247
IJNI: International Journal of Nusantara Islam Vol.
No.
: 247-260
DOI: https://doi.
org/10.
15575/ijni.
ISSN : 2355-651X
Work Environment.
Motivation, and Tutor Performance: Job
Satisfaction as Mediator in Language Course Institutions Arifin,1* Dodi Wirawan Irawanto,2 Margono3
1,2,3
Universitas Brawijaya.
Malang.
Indonesia * Corresponding Author.
Email: roninugraha@iaipibandung.
Received: July 24, 2025.
Revised: December 28, 2025.
Accepted: December 31, 2025.
Published: January 15, 2026 Abstract: This quantitative investigation examines the impact of workplace conditions and motivation on tutor performance, incorporating job satisfaction as a mediating factor.
Data was gathered via questionnaires distributed to tutors across 10 Training and Course Institutions (LKP) in Kampung Inggris.
Pare.
Kediri.
Indonesia.
From a total population of 185 tutors, 165 completed surveys were returned and analyzed.
Researchers employed a non-probability sampling strategy, specifically judgmental purposive sampling.
Analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM).
The results demonstrate statistically significant positive effects: both the work environment and work motivation directly enhance tutor performance and also have a positive influence on job satisfaction.
Furthermore, job satisfaction itself exerts a significant positive effect on performance.
Crucially, mediation analysis confirms that job satisfaction partially mediates the relationship between the work environment and work motivation, and both of these factors influence tutor performance.
These findings offer valuable insights for institutional enhancement strategies.
Keywords: job satisfaction.
tutor performance.
work environment.
work motivation Introduction English proficiency stands as a critical global competency, enabling access to education, economic opportunities, and cross-cultural collaboration.
However.
Indonesia ranks alarmingly low .
th out of 113 nation.
in the 2023 English Proficiency Index (EF Reports, 2.
, signaling an urgent need for skill enhancement.
Non-formal education institutions (Lembaga Kursus dan Pelatihan/LKP) have emerged as vital solutions, with Kampung Inggris Pare serving as IndonesiaAos largest language-learning hub, attracting over 40,000 learners annually (Mukhroji et al.
, 2.
This ecosystem generates significant economic value, circulating Rp 3.
9Ae11.
2 billion monthly and empowering local communities through tourism, homestays, and small businesses (Mualifah & Roekminiati, 2018.
Wawan & Surjono, 2.
Despite this success.
LKPs in Kampung Inggris face systemic challenges: 60% fail to meet IndonesiaAos Eight National Standards for Non-Formal Education, including tutor qualifications and infrastructure (Alexandro, 2.
Tutor performance is further hindered by dual roles, background-job mismatches, low compensation, and declining professionalism, as evidenced by tardiness, absenteeism, and reduced teaching enthusiasm (Fahriyansyah & Muhammad, 2.
Prior studies reveal inconsistent findings on the impact of work environment and motivation on performance.
While Khabri et al .
and Kusumastuti et al .
(Kusumastuti et al.
, 2.
confirm positive effects.
Anggraini .
and Citriadin et al .
report non-significant results.
Similarly, motivationAos influence varies across contexts (Gusriani et al.
, 2022.
Wahyudi et al.
Arifin et al.
/ Work Environment.
Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
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: 247-260
Crucially, job satisfactionAos mediating role remains underexplored in non-formal education, particularly in unique settings like Kampung Inggris, where tutors navigate multicultural classrooms, flexible curricula, and seasonal workloads.
This gap is compounded by the absence of studies examining how environment and motivation jointly shape tutor performance through satisfaction, a nexus vital for sustaining LKP competitiveness.
This study addresses these gaps by analyzing: .
the direct effects of work environment and motivation on tutor performance.
their indirect effects mediated by job satisfaction.
practical strategies for LKPs.
Using quantitative data from 165 tutors across 10 institutions, we test a novel mediation model integrating Self-Determination Theory .
ntrinsic/extrinsic motivatio.
and Job Characteristics Theory .
nvironment-satisfaction linkag.
Theoretically, this resolves contradictions in prior literature while extending human resource frameworks to non-formal Practically, findings will equip LKPs with evidence-based policies to enhance tutor retention, pedagogical innovation, and institutional resilience.
This research offers tripartite contributions.
Theoretically, it validates job satisfaction as a full mediator in non-formal education, reconciling inconsistent past findings through structural equation modeling (SEM-PLS).
For practitioners, it provides actionable levers: optimizing physical environments .
, noise-controlled classroom.
, fostering intrinsic motivation .
, professional autonom.
, and redesigning reward systems.
Policy-wise, it advocates integrating IndonesiaAos National Education Standards into LKP accreditation to elevate tutor welfare and program quality.
Ultimately, by linking tutor performance to socioeconomic sustainability, this study positions Kampung Inggris as a replicable model for global edutourism entrepreneurship Literature review The work environment encompasses the social, psychological, and physical conditions within an organization that influence employee task execution (Ayunasrah & Diana, 2.
It includes both physical elements .
, lighting, temperature, workspace desig.
and non-physical aspects .
interpersonal relationships, leadership suppor.
Key factors affecting this environment, as identified by Aldridge and Fraser .
, include leadership quality, staff collaboration, resource adequacy, autonomy, goal alignment, and work pressure.
In educational contexts, indicators such as collaboration among tutors, student relations, resource availability, decision-making involvement, and openness to instructional innovation are critical for fostering a conducive setting (Burden & Fraser, 1994.
Johnson et al.
, 2.
Work motivation is defined as the internal drive or enthusiasm that propels individuals to exert effort toward achieving organizational goals (Nur Adinda et al.
, 2.
It arises from personal needs and desires, directing and sustaining goal-oriented behaviors (Wang et al.
, 2.
Layek and Koodamara .
categorize motivation into intrinsic .
riven by personal fulfillment, autonomy, and competenc.
and extrinsic .
nfluenced by external rewards, recognition, and job securit.
For tutors, motivation is measured through intrinsic enjoyment of teaching, alignment of work with personal values .
dentified regulatio.
, and external pressures like financial incentives or job stability (Fernet et al.
, 2008.
Beardsley et al.
, 2.
Job satisfaction reflects employees' affective and cognitive evaluations of their work experiences, encompassing feelings of fulfillment and contentment (Pepe et al.
, 2017.
Samancioglu et al.
, 2.
It manifests in four dimensions: cognitive .
valuative judgment of job component.
, affective .
motional response.
, physical .
omfort with work condition.
, and mental .
sychological well-bein.
(Liu et al.
, 2.
Factors influencing satisfaction include work environment quality, compensation, colleague relationships, recognition, and career development opportunities (Ahiri et al.
, 2.
In educational settings, it is assessed through satisfaction with the workplace environment and professional fulfillment derived from the teaching role (OECD.
Liu et al.
, 2.
Tutor performance denotes the measurable outcomes of educators' work in terms of quality, quantity, and effectiveness in fulfilling responsibilities (Saputra et al.
, 2.
It involves creating effective learning environments, executing instructional tasks, and evaluating student progress (Bahriansyah & Mukhtar, 2.
Performance is shaped by internal factors .
, skills, motivation, work ethi.
and external factors .
, institutional resources, leadership, and family suppor.
(Uy Arifin et al.
/ Work Environment.
Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
No.
: 247-260
et al.
, 2.
Indicators include standards-based planning and instruction, cultivating conducive learning conditions, and upholding professional responsibilities such as continuous selfimprovement and ethical conduct (Marzano, 2017.
Long et al.
, 2024.
Mydin et al.
, 2.
Figure 1.
Conceptual Framework Drawing on established organisational behaviour theories, the research framework posits that both contextual and psychological factors directly and indirectly shape educator Environmental psychology and job characteristics theory underpin H1 and H3, as physical/social workplace conditions .
, resource adequacy, collaborative cultur.
are empirically linked to enhanced performance (Khabri et al.
, 2.
and psychological fulfillment (Meku Lelo, 2.
Simultaneously, self-determination theory informs H2 and H4, where intrinsic/extrinsic motivational drivers .
, autonomy, recognitio.
demonstrably boost output (Wahyudi et al.
, 2.
and satisfaction (Pancasila et al.
, 2.
Affective events theory further substantiates H5 and the mediation hypotheses (H6AeH.
, as job satisfaction Ae reflecting emotional responses to work experiences Ae consistently translates to higher performance (Silvia Sofyan et al.
, 2.
and mediates environment/motivation effects (Fitriani & Suriansyah, 2022.
Qomariah et al.
, 2.
H1.
A supportive work environment has a positive and significant impact on tutor H2.
Higher levels of work motivation significantly improve tutor performance outcomes.
H3.
The quality of the work environment exerts a positive and significant influence on tutor job satisfaction.
H4.
Work motivation demonstrates a statistically significant positive effect on job satisfaction among tutors.
H5.
Increased job satisfaction significantly contributes to improved tutor performance.
H6.
Job satisfaction serves as a mediating variable in the relationship between work environment and tutor performance.
H7.
The influence of work motivation on tutor performance is partially mediated by job Method This study employs an explanatory research design with a quantitative approach to test, elucidate, and confirm theoretical relationships within the domain of organizational behavior (Cresswell.
Quantitative methodology systematically measures variables and tests hypotheses using numerically scaled, calculable data to ensure objectivity and statistical rigor.
The specific aim is to analyze both the direct and indirect effects .
ediated by job satisfactio.
of work environment and work motivation on tutor performance at Kampung Inggris.
Pare Kediri.
Indonesia.
By integrating path analysis via Structural Equation Modeling (SEM-PLS), the design enables robust examination of causal pathways while contextualizing findings within the unique socio-educational framework of non-formal language institutions.
Arifin et al.
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Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
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The work environment encompasses the social, psychological, and physical conditions within an organization that directly impact employees' ability to execute tasks effectively (Ayunasrah & Rahma, 2.
In educational settings, this includes both tangible elements like facilities, workspace design, and resource availability, and intangible aspects such as collegial support and leadership dynamics (Fitriani & Ahmad, 2.
Operationalized through the School Level Environment Questionnaire (SLEQ) (Burden & and Fraser, 1994.
Johnson et al.
, 2.
, this variable is measured via five key indicators: Collaboration .
oordination among tutors and teambased program desig.
Student Relations .
tudent behavior, respect for staff, and learning motivatio.
School Resources .
dequacy of teaching tools and accessibilit.
Decision Making .
utor involvement in institutional choice.
, and Instructional Innovation .
penness to novel pedagogical approache.
Work motivation represents the internal drive that energizes individuals to exert sustained effort toward organizational goals through cognitive and behavioral processes (Rezkiawan, 2016.
Zhang & Ye, 2.
It integrates intrinsic elements .
, deriving joy from teachin.
and extrinsic factors .
, salary or career securit.
(Adinda et al.
, 2.
Assessed using the Work Tasks Motivation Scale for Teachers (WTMST) (Beardsley et al.
, 2021.
Fernet et al.
, 2.
, this variable comprises three dimensions: Intrinsic Motivation .
ulfillment from teaching itsel.
Identified Regulation .
lignment of work with personal value.
, and External Regulation .
ngagement driven by rewards or avoidance of penaltie.
Job satisfaction reflects an employeeAos affective and cognitive evaluation of their profession and workplace, characterized by emotional fulfillment and perceived alignment between personal and organizational values (Samancioglu et al.
, 2020.
Sothinathan et al.
, 2.
It captures both contentment with immediate work conditions and broader career commitment (Pepe et al.
, 2.
Grounded in the OECDAos Teaching and Learning International Survey (TALIS 2.
(Liu et al.
OECD, 2.
, it is evaluated through two indicators: Work Environment Satisfaction .
njoyment of institutional conditions despite potential mobilit.
and Professional Satisfaction .
erception of teachingAos net benefits relative to alternative career.
Tutor performance refers to the measurable quality and efficiency of educational outcomes achieved through pedagogical responsibilities, including lesson delivery, student development, and curriculum implementation (Bahriansyah & Mukhtar, 2020.
Saputra et al.
, 2.
It synthesizes technical competence, adaptability, and ethical commitment (Citriadin et al.
, 2.
Modeled via the Marzano Teacher Evaluation Framework (Long et al.
, 2024.
Marzano, 2017.
Mydin et al.
, performance is assessed across four domains: Standards-Based Planning .
esigning curriculum-aligned learning strategie.
Standards-Based Instruction .
mplementing adaptive teaching method.
Conditions for Learning .
ostering safe, resource-rich classroom.
, and Professional Responsibilities .
ursuing continuous improvement and collaborative ethic.
Variable Work Environment Work Motivation Tutor Table 1.
Variable Operational Definitions Indicator Source (Burden & and Fraser.
Collaboration Student.
Relations.
School Resources.
Instructional 1994.
Johnson et al.
Innovation.
Decision Making Intrinsic Motivation.
Identified Regulation.
External (Beardsley et al.
, 2021.
for Regulation Fernet et al.
, 2.
Job Satisfaction The work environment and Job Satisfaction and The (Liu et al.
of Tutor professional satisfaction OECD, 2.
Tutor Performance Standards-based Planning.
Standards-based.
Instruction Conditions for Learning.
Professional Responsibilities (Long et al.
, 2024.
Marzano, 2017.
Mydin et al.
, 2.
Source: Processed Data .
Arifin et al.
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: 247-260
This study targeted a population of 185 tutors from 10 prominent Language Training Institutions (LKP) in Kampung Inggris.
Pare.
Kediri, selected for their role as IndonesiaAos largest non-formal language education hubs.
Tutors were purposively sampled based on strict criteria: Ou2 years of teaching experience and active involvement in LKPs to ensure contextual relevance and comprehensive insights into work environment, motivation, and performance Collaboration with Forum Kampung Bahasa (FKB) identified representative institutions .
Mahesa Institute.
Kresna Institut.
, with 165 valid questionnaires retained .
2% response rat.
after accounting for logistical constraints and incomplete submissions.
Judgmental purposive sampling prioritized ecological validity over randomization, aligning the sample with Kampung InggrisAos unique pedagogical ecosystem while maintaining statistical This study utilized a triangulated approach to data collection, integrating observation, literature review, and structured questionnaires to ensure methodological rigor.
First, systematic observationAiinvolving planned monitoring, recording, and interpretation of tutor behaviors and workplace interactionsAiwas conducted to contextualize theoretical variables within Kampung InggrisAos unique educational setting (Sekaran & Bougie, 2.
Second, a comprehensive literature review synthesized foundational insights from academic journals, books, and institutional documents to refine measurement constructs and validate research Third, self-administered paper-and-pencil questionnaires featuring predefined Likert-scale items (Sekaran & Bougie, 2.
were distributed to all 185 tutors across ten language institutions in Kampung Inggris.
Kediri, enabling quantitative assessment of work environment, motivation, job satisfaction, and performance variables.
This multi -method strategy balanced empirical depth with scalability while aligning with quantitative explanatory This research uses several data analysis techniques, including the following:
Descriptive Statistical Analysis.
Descriptive statistics summarize and present collected data to reveal patterns and characteristics of the study's variables (Sekaran & Bougie.
This method enables researchers to: .
understand group dynamics in specific contexts, .
systematically analyze situational aspects, .
generate ideas for further investigation, and .
support practical decisions .
, resource allocation or workfl ow In this study, it quantifies central tendencies and dispersions of work environment, motivation, job satisfaction, and tutor performance variables.
Inferential Statistical Analysis.
Inferential methods are employed to evaluate hypotheses and assess model validity through the application of Partial Least Squares Structural Equation Modeling (PLS-SEM) , a variance-oriented technique selected for its adaptability across varying data types and reduced reliance on strict assumptions (Ghozali & Hengky.
PLS-SEM excels in: .
handling reflective/formative indicators, .
exploring latent variable relationships, and .
supporting explanatory, predictive, and confirmatory Implemented via SmartPLS 4.
0, it examines causal pathways between independent .
ork environment, motivatio.
, mediating .
ob satisfactio.
, and dependent .
utor performanc.
Measurement Model (Outer Mode.
Evaluation.
The outer model assesses validity and reliability through three criteria: .
Convergent Validity: Indicators are valid if factor loadings exceed 0.
60Ae0.
50 for nascent theorie.
and are statistically significant .
statistic > 1.
AVE > 0.
(Ghozali & Hengky, 2.
Discriminant Validity:
Established when .
indicator loadings are higher on their assigned construct than others and .
the square root of AVE exceeds inter-construct correlations.
Composite Reliability: Internal consistency is confirmed if composite reliability and CronbachAos alpha values exceed 0.
Structural Model (Inner Mode.
Evaluation.
The inner model tests causal hypotheses and predictive power using: .
RA: Measures exogenous variablesAo influence on endogenous constructs .
25 = weak, 0.
50 = moderate, 0.
75 = stron.
(Jianlong et al.
, 2015.
Shakhim & Mohamed, 2.
QA: Evaluates model predictive relevance .
02 = weak, 0.
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Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
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moderate, 0.
35 = stron.
GoF: Assesses overall model fit .
10 = small, 0.
medium, 0.
36 = larg.
, where higher values .
loser to .
indicate superior accuracy (Ghozali & Latan, 2.
Path coefficients () and t-statistics (>1.
determine hypothesis Results Respondent Characteristics The study's respondent profile underscores Kampung InggrisAos distinct educational ecosystem, characterized by a predominance of young .
% aged 20Ae.
, female .
%), and highly educated tutors .
% bachelorAos degree holder.
This demographic concentration reflects the sectorAos structural reliance on early-career professionals whose adaptability and academic training enable immediate pedagogical effectiveness, minimizing onboarding needs while aligning with the dynamic, immersive teaching methods central to Kampung InggrisAos model.
Institutionally.
Kresna InstituteAos prominence .
% of tutor.
highlights its legacy as a pioneer, while newer entities like Markaz Arabiyah .
%) operate with leaner teams.
Critically, 95.
5% of tutors possess O10 years of tenure, indicating high industry turnover that balances cost efficiency against potential experience gaps, despite sustained performance contributions from the minority .
with 11Ae25 yearsAo service.
Collectively, these patterns reveal a workforce optimized for innovation but facing retention challenges inherent to youth-centric roles.
Figure 2.
Loading Factor Value of 36 Valid Research Items The modified model analysis based on Figure 2 confirms that all 36 research items demonstrate robust convergent validity, with loading factors consistently exceeding the 0.
7 threshold.
This empirical validation indicates that each indicator strongly and reliably represents its underlying constructAiwork environment, work motivation, job satisfaction, and tutor performanceAifulfilling critical psychometric standards for instrument quality.
The high loading values reflect statistically significant contributions of individual items to their respective latent variables, verifying the measurement toolAos rigor and appropriateness for capturing targeted phenomena.
Consequently, these validated instruments enhance the overall credibility of research outcomes, providing a trustworthy foundation for evidence-based decision-making and future policy formulation in educational management contexts.
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Table 2.
Convergent Validity Test Loading Variables Item Factor LK1.
0,800
LK1.
0,763
LK1.
0,809
LK1.
0,704
LK2.
0,750
Work Environment (LK) LK2.
0,787
LK3.
0,729
LK3.
0,830
LK4.
0,785
LK5.
0,763
MK1.
1 0,778
MK1.
2 0,844
Work Motivation of Tutors MK2.
1 0,837
(MK)
MK2.
2 0,723
MK3.
1 0,741
MK321 0,854
KT1.
0,776
KT1.
0,838
KT1.
0,818
KT2.
0,830
KT2.
0,739
KT2.
0,784
KT3.
0,801
KT3.
0,803
Tutor Performance (KT) KT3.
0,807
KT3.
0,712
KT3.
0,774
KT3.
0,815
KT3.
0,808
KT4.
0,787
KT4.
0,796
KT4.
0,818
KK1.
0,824
KK1.
0,838
Job Satisfaction (KK) KK2.
0,842
KK2.
0,848
Source: Processed Data, 2025 Note Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Table 2 demonstrates that both CronbachAos alpha and composite reliability coefficients exceed 70 for all constructsAiwork environment, work motivation, job satisfaction, and tutor performance.
This confirms the internal consistency and reliability of all study variables.
Consequently, the measurement instruments exhibit robust psychometric properties, indicating their suitability for rigorous analysis and future research applications.
Variables Work Environment Work Motivation Table 3.
Reliability Test Result Composite reliability Composite reliability Cronbach's alpha .
0,925 0,926 0,937 0,885 0,893 0,913 Arifin et al.
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Tutor Performance Job Satisfaction 0,961 0,961 0,965 0,859 0,860 0,904 Source: Processed Data, 2025 The coefficient of determination (RA) quantifies the proportion of variance in endogenous variables that is statistically explained by exogenous variables within a research model.
Table 4.
Result of the Coefficient of Determination (R.
Variables R-square R-square adjusted Job Satisfaction 0,698 0,692 Tutor Performance 0,461 0,454 Source: Processed Data, 2025 Analysis indicates an RA value of 0.
698 and adjusted RA of 0.
692 for tutor performance, signifying that the structural model accounts for approximately 69.
8% of the variance in this endogenous variable through its predictor constructs.
Thus, 30.
2% of the variability in tutor performance is influenced by other factors outside of this model.
The slightly lower adjusted R-square value .
indicates that this model also takes into account the number of variables used, and still shows that the model has a good fit.
For the job satisfaction variable, the R-square value is 0.
461, with an adjusted R-square of These results indicate that the model accounts for approximately 46.
1% of the observed variance in job satisfaction, implying that 53.
9% of its variability stems from factors beyond the current model's scope.
While lower than the variance explained for tutor performance, the adjusted RA value of 0.
454 nevertheless demonstrates adequate explanatory power for the job satisfaction To assess the model's capacity to anticipate the dependent variable, predictive relevance is Below is the calculation for the QA value ycE 2 = 1 Oe .
Oe ycI 2 .
Oe ycI 2 .
ycE = 1 Oe .
Oe 0.
Oe 0.
ycE 2 = 1 Oe .
ycE 2 = 1 Oe 0.
ycE 2 = 0.
As shown in the calculations, the modelAos QA statistic is 83.
This suggests that 83.
7% of the variance in the dependent variable is accounted for by the work environment, work motivation, and job satisfaction, with the remaining 16.
3% attributed to external factors not included in the study.
The goodness of fit index serves as a measure of a modelAos accuracy across both the inner and outer In partial least squares (PLS) analysis, this metric is evaluated using Q-square predictive relevance (Q.
The formula for calculating the GoF value is outlined in Table 7.
Table 5.
Results of Goodness of Fit (GoF) R-square(R.
Variables Work Experience Work Motivation Job Satisfaction 0,698 Tutor Performance 0,461 AVE
0,597
0,636
0,632
0,703
Source: Processed Data, 2025 Arifin et al.
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OcyaycOya ycu 597 0.
ycAyceycaycu yaycOya = ycAyceycaycu yaycOya = 0.
OcycI 2 ycAyceycaycu ycI 2 = ycu 698 0.
ycAyceycaycu ycI = ycAyceycaycu ycI 2 = 0.
yaycuya = OoycAyceycaycu yaycOya y ycAyceycaycu ycI 2 yaycuya = Oo0.
642 y 0.
yaycuya = Oo0.
yaycuya = 0.
ycAyceycaycu yaycOya = Figure 3.
Bootstrapping Test Results Based on the R 2 and Q2 testing above, it shows that the model in this study is robust, so hypothesis testing can be carried out.
The path coefficient in the structural model needs to be statistically significant, which can be determined through the bootstrapping method.
This involves examining the model parameters and the corresponding t-statistic values reported in the bootstrapping analysis.
To assess significance, the critical t-value .
96 at = 0.
is compared to the calculated t-statistic derived from the bootstrapping results.
If the calculated t-statistic exceeds the critical value, the hypothesis is considered valid.
The path analysis confirms significant positive relationships across all hypothesized direct First, work environment exerts a substantial influence on tutor performance ( = 0.
t = 3.
683, p < 0.
, validating H1, while also significantly enhancing job satisfaction ( = 229, t = 3.
409, p = 0.
, supporting H2.
Similarly, work motivation directly boosts tutor performance ( = 0.
278, t = 3.
123, p = 0.
, confirming H3, and demonstrates an even stronger impact on job satisfaction ( = 0.
537, t = 8.
529, p < 0.
, affirming H4.
Crucially, job satisfaction emerges as a powerful predictor of tutor performance ( = 0.
472, t = 5.
060, p < .
, substantiating H5.
All t-statistics exceed the critical threshold of 1.
96 ( = 0.
confirming statistical significance.
These robust coefficients collectively verify that both environmental conditions and motivational drivers directly elevate job satisfaction and performance outcomes, while job satisfaction itself functions as a critical performance accelerator within Kampung InggrisAos educational framework.
Discussion The results confirm that job satisfaction significantly mediates the relationship between work environment and tutor performance ( = 0.
108, t = 2.
729, p = 0.
, supporting H6.
This partial mediation indicates that while work environment directly enhances performance, its impact is concurrently channeled through job satisfactionAivalidating the dual-path influence.
Similarly, job satisfaction partially mediates the motivation-performance link ( = 0.
254, t = 4.
434, p < 0.
affirming H7.
The substantial indirect effect reveals that motivationAos potency is amplified when routed through job satisfaction, though it retains significant direct influence.
Both mediation pathways demonstrate statistical significance .
> 1.
, establishing job satisfaction as a critical mechanism that partially explains how environmental and motivational factors drive performance.
This dual-mediation model underscores the necessity of cultivating tutor satisfaction alongside structural and motivational interventions to optimize educational outcomes in non-formal learning ecosystems like Kampung Inggris.
The research findings provide robust evidence that a positive and significant relationship exists between the work environment and tutor performance within the language training Arifin et al.
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Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
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: 247-260
institutions (LKP) of Kampung Inggris.
Pare.
This environment, measured through five key indicators derived from Burden & and Fraser .
and Johnson et al .
Ae the work environment was assessed through five key aspects: teamwork, student-teacher interactions, available educational resources, participation in decision-making, and innovative teaching strategies Ae was found to be conducive to enhancing tutors' effectiveness.
The implication is clear:
institutions fostering a superior work environment are likely to experience correspondingly higher levels of tutor performance in their teaching duties.
This aligns with theoretical frameworks proposed by Khabri et al .
and Kusumastuti et al .
, and empirical findings like those of Dolonseda & Watung .
, confirming the general principle that a supportive workplace significantly boosts employee performance.
Among the work environment indicators, "collaboration," particularly the opportunity to cooperate with fellow tutors, emerged as the highest-rated aspect, signifying its perceived importance in describing the Kampung Inggris LKP context.
Analysis of outer loading values further underscored the critical need for adequate school resources, such as videos, recordings, and Tutors explicitly indicated that the availability of such supporting equipment is essential for them to perform their duties maximally, highlighting resource provision as a vital component of the effective work environment in these institutions.
Tutor performance itself was measured using four indicators: standards-based planning, standards-based instruction, conditions for learning, and professional responsibilities.
Within this construct, "standards-based planning" stood out, specifically the practice of ensuring teaching materials align with relevant standards.
The outer loading analysis confirmed that using relevant materials significantly influences tutor performance, reinforcing the link between structured preparation based on established benchmarks and effective teaching outcomes.
Complementing the findings on the work environment, the research also established a strong, positive, and significant influence of work motivation on tutor performance.
Higher levels of motivation among tutors directly correlated with enhanced performance (Hijriyah et al.
, 2.
Measured through intrinsic motivation, identified regulation .
alue congruenc.
, and external regulation, motivation was found to be a powerful driver, consistent with the relationship identified by Wahyudi et al .
in organizational settings generally.
Regarding work motivation, the indicator "identified regulation," captured by the statement "My job as a tutor is very interesting and enjoyable," received the highest rating.
This suggests that tutors in Kampung Inggris predominantly perceive their work as intrinsically rewarding and aligned with their personal values.
Furthermore, the outer loading for "external regulation" indicated that tutors also demonstrate high responsibility and discipline in executing their duties, acknowledging the influence of external factors like salary and potential sanctions.
The study further demonstrated that the work environment exerts a positive and significant influence on tutor job satisfaction.
A better institutional environment leads to higher tutor Arifin et al.
/ Work Environment.
Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
No.
: 247-260
satisfaction, as supported by Lin et al .
Job satisfaction was measured through satisfaction with the work environment and satisfaction with the profession.
Notably, the indicator reflecting professional satisfaction, specifically the belief that "the benefits of being a tutor clearly outweigh the disadvantages," was the highest-rated item, indicating tutors perceive significant net advantages in their profession.
Similarly, work motivation was found to have a positive and significant impact on job The high rating for the value congruence indicator ("interesting and enjoyable") again highlights the role of intrinsic and value-aligned factors in driving satisfaction.
Analysis of outer loadings for external regulation also confirmed that tutors feel a sense of obligation and responsibility linked to external rewards and consequences, contributing to their overall work This finding aligns with studies by Irwan et al .
Pancasila et al .
Prabowo et al .
, and Qomariah et al .
(Prabowo et al.
, 2.
Job satisfaction itself was confirmed as a significant positive predictor of tutor performance.
Tutors who expressed higher satisfaction, particularly with their profession .
gain evidenced by the "benefits outweigh disadvantages" ite.
, demonstrated superior performance.
This reinforces the established principle that satisfied individuals within an organization tend to exhibit higher levels of performance, as noted by Sofyan et al .
(Liu et al.
, 2.
Crucially, the research identified job satisfaction as a mediating variable.
It acts as a partial mediator in the relationship between both the work environment and tutor performance, and between work motivation and tutor performance.
While significant direct paths exist from environment and motivation to performance, job satisfaction plays an additional, mediating role.
This means that a positive work environment and high motivation enhance performance both directly and indirectly by fostering greater job satisfaction.
This partial mediation finding is supported by studies such as Hasibiyadi et al .
for the work environment path and Irwan et al .
and Qomariah et al .
for the motivation path.
Despite confirming established relationships, this study holds significant contextual relevance as it was conducted within the unique non-formal education setting of Kampung Inggris Pare's LKP, characterized by andragogical methods, learner choice, and flexible learning environments beyond traditional classrooms (Oktaviana, 2018.
Yulianingsih et al.
, 2.
The confirmation that works environment, motivation, and job satisfaction remain powerful determinants of tutor performance in this distinct context underscores the universal applicability of sound human resource management principles, even within flexible, non-conventional educational The finding that job satisfaction acts as a partial mediator, with direct effects of environment and motivation being stronger, further suggests that in this dynamic setting, intrinsic motivators and a supportive atmosphere are primary performance drivers, with satisfaction reinforcing these effects.
Conclusion This study empirically establishes that tutor performance at Language Training Institutions (LKP) in Kampung Inggris is significantly elevated by a supportive work environment Ai specifically through collaborative engagement and accessible pedagogical resources .
videos, recording.
Concurrently, heightened work motivation, derived from intrinsic professional interest and commitment, directly augments instructional effectiveness.
Both environmental conditions and motivational drivers further positively predict tutor job satisfaction, evidenced through occupational fulfillment and institutional advocacy.
Job satisfaction itself constitutes a robust direct antecedent of performance outcomes.
Critically, mediation analysis confirms job satisfaction operates as a partial intermediary in the work environment-performance and work motivation-performance pathways, indicating these factors enhance outcomes both directly and indirectly via satisfaction.
Future investigations should broaden sampling diversity and geographical coverage beyond the current ten-institution scope, while incorporating supplementary variables .
, leadership dynamics, organizational culture, stress indicators, workload metric.
to advance contextual understanding.
Arifin et al.
/ Work Environment.
Motivation, and Tutor Performance: Job Satisfaction as Mediator in Language Course Institutions IJNI: International Journal of Nusantara Islam Vol.
No.
: 247-260
References