Journal of English Teaching.
Literature, and Applied Linguistics ISSN 2614-5871 Vol.
No.
Published by English Language Education Department of UMG http://dx.
org/10.
30587/jetlal.
StudentsAo Reading Motivation from a Social Cognitive Perspective Mustika Rahayu Universitas Bandar Lampung Jl.
Zainal Abidin Pagar Alam No.
Labuhan Ratu.
Kedaton.
Kota Bandar Lampung.
Lampung 35142 Rahayumustika599@gmail.
Helta Anggia Universitas Bandar Lampung Jl.
Zainal Abidin Pagar Alam No.
Labuhan Ratu.
Kedaton.
Kota Bandar Lampung.
Lampung 35142 helta@ubl.
Received: 1st February 2026 Accepted: 21st February 2026 Published: 28th February 2026 Abstract This study aims to analyze the structural relationships among environmental factors, personal factors, and behavioral factors in studentsAo reading motivation based on Social Cognitive Theory.
A quantitative research design was employed using Structural Equation Modeling (SEM) to examine both direct and indirect relationships among the variables.
Data were collected through questionnaires administered to eleventh-grade students at SMA Yadika Bandar Lampung to measure environmental support, personal motivation, and reading behavior.
The findings revealed that environmental factors significantly influenced personal factors and reading behavior, while personal factors played a mediating role in strengthening studentsAo reading behavior.
These results provide practical implications for educators to create supportive learning environments and enhance studentsAo self-efficacy in order to improve reading motivation in English as a Foreign Language (EFL) context.
Keywords: EFL, reading motivation, reciprocal determinism, self-efficacy, social cognitive theory Introduction English has evolved into a global language that bridges communication, education, and cultural exchange across Its increasing significance in academic and professional contexts has prompted a surge in individuals striving for English proficiency, particularly in regions where it is taught as a foreign language (Rao, 2.
Among the four language skillsAilistening, speaking, reading, and writingAireading plays a particularly vital role, serving as the foundation for academic success and lifelong learning (Anggia & Habyk, 2.
Despite its importance, fostering reading competence remains a major challenge in English as a Foreign Language (EFL) classroom, where learners often encounter linguistic barriers, limited exposure to authentic texts, and low motivational engagement (Suryani et al.
, 2.
Bandura .
emphasizes self-efficacy as a central concept influencing studentsAo motivation and persistence in academic tasks.
Self-efficacy is the conviction in one's own capacity to carry out certain tasks necessary to get desired Students who have strong self-efficacy are more likely to use the right tactics, stick with challenging texts, and stay engaged over time in reading environments.
Self-efficacy is a powerful predictor of students' motivation, learning behavior, and academic success, as empirical research has repeatedly shown (Zimmerman, 2000.
Schunk & DiBenedetto, 2.
Within this framework, reading motivation can be interpreted as a product of three interrelated components:
Personal factors, such as self-efficacy, interest, and goal orientation, which determine the learnerAos confidence and persistence.
Environmental factors, including teacher support, peer collaboration, and access to resources, which shape external reinforcement.
Behavioral factors, reflected in reading habits and strategy use, which represent the observable outcomes of Journal of English Teaching.
Literature, and Applied Linguistics Vol.
No.
February 2026 Note.
B = Behavior.
PF = Personal Factors.
EF = Environmental Factors Figure 1: Hypothesis model of AuEmpirical Analysis of StudentAos Reading Motivation Model Based on Social Cognitive TheoryAy by Albert Bandura H1: EF has a positive correlation with PF.
B Albert BanduraAos Social Cognitive Theory (SCT) provides a comprehensive framework for understanding learning motivation through the interaction of personal factors, environmental influences, and behavioral outcomes, known as reciprocal determinism (Bandura, 1.
Within this framework, reading motivation can be viewed as the result of interactions among personal factors such as self-efficacy and goal orientation, environmental factors including teacher support and learning resources, and behavioral factors reflected in reading habits and strategy use.
Prior research has investigated reading motivation within EFL contexts.
however, many have concentrated on discrete variables, such as self-efficacy or environmental support, in isolation.
There is still not much empirical research that tests the structural relationships between these factors in a single SCT-based model, especially among Indonesian high school EFL learners.
Consequently, this study seeks to examine the direct and indirect relationships among environmental, personal, and behavioral factors affecting studentsAo reading motivation through Structural Equation Modeling (SEM).
Method This research utilized a quantitative correlational design within the framework of Albert BanduraAos Social Cognitive Theory (SCT) to examine the interrelationships among personal, environmental, and behavioral factors that shape studentsAo reading motivation.
A correlational approach was chosen to identify the direction and strength of relationships among these variables without manipulating them (Creswell & Creswell, 2.
The quantitative method allows for the collection and statistical analysis of numerical data, providing objective insights into how studentsAo beliefs and surroundings influence their reading behavior (Ghanad, 2.
This design is suitable for modeling theoretical constructs using Structural Equation Modeling (SEM), enabling a comprehensive examination of direct and indirect effects among variables.
Participants Purposive sampling selected 120 eleventh-graders from SMA Yadika Bandar Lampung for this study.
Purposive sampling was used to ensure that participants had sufficient experience in learning English reading and could provide relevant responses regarding reading motivation.
English reading activities are regularly taught at the chosen school, making it suitable for EFL motivation research.
SEM requires at least 5 to 10 participants for each estimated parameter (Hair et al.
, 2.
This ensured structural analysis statistical power.
Instruments Two instruments were used in this study:
A Reading Motivation Questionnaire .
easuring Environmental and Personal Factor.
A Reading Behavior Scale The questionnaire consisted of 15 items rated on a five-point Likert scale .
= Strongly Disagree to 5 = Strongly Agre.
The constructs were defined as follows:
C Environmental Factors .
eacher support, peer interaction, family encouragemen.
C Personal Factors .
elf-efficacy, intrinsic motivation, goal orientatio.
C Behavior .
eading frequency, persistence, engagemen.
Journal of English Teaching.
Literature, and Applied Linguistics Vol.
No.
February 2026 The instrument was reviewed by experts and piloted prior to data collection to ensure clarity and content validity.
However, the convergent validity test showed that PF4 and PF5 had low factor loadings .
ess than 0.
Future studies will change or remove these items to improve construct validity.
Clearer operational definitions and confirmatory factor analysis will improve measurement accuracy.
Data Analysis Data were analyzed using Structural Equation Modeling (SEM) to examine the relationships among variables.
Prior to structural analysis, the Rasch Model was employed to assess item quality, reliability, and construct validity.
SEM
analysis involved model specification, goodness-of-fit evaluation, and hypothesis testing to determine direct and indirect effects among environmental, personal, and behavioral factors (Kline, 2.
Findings and Discussion Findings Table 1.
Descriptive statistics of the study construct Variables Mean Environmental Factors Personal Factors Behavior Table 1 presents the descriptive statistics of the study constructs.
Behavior showed the highest mean score .
followed by Personal Factors .
and Environmental Factors .
The standard deviation values indicate moderate variability across constructs, suggesting an acceptable distribution of responses for SEM analysis.
Table 2.
Convergent validity of the questionnaire construct
Latent Variables Item
Factor
Loading Environmental Factors EF1
EF 2
EF 3
EF 4
EF 5
Personal Factors PF1
PF 2
PF 3
PF 4
PF 5
Behavior
Alpha
AVE
Journal of English Teaching.
Literature, and Applied Linguistics Vol.
No.
February 2026 The table above shows the results of convergent validity testing for the questionnaire constructs, including Environmental Factors.
Personal Factors, and Behavior.
Overall, the three constructs demonstrate acceptable levels of reliability, with Composite Reliability (CR) values above 0.
70 for all variables 0.
738 for Environmental Factors, 0.
724 for Personal Factors, and 0.
785 for Behavior.
The CronbachAos Alpha values also show internal consistency, although Personal Factors .
and Behavior .
are slightly below the ideal threshold of 0.
70, they are still considered acceptable for early-stage research.
However, the Average Variance Extracted (AVE) values for all three constructs are below the recommended cutoff 50, with Environmental Factors at 0.
Personal Factors at 0.
445, and Behavior at 0.
These values indicate that the items for each construct explain less than 50% of the variance, which suggests weak convergent validity.
Looking at the factor loadings, most items have acceptable values above 0.
5, but there are some weak items particularly EF1 .
PF4 .
, and PF5 .
which contribute less to their respective constructs.
These items may need to be revised or removed to improve the overall validity of the instrument.
These findings indicate acceptable reliability but limited convergent validity, requiring refinement of weak indicators in future research.
Table 3.
Discriminant validity of the questionnaire Variables The table presents the correlation values among the three study variables: Environmental Factors (EF).
Personal Factors (PF), and Behavior (B).
The correlation between Environmental Factors and Personal Factors is 0.
950, indicating a very strong positive relationship.
The correlation between Environmental Factors and Behavior is 1.
008, and between Personal Factors and Behavior is 1.
257, both of which are unusually high exceeding 1.
0, which is not common or acceptable in correlation analysis.
These extremely high values may indicate a multicollinearity issue, meaning that the variables are too closely related and may overlap in what they are measuring.
It could also suggest potential problems with the measurement model or data In conclusion, while the data show strong relationships among the variables, the unusually high correlations especially values above 1 should be carefully examined and addressed before further analysis is conducted.
Table 4.
The results from the hypothesis test
Path
Estimate t-value p-value Result
EF -> B
Supported EF -> PF Supported PF -> B Supported EF -> PF -> B Supported The table shows that all the relationships between the variables are significant and supported.
Environmental Factors (EF) have a strong effect on Personal Factors (PF), with a high estimate of 0.
639, meaning that a better environment helps improve studentsAo motivation and interest.
Personal Factors also strongly influence Behavior (B), with an estimate of 0.
showing that motivated students tend to show better learning behavior.
Environmental Factors directly affect Behavior as well, with a smaller but still significant estimate of 0.
This means that the environment alone can influence how students behave in learning.
Additionally, there is an indirect effect from EF to B through PF, with a value of 0.
This shows that the environment also influences behavior through personal In short, a good environment helps improve motivation, and motivated students show better behavior.
The environment affects behavior both directly and indirectly through personal factors.
Notably, the indirect effect (EF Ie PF Ie B) was stronger than the direct effect of EF Ie B, reinforcing the mediating role of Personal Factors.
Journal of English Teaching.
Literature, and Applied Linguistics Vol.
No.
February 2026 Figure 2.
The standardized relationship between the factors Discussion The results of this study are in line with other studies that showed a substantial correlation between reading behavior, internal motivation, and learning settings.
Students' reading enthusiasm and engagement are greatly increased by supportive classroom methods, according to Guthrie and Klauda .
In a similar vein, motivated readers exhibit greater perseverance and deeper cognitive participation in reading activities, according to Schiefele et al.
The current results that environmental support boosts individual motivation, which in turn encourages good reading behavior, are supported by this research.
This study aims to examine the structural relationships among Environmental Factors.
Personal Factors, and Behavior in shaping studentsAo reading motivation, grounded in BanduraAos Social Cognitive Theory (SCT).
The findings demonstrate that studentsAo reading behavior is not influenced by a single factor, but rather by the dynamic interaction between external learning environments and internal motivational processes.
The results of the Structural Equation Modeling (SEM) analysis provide empirical support for SCTAos core principle of reciprocal determinism, which posits that personal, environmental, and behavioral factors continuously influence one another.
The findings indicate that Environmental Factors have a significant and positive effect on Personal Factors, as shown by a strong path coefficient.
This result suggests that supportive learning environments, such as teacher encouragement, classroom atmosphere, peer interaction, and access to learning resources, play a crucial role in strengthening studentsAo internal motivation, self-efficacy, and goal orientation.
This aligns with BanduraAos view that environmental conditions can shape learnersAo beliefs about their own capabilities, which in turn affects their engagement in learning activities.
When students perceive their environment as supportive, they are more likely to develop confidence and motivation toward reading tasks.
Furthermore.
Personal Factors were found to significantly influence studentsAo Behavior, with a path coefficient of 637 .
< 0.
This finding confirms that studentsAo beliefs, intrinsic motivation, and self-regulation are key determinants of their learning behavior.
Students who believe in their reading ability and possess strong internal motivation tend to engage more consistently in reading activities.
This supports previous research suggesting that self-efficacy and intrinsic motivation are strong predictors of academic engagement and persistence, particularly in language learning contexts.
In addition to direct effects, the study revealed a significant mediating effect of Personal Factors on the relationship between Environmental Factors and Behavior ( = 0.
407, p < 0.
This indicates that while environmental support is essential, it does not directly translate into behavioral engagement unless it is internalized by students.
In other words, a positive environment enhances studentsAo internal motivation, which then leads to improved reading behavior.
This finding emphasizes the importance of addressing both external and internal dimensions of motivation, as environmental support alone may be insufficient without fostering studentsAo self-beliefs and autonomy.
Despite the strong support for the structural relationships, the study also identified several measurement model The convergent validity analysis revealed that the Average Variance Extracted (AVE) values for Environmental Factors.
Personal Factors, and Behavior were below the recommended threshold of 0.
This suggests that the constructs did not fully capture the variance of their respective indicators.
Additionally, the discriminant validity results showed excessively high correlations among the constructs, indicating potential conceptual overlap or redundancy in questionnaire items.
These issues suggest that future studies should refine the measurement instruments by revising or removing weak items and ensuring clearer distinctions among constructs.
Journal of English Teaching.
Literature, and Applied Linguistics Vol.
No.
February 2026 Overall, this study confirms the applicability of Social Cognitive Theory in explaining studentsAo reading motivation within the EFL context.
The findings highlight the critical role of both Environmental and Personal Factors in shaping studentsAo reading behavior, with Personal Factors acting as a key mediator.
From a pedagogical perspective, the results suggest that teachers should not only create supportive learning environments but also actively foster studentsAo self-efficacy and intrinsic motivation to promote sustained reading engagement.
Although the study faces measurement limitations, it provides valuable insights into the complex mechanisms underlying reading motivation and offers a foundation for future research and instructional improvement in EFL classrooms.
Conclusion This study investigated the structural relationships among Environmental Factors.
Personal Factors, and Behavior in studentsAo reading motivation based on BanduraAos Social Cognitive Theory.
The findings indicate that both Environmental and Personal Factors significantly influence studentsAo reading behavior, either directly or indirectly, with Personal Factors functioning as a key mediating variable.
A supportive learning environment was shown to strengthen studentsAo internal motivation and self-beliefs, which in turn promoted more active and consistent reading behavior.
The results further demonstrate that students with higher self-efficacy and intrinsic motivation are more likely to engage positively in reading These findings confirm the interconnected nature of environmental support, internal motivation, and learning behavior as proposed in Social Cognitive Theory.
Although the measurement model revealed certain limitations, particularly related to convergent and discriminant validity, the overall structural model was strongly supported by the hypothesis testing.
Teachers are encouraged to integrate motivational support strategies alongside structured reading instruction to promote sustained engagement.
References