External motivation” (r = 0.05 , p <0.05) and “Amotivation” (r = 0.09, p <0.001), negatively with “Orientation towards higher education” (r = -0.06, p <0.01), “Gender” (r = -0, 07, p<0.01), “Place of residence” (r=-0.15, p<0.001). “Orientation towards higher education” is positively associated with “Gender” (r = 0.14, p <0.001), all types of motivation except “Amotivation” (r = -0.13, p <0.001), negatively associated with “Place of residence” (r = -0, 06, p < 0.01) and “Alienation” (r = -0.09, p < 0.001). “Settling down” is negatively associated with “Gender” (r = -0.24, p <0.001), “Place of residence” (r = -0.13, p <0.001), “Alienation” (r = -0.08, p <0.001), positively with “Intrinsic cognitive motivation” (r = 0.22, p < 0.001), “Self-development motivation” (r = 0.21, p < 0.001) and “Introjected motivation” (r = 0.13, p < 0.001). All findings are presented in table. 2.

A hierarchical regression analysis was performed to identify the prognostic role of academic motivation and alienation from learning in the choice of educational trajectories     . The dependent variables were the “Orientation towards secondary vocational education”, “Orientation towards higher education” and “Settling down”.

The motivation and alienation indicators’ contribution was studied in different models, since “Amotivation” and “Alienation” demonstrate high correlation rates (r=0.64, p<0.001) and there is a possibility of reducing the reliability of the analysis result due to the data’s multicollinearity [17]. “Intrinsic cognitive motivation” and “Self-development motivation” indicators also showed a close relationship (r=0.81, p<0.001), in addition, their relationship with indicators of educational trajectories is similar and, according to previous studies, they form a single factor of intrinsic motivation [9]. In this regard, a generalized indicator of intrinsic motivation will be considered in the regression analysis.

“Gender” and “Place of residence” were included in the analysis for control. The “Age” indicator was not considered, since the sample is quite homogeneous based on this criterion, in addition, it did not show significant relationships with the variables under study.

Model 1 includes “Gender” and “Place of residence” as independent variables and is identical for both the motivation indicators’ contribution analysis and as well as the alienation contribution analysis. Model 2.1 in addition to “Gender” and “Place of residence” includes alienation indicators as independent variables, while Model 2.2 - “Gender”, “Place of residence” as well as motivation indicators. The share of explained variance in the considered models is small and varies from 2 to 14%.

Table 3. Correlation analysis results

 

Orientation towards secondary vocational education

Orientation towards higher education

Settling down

 

 

Beta

t

Beta

t

Beta

t

Модель 1

R2 = 0,025

F = 24,28

R2 = 0,02

F = 23,95***

R2 = 0,07

F = 74,35***

Constant

 

33.76***

 

36.96***

 

31.73***

Gender

-.06

-2.63**

0.14

6.35***

-0.23

-10.56***

Place of residence

-.14

-6.35***

-0.07

-3.00**

-0.13

-5.68***

 

 

 

 

 

 

 

Модель 2.1

R2 = 0,03

F = 18,96***

R2 = 0,03

F = 20,36***

R2 = 0,08

F = 53,41***

Constant

 

25.29***

 

31.77***

 

27.38***

Gender

-0.06

-2.56**

0.14

6.28***

-0.23

-10.66***

Place of residence

-0.15

-6.65***

-0.06

-2.56**

-0.12

-5.26***

Alienation from learning

0.06

2.85***

-0.08

-3.59***

-0.07

-3.28***

 

 

 

 

 

 

 

Модель 2.2.

R2 = 0,04

F = 11,66***

R2 = 0,14

F = 50,28***

R2 = 0,13

F = 46,50***

Constant

 

18.35***

 

14.96***

 

11.58***

Gender

-.06

-2.52*

0.14

6.29***

-0.22

-10.27***

Place of residence

-.15

-6.61***

-0.03

-1.24

-0.10

-4.81***

Intrinsic cognitive motivation

.01

0.35

0.22

9.24***

0.21

8.41***

Self-development motivation

.03

1.01

0.12

4.30***

0.09

3.10**

Introjected motivation

.00

.001

0.11

3.65***

0.001

-0.1

External motivation

.10

3.66***

-0.11

-4.56***

0.09

3.67***

Note. * p < .05, ** p < .01, *** p < .001 Gender: 1 - male, 2 - female; Place of residence: 1 – rural area, 2 - city.

According to the results, in all models “Gender” and “Place of residence” make a significant negative contribution to the “Orientation towards secondary vocational education”. A significant positive contribution is made by “Alienation” (Model 2.1) and “Amotivation” (Model 2.2).

“Gender” makes a significant positive contribution to the “Orientation towards higher education” (in all models), while “Place of residence” (Models 1 and 2.1) and “Alienation” (Model 2.1) make a negative contribution. When indicators of academic motivation were included in the model, it was found that “Place of residence” ceases to be a significant predictor (Model 2.2), “Intrinsic cognitive motivation”, “Introjected” and “External motivation” make a significant positive contribution, and “Amotivation” makes a negative one.

“Gender”, “Place of residence” (in all models), “Alienation” (Model 2.1) make a negative contribution to the “Settling down”, while “Intrinsic cognitive motivation”, “Introjected motivation” and “Amotivation” - a positive one (Model 2.2).

Discussion

Based on the results, gender is a significant predictor of the educational trajectory choice. It can be assumed that boys are more likely to be oriented towards secondary vocational education, and girls are more oriented towards higher education. A tendency to settle down is more common among boys. In general, current findings correspond to previous data [6; 21].

The place of residence's negative impact on the choice of secondary vocational or higher education suggests that teenagers from rural areas are more likely than their peers from the city to pursue both educational trajectories, which contradicts the previously identified orientation of rural school graduates mainly towards higher education [23; 6; 29].

Secondary vocational education is preferred by teenagers who are bored at school, do not find satisfaction in educational activities and, ultimately, reject them     , which corresponds to the data on the intention of school children oriented to study in technical schools and colleges to start working as soon as possible [4]. Moreover, the current study results supplement the data on the forced choice of this educational trajectory [16]. It is likely that in the case when a teenager does not see value for himself/herself in gaining knowledge, does not want to be active and makes his/her own choice of an educational trajectory, this choice is made under the influence of external factors (for example, parents).

University education is selected by teenagers who are included in the learning process and have personal goals and an idea of ​​what they are studying for. Indirectly, this is also confirmed by the fact that the inclusion of motivational indicators in the orientation towards higher education excludes the significant role of the place of residence. In other words, if a teenager has a pronounced academic motivation - no matter intrinsic or extrinsic - admission to a university becomes a priority regardless of where they live. These results confirm the data on the significant role of motivation in the choice of educational trajectory      [for example, 16] and contradict the data on the leading contribution of socioeconomic characteristics [22].

Settling down as a teenager's strives to study or stay after graduating in his/her native region is more typical for school children from rural areas, which does not correspond to the available data on trends in educational migration [15]. At the same time, the      desire for a settled life increases with a high amotivation level and decreases with a high level of alienation from learning. It is probable that      amotivation as a lack of interest in learning predicts the desire of a teenager to remain in familiar and comfortable conditions (in his/her home city or home region). While alienation from studies reflects the value loss of studying in a particular school     , it makes a teenager hope that educational migration and continuing education in another place (city or region) will again make the process of acquiring knowledge meaningful. This is partly confirmed by the results of previous studies [32]. Interestingly, intrinsic cognitive and introjected motivation reduces the likelihood of educational migration. It can be assumed that in this case, the desire for knowledge may also be associated with the intention of their practical application in their native region to improve the quality of life there. If a teenager studies out of a sense of duty to significant people, then his/her orientation towards settled life can be explained by his unwillingness to burden his/her family with the additional costs of studying in another city. Although such interpretations of the results are supported by data from previous studies [eg, 12; 4], they still need additional empirical verification.

Conclusion

This study focused on identifying the role of academic motivation as well as on the role of alienation from learning in the choice of educational trajectory     . Despite the fact that the importance of the place of residence as a characteristic of the socio-economic status was confirmed, the leading factor in choosing an educational trajectory can also be academic motivation, if it has high level of expression. Therefore, school children with high intrinsic and extrinsic motivation, regardless of where they live, are oriented toward higher education, while those who are mainly amotivated and/or alienated from learning are going to get secondary vocational education.

The current study results can be used for general career guidance for students of the middle school, as well as for work with teenagers who have high educational motivation, but are confident in the insurmountability of socio-economic barriers when entering a university.

The future in studying the psychological factors of an educational trajectory choice may be to identify individual characteristics (for example, differences in life goals, satisfaction with school and teachers, general psychological well-being) of student groups oriented towards different educational trajectories. In addition, conducting interviews as well as involving parents in future studies will help overcome the limitations of the self-report method used in this study.

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Information About the Authors

Natalia A. Rudnova, PhD in Psychology, Junior Researcher, Federal Scientific Center for Psychological and Interdisciplinary Research, Moscow, Russia, ORCID: https://orcid.org/0000-0003-2063-2892, e-mail: rudnova.na@yandex.ru

Tamara O. Gordeeva, Doctor of Psychology, Professor, Department of Educational Psychology, Faculty of Psychologiy, Lomonosov Moscow State University, Leading Research Fellow, International Laboratory of Positive Psychology of Personality and Motivation, National Research University Higher School of Economics, Moscow, Russia, ORCID: https://orcid.org/0000-0003-3900-8678, e-mail: tamgordeeva@gmail.com

Dmitriy S. Kornienko, Doctor of Psychology, Senior Researcher, Federal Scientific Center for Psychological and Interdisciplinary Research, Moscow, Russia, ORCID: https://orcid.org/0000-0002-6597-264X, e-mail: dscorney@mail.ru

Vladimir A. Egorov, PhD in Physics and Matematics, General Director, Nonprofit organization “Trust Fund of Future Generations in the Republic of Sakha (Yakutia)”, Yakutsk, Russia, ORCID: https://orcid.org/0000-0001-8655-9742, e-mail: vladimir_egorov@mail.ru

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