Corresponding Author: Chandra

INTRODUCTION

One benchmark that can be used to determine a school's success in educating students is learning outcomes (Glassman & Kang, 2016). Learning outcomes are all student achievements in the cognitive, affective, and psychomotor domains. Learning outcomes are an essential benchmark because they can be used as evaluation material for schools, teachers, and students to improve the quality of education (Suprianto, 2018). To provide maximum learning results, more is needed for students to exert their efforts; the role of teachers as educators and schools as educational institutions are needed to provide learning experiences that suit students' needs and build a disciplined and conducive school atmosphere.

Implementing the independent curriculum in educational units has begun to mean that learning is centered on students with competency achievement as the emphasis (Cholilah et al., 2023). Learning outcomes are one of the outcomes expected from students with teachers as facilitators. However, student learning outcomes in Indonesia tend to be less than optimal. This is supported by Ratna et al. (2022) in their research, explaining that the learning outcomes of students in Indonesia tend to be not optimal. Therefore, efforts to optimize student learning outcomes according to their respective characteristics must always be made so that student learning outcomes can meet the criteria for achieving the learning objectives set.

To be a complete human being, it is not enough to have good academic skills; on the other hand, it is necessary to instill noble values and character in students. One of the ways these manners and values can be instilled is through religious learning. In Indonesia, special schools provide learning by emphasizing religious values, one of which is the Maitreyawira Private High School (SMAS). As one of the SMAS in Indonesia, Maitreyawira Private High School has the critical task of providing and instilling religious values and manners, especially in Buddhist teachings. However, in reality, the results of studying Buddhist Education at SMAS Maitreyawira are still not optimal; this is reflected in the results of a preliminary survey of 30 SMAS Maitreyawira class X students as follows:

1. There are 60% of tenth-grade students who are still unable to meet the demands of the Basic Competencies (KD), particularly in applying the role of the Buddhist religion in science, technology, arts, and culture.

2. There are 73.33% of tenth-grade students who are still unable to meet the demands of the Basic Competencies (KD), specifically in demonstrating responsible, caring, responsive, and proactive behavior towards various life phenomena in accordance with the cosmic order law (niyama).

3. There are 56.66% of tenth-grade students who still face challenges in meeting the demands of the Basic Competencies in appreciating the history of the dissemination of the Buddhist religion during the Ancient Mataram era, Srivijaya, the colonial and independence periods, up to the present.

4. There are 40% of tenth-grade students who are still unable to meet the understanding requirements of the Basic Competencies, namely appreciating various life phenomena in accordance with the cosmic order law (niyama).

5. There are 46.66% of tenth-grade students who still encounter difficulties in interpreting the role of the Buddhist religion in science, technology, arts, and culture within the Basic Competencies.

6. There are 53.33% of tenth-grade students who still face challenges in meeting the requirements of the Basic Competencies in practicing responsive and proactive behavior regarding the role of the Buddhist religion in science, technology, arts, and culture.

Based on the survey results, it was found that there are still several problems in fulfilling the demands on Basic Competencies that Maitreyawira High School students must meet. This problem is the cause of the still not optimal learning outcomes for Buddhist education at SMAS Maitreyawira. Several things cause the failure to achieve student learning outcomes; the results of observations show that 1) teachers still use conventional learning methods so that the teaching and learning process is still centered on the teacher, not the students, 2) the results of observations show that students are not yet disciplined in the learning process. Indicated by the presence of students who pay little attention when the teacher explains in class; 3) quite a few students are busy themselves chatting and playing with friends, so they ignore and do not listen to what the teacher says or explains; 4) some students are less or impolite in their behavior or speech when expressing group opinions; 5) some students tend to experience delays and even forget to make assignments, this creates indiscipline among the students themselves; 6) the process of absorbing information when learning is not optimal because students lack the discipline to carry out learning; 7) the lack of learning discipline from students makes students unprepared when facing sudden tests because the time spent studying is used for playing; 8) students' self-awareness is still not optimal in viewing the importance of instilling moral and religious values in everyday life.

Based on the survey results, it was found that problems with student learning outcomes were caused and influenced by several aspects, such as positive discipline, differentiated instruction strategy, and learning motivation. Discipline is an effort that puts an individual on the path of behavior and attitudes that have been determined for a person by their parents. Discipline is a guidance process that aims to maintain specific patterns of behavior, forming a human being with specific characteristics or certain habits to improve the moral and mental state of the individual. A disciplined attitude when participating in learning is essential for creating a better learning process. A disciplined attitude when learning will further sharpen students' memory and skills regarding the material that has been taught because students will always be motivated to learn and carry out learning based on their awareness, ultimately motivating them to improve their learning outcomes.

Positive discipline is essential to achieve maximum student learning outcomes; positive discipline at school will encourage students to focus more on the learning process (Sobri, 2020). This condition certainly positively impacts student learning outcomes because discipline is critical to achieving a learning goal (Strelan et al., 2020). Apart from discipline, learning strategies are also essential in improving student learning outcomes. One of them is a differentiated instruction strategy. differentiated instruction by module 2.1 in the Teacher Mobilization Program co, commonly abbreviated as PGP: differentiated instruction is a philosophy or process in an effective learning process to create various ways to find out new information for all students in different classroom communities, including steps used to develop learning products, reason ideas, build, process or acquire content, as well as develop assessment measures so that all students in a classroom who have different ability backgrounds can learn effectively (Swandewi, 2021). The process of differentiating learning is carried out in response to each student's learning interests, styles, and learning needs.

Learning motivation is also indicated to be one of the factors that can influence student learning outcomes (Jamil, 2016). Learning motivation is encouragement from within or outside students to carry out the learning process (Supriani et al., 2020). Motivation is one aspect that can cause students to consciously try to achieve the competencies being taught so that their learning outcomes will be more optimal. Psychologically, learning motivation will mentally encourage students to act and behave according to the characteristics of students who should be; thus, learning motivation must be developed and encouraged, either by students or by teachers, to support their learning process (Schweder & Raufelder, 2024).

Based on the results of surveys and observations of the learning outcomes of Maitreyawira High School students, several problems were still found related to student learning outcomes that were not yet optimal, so more in-depth research is needed regarding the learning outcomes of Buddhist education and the factors that influence them. This research aims to learn in-depth about the Influence of Positive Discipline and differentiated instruction on the Buddhist Education Learning Outcomes of Maitreyawira High School Students throughout Indonesia. The results of this research can provide input to school principals, especially those who need it, in general regarding positive discipline, differentiated instruction, and learning motivation regarding the Buddhist Education Learning Outcomes of Maitreyawira High School Students throughout Indonesia so that they can do their work optimally in order to achieve the school's vision and mission by expectations.

METHOD

This research was conducted with a limited focus on Maitreyawira High School students. This research was conducted at SMAS Maitreyawira throughout Indonesia (Palembang, Batam, Deli Serdang, Tanjung Pinang, Jakarta, Kisaran). This research was conducted over six months, starting from the time the instrument for this research was approved, namely from January 2023 to June 2023. Quantitative research examines a specific population with problems to solve by analyzing numerical data. Alternatively, numerical so that this type of research can test temporary answers that have been formulated. The population in this research was the total number of Maitreyawira High School students throughout Indonesia (Palembang, Batam, Deli Serdang, Tanjung Pinang, Jakarta, Kisaran) totaling 1,089 people. The technique for determining the sample in this research was performed using Probability Sampling and simple Random Sampling using the Slovin equation, so the number of samples used was 92 Maitreyawira High School students. The data collection techniques used in this research were questionnaires and documentation. The data analysis techniques used in this research are the classical assumption test, multiple linear regression analysis, coefficient of determination test, and hypothesis testing, which includes the F test, t-test, and partial correlation test.

RESULTS AND DISCUSSION

Classic Assumption Test

Normality Test

Table 1. Normality Test Results

One-Sample Kolmogorov-Smirnov Test
		Positive Discipline	Differentiated instruction strategy	Motivation to learn	Learning outcomes
N		92	92	92	92
Normal Parameters^a,b	Mean	105.0761	64.2174	87,0000	30.3261
Normal Parameters^a,b	Std. Deviation	6.77622	5.04012	5.60612	5.52339
Most Extreme Differences	Absolute	,085	,084	,087	,080
	Positive	,085	,084	,051	,080
	negative	-.058	-.071	-.087	-.071
Statistical Tests		,085	,084	,087	,080
Asymp. Sig. (2-tailed)		,098 ^c	.120 ^c	.083^c	.184^c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.

Source: Processed data, 2023

Based on Table 1, the significance value of the unstandardized residual for each variable is more significant than 0.05. Namely, the positive discipline variable is 0.098, the differentiated instruction strategy strategy variable is 0.120, the learning motivation variable is 0.083, and the learning outcomes variable is 0.184, so it can be concluded that the data used in this study was normally distributed.

Linearity Test

Table 2. Linearity Test Results for Positive Discipline

Variables and Learning Outcome Variables

ANOVA Table
			Sum of Squares	df	Mean Square	F	Sig.
Learning Outcomes *Positive Discipline	Between Groups	(Combined)	1560.983	27	57,814	3,045	,000
		Linearity	946,519	1	946,519	49,848	,000
		Deviation from Linearity	614,465	26	23,633	1,245	,237
	Within Groups		1224.984	1215.234	64	18,988
	Total		2776.217	2776.217	91

Source: Processed data, 2023

Based on Table 2, it can be seen that the Deviation from the Linearity value is > 0.05 (0.237 > 0.05). These results indicate a linear relationship between positive discipline variables and learning outcomes.

Table 3. Results of Linearity Test for Learning Strategy Variables

Differentiation and Learning Outcome Variables

ANOVA Table
			Sum of Squares	df	Mean Square	F	Sig.
Learning Outcomes * Differentiated instruction strategy Strategy	Between Groups	(Combined)	1458.546	21	69,455	3,690	,000
		Linearity	1138,768	1	1138,768	60,496	,000
		Deviation from Linearity	319,778	20	15,989	,849	,648
	Within Groups		1317.671	70	18,824
	Total		2776.217	91

Source: Processed data, 2023

Based on Table 3, it can be seen that the Deviation from the Linearity value is > 0.05 (0.648 > 0.05). These results indicate a linear relationship between the differentiated instruction strategy strategy variables and learning outcomes.

Table 4. Linearity Test Results for Learning

Motivation Variables and Learning Outcome Variables

ANOVA Table
			Sum of Squares	df	Mean Square	F	Sig.
Learning Outcomes * Learning Motivation	Between Groups	(Combined)	1967,895	23	85,561	7,198	,000
		Linearity	1752,840	1	1752,840	147,457	,000
		Deviation from Linearity	215,056	22	9,775	,822	,688
	Within Groups		808.322	68	11,887
	Total		2776.217	91

Source: Processed data, 2023

Based on Table 4, it can be seen that the Deviation from the Linearity value is > 0.05 (0.688 > 0.05). These results indicate that the variables of learning motivation and learning outcomes have a linear relationship.

Multicollinearity Test

Table 5. Multicollinearity Test Results

Coefficients^a
Model		Collinearity Statistics
		Tolerance	VIF
1	Positive Discipline	,679	1,472
	Differentiated instruction strategy Strategy	,557	1,796
	Motivation to learn	,547	1,827
a. Dependent Variable: Learning Outcomes

Source: Processed data, 2023

Based on Table 5 above, it is found that the variables positive discipline, differentiated instruction strategy strategies, and learning motivation have a tolerance value greater than 0.1 and a VIF value smaller than 10. Thus, multicollinearity does not occur.

Heteroscedasticity Test

Table 6. Heteroscedasticity Test Results

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta	t	Sig.
1	(Constant)	1,335	4.107		,325	,746
	Positive Discipline	,049	.041	,152	1,202	,232
	Differentiated instruction strategy Strategy	.071	,061	,163	1,168	,246
	Motivation to learn	-.103	,055	-.262	-1,862	,066
a. Dependent Variable: ABS_RES1

Source: Processed data, 2023

Based on Table 6 above, it is found that the variables positive discipline, differentiated instruction strategy strategies, and learning motivation have a significance greater than 0.05. Thus, heteroscedasticity does not occur.

Multiple Linear Regression Analysis

Table 7. Results of Multiple Linear Regression Analysis

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	Q	Sig.
Model		B	Std. Error	Beta	Q	Sig.
1	(Constant)	-48,578	5,880		-8,261	,000
	Positive Discipline	,158	,059	,194	2,687	,009
	Differentiated instruction strategy Strategy	,189	,087	,172	2,162	.033
	Motivation to Learn	,577	,079	,585	7,280	,000
a. Dependent Variable: Learning Outcomes

Source: Processed data, 2023

Based on the results of the regression analysis, as presented in Table 7, the following structural equation can be created:

Y = -48.578 + 0.158 X₁+ 0.189 X₂+ 0.577 X₃

The results of this equation show the magnitude and direction of the influence of each independent variable on the dependent variable. A positive regression coefficient means it has a unidirectional influence on learning outcomes. Based on the multiple linear regression equation, the coefficients can be explained as follows:

a. The coefficient value of positive discipline (X₁) is positive at 0.158, meaning that if X₁ (positive discipline) increases with the assumption that differentiated instruction strategy strategies and learning motivation remain constant, then learning outcomes will also increase.

b. The coefficient value of differentiated instruction strategy strategy (X₂) is positive at 0.189, indicating that if X₂ (differentiated instruction strategy strategy) increases with the assumption that positive discipline and learning motivation remain constant, then learning outcomes will also increase.

c. The coefficient value of learning motivation (X₃) is positive at 0.577, meaning that if X₃ (learning motivation) increases with the assumption that positive discipline and differentiated instruction strategy strategies remain constant, then learning outcomes will also increase.

Coefficient of Determination Test

Table 8. Determination Analysis Results

Model Summary^b
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	,830^a	,689	,678	3.13407
a. Predictors: (Constant), Learning Motivation, Positive Discipline, Differentiated instruction strategy Strategy
b. Dependent Variable: Learning Outcomes

Source: Processed data, 2023

The magnitude of the influence of the independent variable on the dependent variable, as indicated by the total determination value (Adjusted R Square) of 0.678, means that 67.8% of learning outcomes are influenced by positive discipline variance, differentiated instruction strategy strategies, and learning motivation, while the remaining 32.2% explained by other factors not included in the model.

Simultaneous Significance Test (F Statistical Test)

Table 9. F Statistical Test Results

ANOVA^a
Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	1911,848	3	637,283	64,881	,000 ^b
	Residual	864,370	88	9,822
	Total	2776.217	91
a. Dependent Variable: Learning Outcomes
b. Predictors: (Constant), Learning Motivation, Positive Discipline, Differentiated instruction strategy Strategy

Source: Processed data, 2023

a. Determining Hypothesis Formulation

H₀: β₁, β_2,β₃= 0, meaning there is no positive and significant influence between positive discipline, differentiated instruction strategy strategies, and learning motivation on learning outcomes.

H_a: β₁, β_2,β₃> 0, meaning that there is a positive and significant influence simultaneously between positive discipline, differentiated instruction strategy strategies, and learning motivation on learning outcomes.

b. Testing Terms

Using a degree of confidence of 95% or an error rate of 5% (α 0.05, free, comparative data: k and degree of the denominator: nk -1 then the value of F table = 0.05 (k) is obtained. ; nk -1 ), (92 ï¿½ 3 - 1) = 88 in the F_tableobtained is F_{(0.05; 3,
88)}= 2.71.

c. Testing Criteria

If F_count > 2.71, Ho is rejected, meaning the influence is significant.

If F_count< 2.71, Ho is accepted, meaning the effect is insignificant.

d. Acceptance and Rejection of Ho

The data processing results using the SPSS program obtained a calculated F_valueof 64.881 with a significance of 0.000. In this study, df1 = 3 and df2 = 88, so the F table value is F0.05(3.88) = 2.71. Based on the overall test results, the calculatedF_value > F_table, 64.881 > 2.71, with a sig value of 0.000 < 0.05, then H₀is rejected, and H₁is accepted.

Figure 1. Area of Rejection and Acceptance of H₀with F Test (F-test)

e. Conclusion

Based on the analysis results, the significance value of the F test was obtained, namely 0.000 < 0.05. The calculatedF_value > F_table, 64.881 > 2.71. These results mean a positive and significant influence between positive discipline, differentiated instruction strategy strategies, and learning motivation on learning outcomes.

Significance Test Parameter Individual (Test Statistics t)

Testing of independent variables on learning outcomes in the t-test is carried out to determine whether the relationship actually occurs (significant) or is only obtained by chance.

Table 10. Statistical Test Results t

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	Q	Sig.
Model		B	Std. Error	Beta	Q	Sig.
1	(Constant)	-48,578	5,880		-8,261	,000
	Positive Discipline	,158	,059	,194	2,687	,009
	Differentiated instruction strategy Strategy	,189	,087	,172	2,162	.033
	Motivation to learn	,577	,079	,585	7,280	,000
a. Dependent Variable: Learning Outcomes

Source: Processed data, 2023

The Effects of Positive Discipline on Learning Outcomes

To test the effect of positive discipline on learning outcomes, the following steps are used:

a. Determine the hypothesis formulation

Ho: β ₁= 0, meaning no positive and partially significant influence exists between positive discipline and learning outcomes.

Ha: β ₁> 0, meaning a partially positive and significant influence exists between positive discipline and learning outcomes.

b. Testing Terms

Using a degree of confidence of 95% or an error rate of 5% ( α 0.05, and degrees of freedom: nk-1, a two-sided test on the left and right sides obtained the t-table value (0.05; nk-1) = ( 92 - 3 - 1), then t table = 1.662.

c. Testing Criteria

1) If the t_count < 1.662, then Ho is accepted, meaning the effect is not significant

2) If t_count > 1.662 then Ho is rejected, meaning the influence is significant

d. Compare t count with t table

t_value > t_table (2.687 > 1.662 ), then H₀ isrejected and H₂ isaccepted. For more details, you can see the typical curve below.

Figure 2. H₀ Acceptance and Rejection Areas (t₂- test)

e. Conclusion

Based on the results of the analysis, a significance value of 0.009 was obtained, less than 0.05 (0.009 < 0.05), with a regression coefficient value of 0.158 and a calculated t_value > t_table (2.687 > 1.662). This result means a partial positive and significant influence exists between positive discipline and learning outcomes.

The Effect of Differentiated instruction strategy Strategies on Learning Outcomes

To test the effect of differentiated instruction strategy strategies on learning outcomes, the following steps are used:

a. Determine the hypothesis formulation

Ho : β₂= 0, meaning there is no positive and partially significant influence between differentiated instruction strategy strategies and learning outcomes.

H_a: β₂> 0, meaning differentiated instruction strategy strategies have a partially positive and significant influence on learning outcomes.

b. Testing Terms

c. Testing Criteria

1) If the t_count< 1.662, then Ho is accepted, meaning the effect is not significant

2) If t_count > 1.662 then Ho is rejected, meaning the influence is significant

d. Compare t count with t table

e. t_value > t_table(2.162 > 1.662 ), then H₀ isrejected and H₃ isaccepted. For more details, you can see the typical curve below.

Figure 3. Ho Acceptance and Rejection Areas (t₂- test)

f. Conclusion

Based on the results of the analysis, a significance value of 0.033 was obtained, less than 0.05 (0.033 < 0.05), with a regression coefficient value of 0.189 and a calculated t_value > t_table (2.162 > 1.662). These results mean that there is a partial positive and significant influence between differentiated instruction strategy strategies and learning outcomes.

Influence of Learning Motivation on Learning Outcomes

To test the effect of learning motivation on learning outcomes, the following steps are used:

a. Determine the hypothesis formulation

Ho : β₃= 0, meaning there is no positive and partially significant influence between learning motivation and learning outcomes.

Ha : β₃> 0, meaning a partially positive and significant influence exists between learning motivation and learning outcomes.

b. Testing Terms

c. Testing Criteria

1) If the t_count < 1.662, then Ho is accepted, meaning the effect is not significant.

2) If t_count > 1.662 then Ho is rejected, meaning the influence is significant.

d. Compare t_count with t_table

t_value > t_table (7.280 > 1.662 ), then H₀ is rejected and H₄ is accepted. For more details, you can see the typical curve below.

Figure 4. Ho Acceptance and Rejection Areas (t₂- test)

e. Conclusion

Based on the results of the analysis, a significance value of 0.000 was obtained, less than 0.05 (0.000 < 0.05), with a regression coefficient value of 0.577 and a calculated t_value > t_table (7.280 > 1.662). These results mean that there is a partial positive and significant influence between learning motivation and learning outcomes.

The Influence of Positive Discipline on Learning Outcomes

Based on the results of data analysis, it shows that positive discipline has a positive and significant effect on learning outcomes; this is obtained from a significance value of 0.009 less than 0.05 (0.009 < 0.05), with a regression coefficient value of 0.158 and a calculated t_value > t_table ( 2.687 > 1.662). This result means that positive discipline has a partially positive and significant effect on learning outcomes.

Discipline is an important aspect and must be possessed by a student; this is because, through positive discipline, students will be able to produce maximum learning results. Positive discipline is essential to achieve maximum learning outcomes for students; positive discipline at school will encourage students to focus more on the learning process. This condition certainly positively impacts student learning outcomes because discipline is essential to achieving a learning goal.

This research aligns with the results of research conducted (Novianty, 2020), showing that positive discipline positively affects learning outcomes. Similar research results presented by (Siahaan and Pramusinto, 2018) show that positive discipline has a positive effect on learning outcomes.

The Influence of Differentiated instruction strategy Strategies on Learning Outcomes

Based on the results of data analysis show that differentiated instruction strategy strategies have a positive and significant effect on learning outcomes; this is obtained from a significance value of 0.033 less than 0.05 (0.033 < 0.05), with a regression coefficient value of 0.189 and a calculated t_value > t_table (2.162 > 1.662). These results mean that differentiated instruction strategy strategies partially positively and significantly affect learning outcomes.

Learning strategies are essential because, through appropriate learning strategies, the learning process will become more conducive. Learning strategies are also essential in improving student learning outcomes. One of them is a differentiated instruction strategy strategy. Differentiated instruction strategy is a philosophy or process in an effective learning process to create various ways to find out new information for all students in different classroom communities, including the steps used to develop learning products, reason ideas, build, process, or obtain content, as well as developing assessment measures so that all students in a classroom who have different ability backgrounds can carry out learning effectively. The process of differentiating learning is carried out in response to each student's learning interests, styles, and learning needs.

The results of this research are in line with the results of research conducted by (Kamal, 2021), showing that good differentiated instruction strategy strategies can improve student learning outcomes. This condition is supported by research (Suwartiningsih, 2021) showing that differentiated instruction strategy strategies can improve student learning outcomes.

The Influence of Learning Motivation on Learning Outcomes

Based on the results of the data analysis show that learning motivation has a positive and significant effect on learning outcomes; this is obtained from a significance value of 0.000 less than 0.05 (0.000 < 0.05), with a regression coefficient value of 0.577 and a calculated t_valueof > t_table (7.280 > 1.662). These results mean that learning motivation has a partially positive and significant effect on learning outcomes.

Motivation to learn is one crucial aspect of encouraging students to have a desire to learn. Learning motivation is also indicated to be one of the factors that can influence student learning outcomes. Learning motivation is encouragement from within or outside students to carry out the learning process. Motivation is one aspect that can cause students to consciously try to achieve the competencies being taught so that their learning outcomes will be more optimal. Psychologically, learning motivation will mentally encourage students to act and behave according to the characteristics of students who should; thus, learning motivation must be developed and encouraged by students or by encouragement from teachers to support the learning process.

The results of this research align with the results of research conducted by (Utomo et al., 2022), which explains that learning motivation can improve student learning outcomes. Similar research results presented by (Prasetyo & Dasari, 2023) show that learning motivation positively affects learning outcomes.

The Influence of Positive Discipline, Differentiated instruction strategy Strategies, and Learning Motivation on Learning Outcomes

Based on the results of data analysis show that the influence of positive discipline, differentiated instruction strategy strategies, and learning motivation on learning outcomes is positive and significant; this is obtained from the results of the F test, which shows the significant value of the F test, namely 0.000 < 0.05 and the calculatedF_value > F_table, 64.881 > 2.71. These results mean that positive discipline, differentiated instruction strategy strategies and learning motivation simultaneously have a positive and significant effect on learning outcomes.

Increasing learning outcomes must also be supported jointly by positive discipline and differentiated instruction strategy strategies. The results of this research are in line with the results of research conducted by (Chotimah & Oktarina, 2019) (Iskandar, 2021) and (Dasari, 2023), which show that learning discipline, differentiated instruction strategy strategies, and learning motivation can improve student learning outcomes.

CONCLUSION

Based on the research results, positive discipline, differentiated instruction strategy strategies, and individual and collective learning motivation positively and significantly influence the learning outcomes of Buddhist Education at Maitreyawira High School students. These findings indicate that implementing positive discipline, differentiated instruction strategy strategies, and efforts to increase learning motivation can increase student achievement of learning outcomes in these subjects.

The implications of this research show the critical role of positive discipline, differentiated instruction strategy strategies, and learning motivation in Buddhist education at the high school level. Teachers and related parties must focus on and develop teaching methods that encourage positive discipline, differentiated instruction strategy strategies, and efforts to increase student learning motivation. Additionally, school policies can be designed to support the implementation of these practices to improve the quality of learning in Buddhist education.

In general, this research contributes to understanding the factors that influence learning outcomes in Buddhist religious education in high school and can be a basis for developing learning strategies and programs to improve the quality of Buddhist education in high school-level educational institutions.

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