ORIGINAL ARTICLE
STRENGTHENING JUNIOR HIGH SCHOOL STUDENTSAo
LEARNING MOTIVATION THROUGH SELF-CONTROL
AND FAMILY SUPPORT
Karina1*.
Nur Ainy Sadijah2.
Regi Ramadan3 Universitas Buana Perjuangan Karawang.
Indonesia *Corresponding Author: ps22.
karina@mhs.
ABSTRACT
Learning motivation is essential for sustaining adolescents' engagement, persistence, and academic development, yet preliminary evidence from a public junior high school indicated that 61% of students had low motivation.
This study examined self-control and family support as simultaneous predictors of learning motivation among junior high school students.
A quantitative cross-sectional predictive design was used.
The population comprised 580 students, from whom 231 participants were selected through grade-based quota sampling with sample size guided by the Krejcie-Morgan procedure.
Data were collected using Likert-type scales measuring learning motivation, self-control, and family support and were analyzed through multiple linear regression in SPSS 26.
The model was significant.
, .
= 216.
574, p < .
001, and explained 65.
5% of the variance in learning motivation (R = .
R2 = .
655, adjusted R2 = .
Self-control was a positive predictor (B = .
559, beta = .
256, t = 5.
884, p < .
while family support showed a stronger positive contribution (B = .
468, beta = .
663, t = 15.
264, p < .
The findings indicate that motivated learning in early adolescence is jointly associated with students' capacity to regulate impulses and with informational, emotional, instrumental, and appraisal support from their families.
Schools should therefore combine self-regulation development with structured family engagement.
Longitudinal, multi-school, and multi-informant research is recommended to test causal pathways and contextual variation.
Keywords: Academic Motivation.
Family Support.
Junior High School.
Self-Control.
Student Development INTRODUCTION In the past decade, much research has focused on the psychological and social conditions that sustain students' motivation in increasingly demanding educational environments.
Learning motivation refers to the processes that energize, direct, and maintain students' academic behavior, including their willingness to begin tasks, invest effort, persist when difficulties arise, and pursue valued learning goals.
Contemporary motivation theories emphasize that motivation is not a single fixed trait.
It develops through the interaction of students' beliefs, values, emotions, self-regulatory capacities, and relationships with significant others.
Self-determination theory, for example, distinguishes autonomous reasons for learning from controlled reasons and amotivation, and shows that more self-determined motivation is consistently associated with engagement, persistence, achievement, and psychological well-being (Howard et al.
, 2021.
Ryan & Deci, 2.
Situated expectancy-value theory similarly explains that students are more likely to invest effort when they expect that they can succeed and when they attach intrinsic, attainment, utility, or personally meaningful value to an academic task (Eccles & Wigfield.
These perspectives position learning motivation as a central mechanism through which personal and contextual resources are translated into educational participation and achievement.
The importance of motivation is especially visible during early adolescence.
Junior high school students experience rapid physical, cognitive, emotional, and social changes while simultaneously facing more complex curricula, multiple subject teachers, stronger peer influence, and growing expectations for independent learning.
At this developmental stage, academic behavior can become less dependent on direct adult control, but students' capacity to manage distractions and sustain long-term goals is still developing.
Motivation therefore becomes a practical indicator of whether students can adapt to the demands of secondary education.
Empirical syntheses have demonstrated meaningful associations between motivation and academic outcomes across school levels and subject areas.
Toste et al.
, for instance, identified a significant positive relationship between motivation and reading achievement among kindergarten through Grade 12 students, while motivation intervention research shows that theoretically grounded strategies can improve authentic educational outcomes (Lazowski & Hulleman, 2.
Motivation also works in concert with emotions and self-regulated learning: students who manage their learning strategically and maintain constructive motivational beliefs are more likely to attain stronger academic results (Mega et al.
, 2014.
Pintrich, 2004.
Zimmerman, 2.
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The local problem addressed in this study reflects these broader concerns.
Preliminary data collected in December 2025 at SMP Negeri 2 Telagasari showed that only 39% of students were classified as having high learning motivation, whereas 61% were in the low category.
The weakness was visible across several motivational indicators: 45% of students demonstrated insufficient achievement drive, 40% showed weak commitment to academic tasks, 51% lacked learning initiative, and 24% reported low optimism when confronting learning difficulties.
Interviews conducted during the preliminary inquiry were consistent with the survey pattern.
Several students reported that they studied mainly when examinations or assignments were imminent, did not establish explicit grade targets, postponed assignments, participated passively in group activities, rarely initiated independent study, and became discouraged after receiving low marks.
These behaviors are educationally consequential because they may reduce practice time, persistence, help-seeking, and the likelihood that students will develop stable learning routines.
A useful explanation of this problem must consider both internal and external determinants.
One major internal determinant is self-control, defined as the capacity to regulate impulses, emotions, attention, and behavior in accordance with valued standards or longer-term goals.
Self-control allows students to resist immediately rewarding alternatives, organize study behavior, continue working after frustration, and delay gratification in favor of academic objectives.
The Brief Self-Control Scale developed by Tangney et al.
conceptualizes this capacity through domains such as self-discipline, non-impulsive action, healthy habits, work ethic, and reliability.
Research has repeatedly associated stronger self-control with better adjustment and academic functioning.
Tangney et al.
reported that individuals with higher self-control demonstrated better grades and broader psychosocial Duckworth and Seligman .
found that self-discipline predicted adolescents' academic performance beyond intelligence.
and de Ridder et al.
concluded in a meta-analysis that trait selfcontrol is related to a wide range of adaptive behaviors.
Long-term evidence also links childhood selfcontrol to later health, economic, and behavioral outcomes (Moffitt et al.
, 2.
Self-control should not be reduced to effortful resistance at the moment of temptation.
Contemporary accounts emphasize proactive regulation, including selecting supportive environments, modifying situations, directing attention, and building beneficial habits before competing impulses become overwhelming (Duckworth et al.
, 2.
Galla and Duckworth .
demonstrated that beneficial habits partly explain why individuals with high self-control achieve positive outcomes.
In an academic context, this means that motivated students may not simply possess stronger willpower.
they may also establish routines, reduce distractions, begin assignments earlier, and make studying easier to initiate.
Such behaviors can protect motivational momentum.
When students repeatedly act in accordance with academic goals, they experience progress and competence, which can reinforce future engagement.
Accordingly, self-control is expected to make a positive contribution to learning motivation by enabling students to convert intentions into consistent learning behavior.
An equally important external determinant is family support.
Family support includes the emotional reassurance, informational guidance, tangible assistance, and evaluative feedback that students perceive from parents or other caregivers.
These forms of support can help adolescents interpret academic demands, manage setbacks, access learning resources, and maintain confidence that their effort is noticed and valued.
The family context is particularly relevant during early adolescence because students are seeking greater autonomy while still depending on caregivers for structure, encouragement, and educational expectations.
Research on parental involvement and autonomy support indicates that the quality of involvement matters as much as its frequency.
Support that communicates care, competence, appropriate expectations, and respect for the student's perspective tends to be more beneficial than intrusive monitoring or controlling pressure (Pomerantz et al.
, 2007.
Ryan & Deci, 2.
The evidence base for family influence is extensive.
Fan and Chen's .
meta-analysis identified a practically meaningful relationship between parental involvement and academic achievement, and Hill and Tyson .
found that parental involvement during middle school was positively associated with achievement, particularly when involvement took the form of academic socialization rather than direct control of schoolwork.
Gonzalez-DeHass et al.
reviewed evidence linking parental involvement to motivational outcomes, including school engagement, perceived competence, and task orientation.
a later meta-analysis of 448 independent studies.
Barger et al.
found small but consistent positive associations between parents' involvement and children's achievement, engagement, and motivation.
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Parent autonomy support has also been linked to academic achievement, autonomous motivation, engagement, perceived competence, and psychological functioning (Vasquez et al.
, 2.
These findings suggest that students' motivation develops within a relational system in which families communicate expectations, provide resources, and shape the meaning of academic success.
Family support may influence learning motivation through several mechanisms.
Emotional support can reduce anxiety and help students interpret failure as manageable rather than definitive.
Informational support can clarify learning strategies, deadlines, and educational pathways.
Instrumental support can provide time, study space, materials, transportation, or access to digital resources.
Appraisal support can supply constructive feedback that helps students evaluate progress realistically.
Social relationship research also shows that supportive relationships with parents, teachers, and peers are associated with students' interest, goal orientations, and social-academic adjustment in middle school (Wentzel, 1.
Furthermore, parental styles characterized by autonomy support, involvement, and structure have been associated with children's self-regulation and competence in school (Grolnick & Ryan, 1.
Thus, family support may strengthen motivation directly by increasing students' sense of relatedness and value and indirectly by reinforcing self-regulatory practices.
Although previous research supports the importance of both self-control and family support, several issues remain unresolved.
First, many studies examine personal self-regulation and family involvement in separate analytical models, making it difficult to determine their relative contributions when considered simultaneously.
Second, findings about parental involvement are heterogeneous because involvement can range from autonomy-supportive academic socialization to controlling homework more involvement is not always better (Boonk et al.
, 2018.
Pomerantz et al.
, 2.
Third, much of the international evidence focuses on Western settings, older adolescents, or academic achievement rather than learning motivation as the immediate outcome.
Fourth, evidence from Indonesian junior high schools remains comparatively limited, particularly in settings where preliminary data indicate widespread motivational difficulties.
It therefore remains unclear whether an internal selfregulatory resource or an external family resource provides the stronger statistical contribution to students' motivation in this specific developmental and cultural context.
The scientific literature suggests an integrated solution.
Rather than treating low motivation solely as an individual deficit or solely as a family problem, an ecological self-regulation perspective proposes that motivation emerges from the fit between students' internal regulatory capacities and the support available in their daily environment.
Self-control can help students initiate and sustain goal-directed behavior, while family support can provide the meaning, resources, reassurance, and structure that make such behavior possible.
Bureau et al.
showed that need-supportive relationships are important pathways to self-determined student motivation, and Wang and Sheikh-Khalil .
demonstrated that parental involvement can contribute to achievement and mental health through students' behavioral and emotional engagement.
These findings justify testing self-control and family support in the same predictive model.
The purpose of this study was therefore to examine whether self-control and family support significantly predict the learning motivation of junior high school students, both separately and jointly.
The study proposed that self-control would positively predict learning motivation, that family support would positively predict learning motivation, and that the two variables together would explain a substantial proportion of motivational variance.
The novelty of the study lies in integrating an internal psychological resource and an external relational resource in one model, comparing their standardized contributions, and grounding the analysis in a school context where most students had been identified as experiencing low motivation.
The scope was limited to students in one public junior high school and to cross-sectional self-report data.
Consequently, the study evaluates predictive associations rather than definitive causal effects.
Even within these limits, the findings can inform school counseling, family engagement, and student-development programs designed to strengthen motivation during early METHOD Research Design and Approach This study employed a quantitative, cross-sectional predictive correlational design.
The design was selected to estimate the independent and combined statistical contributions of self-control and family EDUCATIONE: Journal of Education Research and Review | 623
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support to learning motivation at one point in time.
Although the original study was framed as causal research, the use of nonexperimental, cross-sectional data does not establish temporal order or eliminate alternative explanations.
The results are therefore interpreted as predictive associations.
Self-control was specified as the first predictor (X.
, family support as the second predictor (X.
, and learning motivation as the criterion variable (Y).
The conceptual relations tested in the regression model are illustrated in Figure 1.
Figure 1.
Conceptual framework of the predictive model Population and Sample The study population consisted of 580 students enrolled at SMP Negeri 2 Telagasari.
A sample of 231 students was selected through non-probability quota sampling, with representation distributed across Grades 7, 8, and 9.
The target sample size was guided by the procedure of Krejcie and Morgan .
for a finite population at an approximately 5% margin of error.
The final sample included 87 Grade 7 students, 80 Grade 8 students, and 64 Grade 9 students.
It comprised 71 male students and 160 female students.
Because quota sampling does not give every population member a known probability of selection, the representativeness of the sample should be interpreted cautiously, and inferential generalization beyond the participating school is limited.
Data Collection Techniques and Instruments Data were collected with three Likert-type psychological scales.
The learning motivation scale was developed for the study and operationalized four dimensions: achievement drive, commitment, initiative, and optimism.
Achievement drive referred to students' orientation toward attaining learning goals and improving performance.
Commitment represented persistence in completing academic Initiative referred to self-starting learning behavior without continuous external prompting, while optimism reflected the tendency to continue striving after difficulty or disappointing Higher total scores indicated stronger learning motivation.
Self-control was measured using an adaptation of the Brief Self-Control Scale originally developed by Tangney et al.
The instrument represents self-discipline, deliberate or non-impulsive action, healthy habits, work ethic, and reliability.
The Indonesian adaptation has reported acceptable psychometric properties (Arifin & Milla, 2.
In the present study, higher scores represented a stronger capacity to regulate impulses and maintain behavior aligned with longer-term academic goals.
Family support was assessed with a researcher-compiled scale based on four established forms of social support: informational support, emotional support, instrumental assistance, and appraisal support (House, 1.
Informational support captured advice and academic guidance.
emotional support represented care, empathy, and encouragement.
instrumental support referred to practical resources or and appraisal support represented constructive feedback and recognition.
Instrument preparation involved construct specification, item writing or adaptation, expert review, pilot testing, and final questionnaire administration.
Content validity was evaluated through expert judgment using Aiken's V coefficient, which quantifies agreement among raters regarding the relevance of scale items (Aiken, 1.
Internal consistency was evaluated with Cronbach's alpha (Cronbach.
The source manuscript, however, did not report the number of experts, item counts, response anchors, item-level Aiken's V values, or the final alpha coefficients for the three scales.
These statistics EDUCATIONE: Journal of Education Research and Review | 624
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should be inserted from the original research records before journal submission because they are necessary for a complete evaluation of measurement quality.
Validity.
Reliability, and Ethical Considerations Questionnaires were distributed to the selected students and returned for data screening and analysis.
The source manuscript did not provide a formal ethics committee approval number or a complete description of parental consent and student assent procedures.
Before submission, the authors should add the responsible ethics body, approval number where applicable, school authorization, consent procedure, confidentiality safeguards, and data-protection arrangements.
The analysis in this article uses only aggregated results and contains no identifying student information.
Data Analysis Procedures Data analysis was conducted in SPSS version 26.
The analysis began with respondent profiling and assessment of regression assumptions.
The Kolmogorov-Smirnov procedure was used to examine the distribution of residuals, and tests of deviation from linearity were used to assess whether the relation between each predictor and learning motivation could be reasonably represented by a linear function.
Multiple linear regression then estimated the simultaneous model and the partial contribution of each Model fit was evaluated with the F test, the multiple correlation coefficient (R), the coefficient of determination (R.
, adjusted R2, and the standard error of estimate.
Individual predictors were evaluated using unstandardized coefficients (B), standard errors, standardized coefficients .
, t statistics, and probability values.
Statistical significance was evaluated at alpha = .
The source data did not report tolerance, variance inflation factors, residual plots, or influence diagnostics.
multicollinearity, homoscedasticity, and influential observations could not be independently evaluated in this revision.
RESULTS AND DISCUSSION
The analysis was conducted with complete data from 231 students.
The results are presented in sequence, beginning with the respondent profile and regression assumptions, followed by the overall model, partial predictor coefficients, and an integrated discussion of the findings.
Respondent Characteristics and Assumption Testing Table 1.
Respondent Demographic Characteristics Characteristic Category Frequency Percentage (%) Gender Male Gender Female Gender Total Grade Grade Grade Grade Total Table 1 shows that female students constituted 69.
3% of the sample and male students 30.
Grade 7 students represented the largest group .
7%), followed by Grade 8 .
6%) and Grade 9 .
7%).
The distribution provides participation from all three grade levels, but the gender imbalance should be considered when interpreting the model because the data do not indicate whether motivation, selfcontrol, or perceived family support differed by gender.
Future analyses should test whether the regression relations are invariant across gender and grade level rather than assuming that the same pattern applies equally to all subgroups.
Table 2.
Normality and Linearity Test Results Assumption Statistic / p Residual normality (Kolmogorovp = .
Smirno.
Criterion Interpretation p > .
Normality supported EDUCATIONE: Journal of Education Research and Review | 625
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Assumption Self-control - learning motivation linearity Family support learning motivation Statistic / p Criterion p = .
p > .
p = .
p > .
Interpretation Linear relation Linear relation The residual normality test yielded p = .
200, which exceeded the .
05 criterion and therefore did not provide evidence against a normal distribution.
The linearity tests also supported linear modeling: the deviation-from-linearity probability was .
262 for self-control and .
085 for family support.
Both values were greater than .
These results indicate that the available data satisfied the reported normality and linearity requirements for multiple regression.
Nevertheless, assumption testing should ideally include visual inspection of residual histograms and Q-Q plots, plots of standardized residuals against predicted scores, multicollinearity indices, and checks for influential cases.
The absence of these additional diagnostics does not invalidate the reported model, but it limits the completeness of the statistical audit.
Overall Regression Model Table 3.
Multiple Regression Model Summary and ANOVA
Adjusted RA
SEE
2, 228
< .
The simultaneous regression model was statistically significant.
, .
= 216.
574, p < .
The multiple correlation was high (R = .
, and the two predictors explained 65.
5% of the observed variance in learning motivation (R2 = .
adjusted R2 = .
The standard error of estimate was In substantive terms, students who reported stronger self-control and stronger family support also tended to report higher achievement drive, commitment, initiative, and optimism.
The remaining 34.
of variance may reflect unmeasured influences such as perceived competence, teacher support, peer norms, academic self-efficacy, task value, classroom climate, prior achievement, emotional well-being, socioeconomic resources, and the quality of instructional practice.
The magnitude of R2 is notable for an educational-psychological model based on only two predictors.
Motivation is typically multidetermined, and major frameworks emphasize interactions among personal beliefs, emotions, goals, relationships, and learning conditions (Eccles & Wigfield, 2020.
Ryan & Deci.
Explaining nearly two-thirds of the variance suggests that the two measured resources were closely connected to the students' reported motivation in this school.
At the same time, the value should not be interpreted as proof that interventions targeting only self-control and family support will produce an equivalent change in motivation.
Shared method variance is possible because all variables were measured by self-report in the same questionnaire context, and cross-sectional regression may overstate explanatory clarity when predictors and outcomes contain conceptually overlapping evaluative content.
Partial Effects of Self-Control and Family Support Table 4.
Multiple Regression Coefficients Predicting Learning Motivation Zero-order Predictor Constant Self-control < .
Family support < .
The resulting unstandardized prediction equation was: Learning motivation = -4.
559(Selfcontro.
468(Family suppor.
The first specific finding was that self-control positively predicted learning motivation.
B = .
SE = .
095, beta = .
256, t = 5.
884, p < .
Holding family support constant, each one-unit increase in self-control was associated with a .
559-unit increase in the predicted learning motivation score.
The positive standardized coefficient supports the hypothesis that students' EDUCATIONE: Journal of Education Research and Review | 626
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regulatory capacity is related to their willingness to initiate, sustain, and recover in learning.
This finding is theoretically coherent because motivation requires more than endorsing an academic goal.
Students must repeatedly prioritize that goal over distractions, impulses, avoidance, and short-term alternatives.
Self-control supplies the behavioral consistency through which motivational intentions become observable study routines.
The result is consistent with the foundational evidence reported by Tangney et al.
, who associated higher self-control with better grades and adjustment, and with Duckworth and Seligman .
, who demonstrated the academic relevance of self-discipline among adolescents.
The broader meta-analytic evidence also shows that trait self-control is associated with adaptive behavior across domains .
e Ridder et al.
, 2.
From a self-regulated learning perspective, students are active participants who plan, monitor, and adjust cognition, motivation, and behavior in relation to goals (Pintrich, 2004.
Zimmerman, 2.
The present coefficient indicates that this internal regulatory function remains important even after family support is statistically controlled.
One explanation is that self-control supports the formation and protection of learning routines.
student may value good grades but still fail to act when digital entertainment, peer interaction, fatigue, or anxiety offers a more immediate alternative.
Students with stronger self-control are more likely to begin tasks despite low momentary interest, limit distractions, persist after errors, and return to unfinished work.
Importantly, effective self-control often operates through situational strategies rather than repeated acts of willpower.
Duckworth et al.
argued that people can regulate behavior by selecting or modifying situations before temptation becomes dominant.
Galla and Duckworth .
further showed that beneficial habits mediate part of the relation between self-control and positive In school practice, this implies that students can strengthen motivation by designing regular study times, keeping devices away during homework, preparing materials in advance, and using small task-starting cues.
Self-control may also influence motivation through competence feedback.
When students regulate their behavior effectively, they complete more tasks, receive more opportunities for corrective feedback, and observe progress toward goals.
These experiences can increase expectancy for success and perceived competence, both of which are central to motivation (Eccles & Wigfield, 2020.
Ryan & Deci.
Conversely, repeated procrastination and incomplete work can produce a cycle of low performance, negative feedback, reduced confidence, and further avoidance.
The finding therefore supports interventions that make self-regulation visible and teachable rather than treating motivation as a matter of attitude alone.
The second specific finding was that family support was a stronger positive predictor of learning motivation.
B = .
SE = .
031, beta = .
663, t = 15.
264, p < .
Although the unstandardized coefficient was numerically smaller than that of self-control because the measures may have different score ranges, the standardized coefficient shows that family support had the larger relative contribution in this model.
Its beta was approximately 2.
6 times the beta for self-control.
This pattern suggests that the motivational difficulties observed in the participating school cannot be addressed only by asking students to become more disciplined.
The social environment in which students interpret academic demands appears highly salient.
The strength of family support is consistent with research showing that supportive parent-child relationships shape students' engagement, values, and school adjustment.
Wentzel .
found that perceived support from parents, teachers, and peers was related to motivation in middle school.
Gonzalez-DeHass et al.
concluded that parental involvement can be associated with school engagement, intrinsic-extrinsic motivational orientations, perceived competence, self-regulation, and mastery orientation.
Meta-analyses have similarly documented positive, although heterogeneous, relations between parental involvement and academic outcomes (Barger et al.
, 2019.
Fan & Chen, 2001.
Hill & Tyson, 2.
The present findings extend that literature by showing a strong association with motivation itself rather than only with final achievement.
Family support may be especially influential for early adolescents because it simultaneously addresses relatedness, structure, and academic meaning.
Emotional attention communicates that students are valued even when performance is imperfect.
Informational guidance helps them understand what to do and how to respond to difficulty.
Instrumental assistance reduces practical barriers by providing materials, quiet time, transportation, connectivity, or help accessing school resources.
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Appraisal support provides feedback that can normalize struggle while recognizing progress.
These functions can sustain optimism and commitment, two dimensions of the motivation measure used in this Parent autonomy support is particularly relevant because it combines expectations with respect for the student's perspective.
Vasquez et al.
found that autonomy support was related to achievement and adaptive psychosocial functioning, while Grolnick and Ryan .
associated autonomy support, involvement, and structure with self-regulation and school competence.
The finding that family support was stronger than self-control should be interpreted in context rather than as a universal ranking.
Self-control and family support are not isolated or competing resources.
Families can help students develop self-control by establishing predictable routines, modeling planning, discussing goals, supporting appropriate choice, and providing calm feedback after setbacks.
Students with stronger self-control may also be better able to use the support that families provide.
The regression model estimates independent linear contributions but does not test mediation, moderation, reciprocity, or developmental change.
A plausible integrated mechanism is that family support strengthens need satisfaction and task value, which improves motivation, while self-control helps translate that motivation into consistent action.
Bureau et al.
found that need-supportive behaviors from significant others are important antecedents of self-determined motivation, and Howard et al.
showed that more autonomous forms of motivation are associated with beneficial educational outcomes.
The large family-support coefficient also resonates with the preliminary interview data.
Students reported limited grade targets, task delay, low independent study, and discouragement after low marks.
Each behavior can be influenced by family communication.
Families that discuss educational aspirations without coercion can help students form meaningful targets.
Families that establish study routines can reduce task delay.
Families that encourage choice and problem solving can support independent Families that respond to low grades with constructive planning rather than criticism can protect optimism.
This interpretation accords with Pomerantz et al.
, who emphasized that the manner and purpose of parental involvement determine whether it is beneficial.
More monitoring is not necessarily more supportive.
involvement is most constructive when it promotes competence and autonomy rather than dependency or fear.
The model also has implications for how schools conceptualize responsibility for motivation.
deficit-oriented approach may label students as lazy or uncommitted and prescribe exhortation.
The present results support a systems approach.
Students need explicit self-regulation instruction, but families also need accessible guidance on developmentally appropriate support.
School-family partnerships should therefore move beyond attendance at formal meetings.
Schools can provide short, practical modules on setting expectations, discussing progress, structuring home study, responding to setbacks, and supporting autonomy.
Communication should be designed for families with varying work schedules, educational backgrounds, and access to technology.
Barger et al.
and Boonk et al.
caution that the effects of parental involvement vary by form, so programs should prioritize highquality academic socialization and emotional support rather than simply increasing the volume of homework supervision.
For counseling and student-development services, the findings suggest a dual-component The student component can teach goal setting, implementation intentions, distraction management, task chunking, self-monitoring, and reflection on progress.
Motivation interventions are more effective when they target theoretically specified mechanisms and connect academic tasks to value, competence, and attainable goals (Lazowski & Hulleman, 2.
The family component can teach supportive communication, realistic expectations, process-focused praise, resource planning, and autonomy-supportive monitoring.
These components can be linked through weekly student-family learning plans that identify one academic goal, one self-control strategy, one form of family support, and one brief review of progress.
Teachers also have a role in reinforcing the same motivational ecology.
Classroom tasks should provide clear purposes, appropriately challenging goals, actionable feedback, and opportunities for student choice.
When school practices are confusing, excessively controlling, or disconnected from students' experiences, even supportive families and self-controlled students may struggle to maintain Conversely, coherent expectations across home and school can reduce uncertainty and make self-regulation more effective.
Ryan and Deci .
emphasize that autonomy, competence, and relatedness are supported by social environments.
Eccles and Wigfield .
likewise highlight the EDUCATIONE: Journal of Education Research and Review | 628
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situated nature of expectancies and values.
The practical implication is that motivation should be treated as an institutional design concern as well as an individual psychological outcome.
At the policy level, family engagement indicators should be defined qualitatively.
Counting parent attendance at meetings may not capture whether students receive emotional reassurance, constructive feedback, learning resources, or autonomy-supportive guidance.
Schools could assess family support through brief student feedback, not to evaluate or blame families, but to identify barriers and tailor Support may need to include low-cost study materials, flexible communication channels, parent education sessions, or referrals to social services.
Because the participating school displayed a high proportion of students with low motivation, a tiered approach is appropriate: universal motivational supports for all students, targeted small-group self-regulation programs for students at moderate risk, and individualized counseling and family collaboration for students with persistent disengagement.
The study contributes to the literature by demonstrating that an internal resource and an external resource jointly explain substantial variation in learning motivation among Indonesian junior high school students.
The result complements self-control research that often emphasizes performance and adjustment and parental-involvement research that often emphasizes achievement.
By positioning learning motivation as the outcome, the study identifies a proximal process that may precede changes in attendance, task completion, persistence, and academic performance.
The comparison of standardized coefficients also provides a practical prioritization signal: family engagement may offer a particularly important entry point in this context, but it should be combined with direct development of students' self-regulatory skills.
Several alternative interpretations must be considered.
First, highly motivated students may perceive their families more positively or elicit more supportive behavior, creating reciprocal influence.
Second, family support may be associated with unmeasured socioeconomic resources, parental education, stable routines, or school communication.
Third, self-control and motivation measures may share content related to persistence and discipline, increasing their association.
Fourth, students who respond in socially desirable ways may give high scores across all three scales.
Fifth, the preliminary motivational categories were based on local cutoffs whose derivation was not reported.
These possibilities reinforce the need to avoid causal language and to replicate the model with longitudinal and multi-informant data.
The reliability of the findings is also constrained by incomplete measurement reporting.
The source manuscript states that Aiken's V and Cronbach's alpha were used, but it does not provide the coefficients.
Valid content representation and internal consistency are prerequisites for interpreting regression estimates because measurement error can attenuate or distort relations.
Aiken .
provides a framework for quantifying expert agreement, and Cronbach .
established coefficient alpha as an index of internal consistency.
The revised article therefore preserves the reported results while explicitly identifying the missing psychometric information as an author query.
A final submission should include item numbers, example items, response options, scoring procedures, validity coefficients, reliability coefficients, and any item-removal decisions.
The single-school, quota-sampled design further limits external validity.
The school may have distinctive leadership, community, socioeconomic, cultural, or instructional characteristics.
The predominance of female respondents may also shape aggregate estimates.
Replication should use probability sampling across urban, rural, and geographically diverse schools and should test whether coefficients differ across grade, gender, socioeconomic status, and family structure.
A multilevel design would be valuable because students are nested within classes and schools, and motivation may be influenced by teacher practices and school climate.
Longitudinal studies could establish whether family support predicts later motivation, whether self-control mediates that relationship, and whether motivation subsequently predicts achievement.
Future research should also differentiate forms of family involvement.
Meta-analytic evidence indicates that academic socialization and autonomy support may be more beneficial than direct or controlling homework involvement (Hill & Tyson, 2009.
Vasquez et al.
, 2.
Researchers should therefore examine emotional support, informational guidance, instrumental resources, appraisal, expectations, autonomy support, structure, psychological control, and school-based involvement as distinct constructs.
Experimental or quasi-experimental studies can then evaluate which combinations produce meaningful changes.
Similar differentiation is needed for self-control: habit formation, attention management, emotion regulation, planning, and impulse inhibition may not contribute equally to EDUCATIONE: Journal of Education Research and Review | 629
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Overall, the findings clearly show a coherent pattern: learning motivation was highest among students who reported both the capacity to regulate themselves and a supportive family The statistical dominance of family support does not reduce the importance of self-control.
rather, it indicates that self-regulation operates within a relational context.
Educational practice will be most effective when it avoids choosing between student responsibility and family responsibility and instead develops coordinated supports that make motivated behavior understandable, feasible, and CONCLUSION This study examined self-control and family support as predictors of junior high school students' learning motivation.
The results showed that the two variables jointly formed a significant model and 5% of the variance in motivation.
Self-control made a positive contribution, indicating that discipline, impulse regulation, constructive habits, and persistence are associated with stronger achievement drive, commitment, initiative, and optimism.
Family support made the larger standardized contribution, underscoring the importance of emotional attention, informational guidance, practical assistance, and constructive appraisal during early adolescence.
The study contributes an integrated internal-external account of motivation and supports school programs that combine self-regulation training with autonomy-supportive family engagement.
Because the data were cross-sectional, selfreported, quota-sampled, and drawn from one school, the findings should not be interpreted causally.
Future research should use longitudinal, multi-school, multi-informant, and experimental designs and should report complete psychometric evidence to clarify mechanisms and strengthen generalizability.
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