INTRODUCTION

.Inclusive education has emerged as one of the main approaches to guarantee equitable access to quality education for all learners, including students with special educational needs. The National Education System in Indonesia supports the implementation of inclusive education and is strengthened by regulations that encourage regular schools to accommodate students with diverse learning characteristics. However, the success of inclusive education is not only a matter of students’ physical access to mainstream classrooms, but also of the availability of educational services that are capable of meeting their academic, social and psychological needs. Slow learner students who need special attention as their learning characteristics are quite different from their peers are included in the diversified groups of students being served in inclusive schools. Students with slow learning typically have an intelligence below average, slower learning rate, and more difficulty understanding abstract ideas during the same period of instruction as other students. While they do not have an intellectual disability, their slower cognitive development often affects academic achievement, learning persistence and classroom participation. Frequent failures in academic activities often undermine students’ confidence in their own abilities and lead to a decrease in motivation to actively engage in learning activities (Gore, 2014). Therefore, learning motivation is one of the most important psychological factors that influence the educational success of slow learner students.

Learning motivation is the internal motivation that motivates students to start, continue and control their learning activities to achieve their academic goals. The high level of students’ learning motivation was associated with the willingness to persist with the implementation of tasks, to recover from setbacks and the desire to improve academic achievement. In contrast, low motivated students are characterized by passive learning behaviours, low participation in the classroom, low involvement in the tasks and the tendency to avoid difficult learning situations. These characteristics are commonly found in slow learner students. Their persistent academic difficulties consistently erode their confidence and their desire to engage in classroom learning. The phenomenon is more complex in inclusive classrooms, where learning activities are typically designed for students with average learning abilities. Uniform instructional pacing leaves slow learner students no time to process information at the same rate as their peers and causes them to experience repeated academic failure. Such experiences may eventually lead to learned helplessness, a psychological condition in which students feel that their efforts no longer influence learning outcomes. Students with learned helplessness have low persistence, low initiative, avoid academic activities, and decline of learning motivation. If this condition is not well addressed, it can become a barrier to academic development and social adaptation in inclusive educational environments.

Based on the preliminary observations of SMP Negeri 1 Sangatta Selatan, these challenges are found in the slow learners students. Out of the 32 students, seven students (21.9%) were identified as slow learners according to the school records and teachers’ recommendation. These students, according to early observations, were often less active participants in classroom instruction, lost motivation easily when faced with difficult learning tasks, and showed little independence in doing their homework. Furthermore, the initial learning motivation questionnaire results revealed that approximately 65% of the identified slow learner students had low learning motivation and only 10% were identified as having high learning motivation. The findings suggest that the academic problems of slow learner students are linked to psychological impediments that inhibit their motivation to take part in learning activities. Interventions such as academic guidance, classroom management strategies and individual counseling have been implemented to improve students’ learning motivation. However, conventional counseling services are often limited to verbal advice and motivational encouragement, and lack structured behavioral mechanisms to help students translate intentions into sustained learning behaviors. These approaches may not be effective for slow learner students as they require concrete guidance, observable behavioral targets and constant reinforcement for gradual change of behavior.

One behavioral intervention with practical potential is the behavior contract technique. Behavioral counseling theory explains that a behavior contract is a written agreement that states the expected behaviors, how to implement them, how to reinforce them, and how to evaluate them. The technique helps students to clearly understand what behaviors should be performed and what positive consequences will come from successful implementation by translating abstract expectations into concrete behavioral commitments. The systematic use of reinforcement also helps to create positive learning habits and gradually reinforce the self-efficacy of students through repeated experiences of success. Behavior contracts are even more effective in group counseling. Students can join group counseling in which they can communicate with other students with similar learning problems, share experiences, get emotional support, and see how other members of the group adjust their learning behaviors. Such group dynamics create a supportive psychological climate that encourages students to commit to behavioral change and at the same time reduces feelings of isolation and academic failure. Thus, the use of behaviour contract strategies in group counselling provides a comprehensive intervention that integrates behavioural modification with social support, which are both important for enhancing the learning motivation of slow learner students.

Previous research has generally found positive outcomes of behavioral counseling techniques in improving student discipline, responsibility and classroom behavior. Similarly, group counseling research has shown effectiveness in improving various psychological factors such as self-confidence, social interaction, and academic engagement. However, empirical evidence about the integration of group counseling and behavior contract techniques for the purpose of improving learning motivation of slow learner students in Indonesian inclusive junior high schools is still limited. Most existing studies focus on behavioral problems or academic achievement without explicitly examining motivational change among students with slow learning characteristics. This gap points to the need for further empirical research that addresses both behavioral intervention and motivational development in inclusive educational settings. The novelty of the present study is that it combines group counseling and the behavior contract technique as a structured behavioral intervention that is specifically designed to enhance the motivation of slow learner students to learn in an inclusive junior high school. This contrasts with earlier interventions which were primarily based on verbal encouragement, while this study concentrates on quantifiable behavioral commitments, positive reinforcement, peer support, and ongoing evaluation using cyclical classroom action research. It is expected that the integrated approach will provide a practical counseling model that can solve the psychological and behavioral aspects of learning motivation of slow learner students.

This study was aimed at improving the learning motivation of slow learner students at SMP Negeri 1 Sangatta Selatan through the application of group counseling with behavior contract technique. The results are expected to make a theoretical contribution to the development of behavioral counseling interventions for inclusive education and a practical contribution to guide school counselors and teachers to design more effective motivational support programs for slow learner students in inclusive schools.

METHOD

The research was conducted with the Guidance and Counseling Action Research (GCAR) model based on the spiral model of Kemmis and McTaggart which consists of four stages, namely planning, action, observation and reflection. The design was chosen because it allows for the continuous improvement of the counseling services according to the results obtained in each cycle. The present study was conducted in the context of school guidance and counseling services, unlike the action research in the classroom based on instructional practices. The intervention was a series of group counseling sessions with the use of behavior contract technique to improve the learning motivation of slow learner students through structured behavioral commitments and continuous reinforcement. The research was done in 2 cycles of action, so that the counseling strategy could be modified and strengthened if the desired motivational outcomes had not been attained in the prior cycle. This research was carried out in the second semester of the academic year 2025/2026 at SMP Negeri 1 Sangatta Selatan East Kutai Regency, Indonesia. The research setting was the school's guidance and counseling service, not the regular classroom, as the intervention was centred on counseling activities offered in small groups. Participants were purposively sampled on the basis of pre-determined inclusion criteria. The researchers’ participants were taken from seven students who were identified as slow learners through the school psychological records, teachers’ recommendations, academic documentation, and preliminary assessments by the school counselor. The preliminary assessment revealed low motivation to learn among all participants as shown by low persistence in completing academic tasks, low participation in learning activities, low learning independence, low perseverance when facing academic difficulties and inconsistent study habits. The small group size allowed for intensive interaction, ongoing monitoring, and individual behavioural support during the counselling process.

The intervention was delivered through two consecutive counseling cycles. During the planning phase, the researcher prepared plans of counseling sessions, behavior contract forms, behavioral targets and reinforcement strategies. The action phase consisted of group counseling sessions in which students collaboratively developed written contracts of behavior, including measurable learning behaviors, procedures for reinforcement, and consequences for the contract being fulfilled or not fulfilled. Observation sheets and counseling records were used to systematically monitor students’ learning motivation and behavioral changes during the observation phase. Finally, the reflection phase involved the researcher assessing the effectiveness of each cycle and utilizing the results to modify counseling strategies, behavioral targets, reinforcement mechanisms, and monitoring procedures before proceeding with the next cycle. The second cycle was mainly about improving students' commitment, providing more individualized reinforcement and improving adherence to the established behavior contracts. To ensure methodological triangulation, data were collected through multiple techniques, including learning motivation questionnaires, structured observations, semi-structured interviews and documentation. The instrument of the learning motivation questionnaire used the Likert scale, which was developed based on established indicators of learning motivation. Observation sheets were used to record students’ participation, persistence, compliance with behavior contracts and engagement during counseling. Interviews were used to gain insight into the students’ experiences, perceived challenges, and behavioral changes during the intervention. Documentation consisted of counseling records, behavior contract forms, observation sheets, and supporting school documents. Content validity of the instrument was verified by expert opinion. The reliability of the questionnaire was assessed by Cronbach’s Alpha, and the reliability of the observation was evaluated by inter-rater agreement between two observers. Quantitative data were descriptively analyzed by comparing the mean scores and percentages through the preliminary stage, Cycle I, and Cycle II, while qualitative data from observations, interviews, and documentation were analyzed using the interactive model of Miles and Huberman, which involved data reduction, data display, and conclusion drawing for a thorough interpretation of changes in students’ learning motivation.

RESULT AND DISCUSSION

Instrument Validity and Reliability Test

The validity of the instrument was determined by testing the validity of the instrument to find out whether each item in the questionnaire was a valid measure of the learning motivation construct. Validity analysis was conducted by IBM SPSS Statistics version 26 with Corrected Item-Total Correlation method. The instrument was administered to 32 respondents and the critical value of r-table was 0.349 with a significance level of 5% (α = 0.05). The item was accepted as valid if the corrected item-total correlation was greater than the r-table. The results showed that the corrected item-total correlation coefficients of all the items in the questionnaire were greater than 0.349. Therefore, all 15 items satisfied the validity criterion and were suitable for measuring students’ learning motivation.

Table 1.Instrument Validity Test Results

As shown in Table 1, all items of the questionnaire had corrected item-total correlation coefficients above the critical r-table value (0.349). Therefore, the whole instrument was considered to have adequate construct validity and appropriate for data collection in this study.

Reliability of the instrument was assessed after the validity analysis to find the internal consistency of the items of the questionnaire. Reliability testing was performed using Cronbach’s Alpha coefficient with IBM SPSS Statistics version 26. The instrument is said to be reliable based on the Cronbach’s Alpha coefficient when it is above 0.70 and the values above 0.90 are indicative of good internal consistency (Santos, 2012). The results of the reliability analysis showed that the Cronbach’s Alpha coefficient of the learning motivation questionnaire with 15 items was 0.942, which indicated a very high level of internal consistency.

Table 2. Reliability Test Results

The reliability analysis revealed that Cronbach’s Alpha coefficient of the 15-item learning motivation questionnaire was 0.942, indicating excellent internal consistency. Since the obtained coefficient was higher than the recommended threshold of 0.70, the instrument satisfied the reliability requirement and indicated a high level of consistency in measuring the intended construct. The results suggest that the items of the questionnaire consistently measured the students’ learning motivation and were appropriate to be used in the present study. The interpretation of the Cronbach’s Alpha coefficient is presented in Table 3. The alpha value obtained (0.942) falls into the Very High reliability category based on accepted reliability criteria. Therefore, the learning motivation questionnaire can be considered a highly reliable instrument and was deemed

Pre-Cycle (Baseline Condition)

The pre-cycle stage was conducted to find out the initial level of students’ motivation of learning before the application of group counseling with the technique of behavior contract. At this stage, a questionnaire for measuring learning motivation consisting of 15 Likert-scale items was administered to 32 seventh-grade students. The questionnaire was prepared to measure five indicators of learning motivation, namely: persistence in learning, active participation, independent learning, perseverance in overcoming difficulties, and consistency in fulfilling learning responsibilities. The results of the screening were used to identify students who required counseling intervention. The scores of the questionnaire were then classified into three levels: high (48-60), moderate (36-47) and low (15-35). Table 3 presents the distribution of student learning motivation.

Table 3. Distribution of Students' Learning Motivation in the Pre-Cycle

Table 3 indicates that the majority of students (56.25%) had a mild level of learning motivation and 25.00% of students were classified as high motivation. However, 18.75% of students were still in the low motivation category, which indicates that a large proportion of students still had motivational problems. In general, the results indicated that the learning motivation was not optimal and many students still needed more support to improve their involvement in the learning process.Based on the results of the first screening, seven students were selected purposively as subjects of the research. The selection was based on the lowest learning motivation scores including the students who were categorized as having low motivation and those with moderate motivation but their scores were near the lower threshold. The selected participants had an overall motivation score of 244, and the average score was 35, placing the group in the low motivation category. These findings indicate that the participants experienced difficulties in various motivational dimensions, particularly persistence, active engagement, learning autonomy, perseverance and consistency in learning activities. The baseline findings also indicated certain areas of deficiency in a number of motivational indices. The sixth questionnaire item was consistently scored low by all selected participants, indicating low willingness to participate actively during classroom learning or counseling activities. Similar patterns were obtained for persistence and independent learning indicators. This confirmed the participants’ deficiencies in several essential components of learning motivation. Hence, the pre-cycle findings gave a strong empirical foundation for the implementation of group counseling with the behavior contract technique as a structured behavioral intervention to improve the learning motivation of slow learner students in a gradual and measurable manner.

Cycle I

Cycle I was divided into four stages of action research such as planning, implementation, observation and reflection. In the planning phase, the researcher prepared the group counseling lesson plan, selected seven slow learner students who had low learning motivation based on the pre-cycle screening results, made the behavior contract forms, and prepared the observation sheets and learning motivation questionnaire. The intervention consisted of three counseling sessions during which students negotiated individual behavioral targets, signed written behavior contracts, received positive reinforcement, and had group discussions to reinforce their commitment to the agreed learning behaviors. The researcher observed the students responses and recorded the behavioral changes during the implementation to determine the effectiveness of the intervention. The results of the observation show that the implementation of group counseling generally followed the planned procedures. Students could understand the purpose of the behavior contract, set realistic behavioral goals, and actively participate in the preparation of written agreements. But there were some implementation challenges identified. There was no systematic daily monitoring of students’ behavioral commitments and the reinforcement given during the first cycle remained rather limited in frequency and variety. So although students began to show positive behavioral changes, they were not yet consistent enough to be considered habits. These results suggest that continuous monitoring and more varied reinforcement strategies are important components to enhance behavioral change among slow learner students.

Table 5. Implementation Fidelity of Group Counseling Using the Behavior Contract Technique (Cycle I)

The overall implementation fidelity was at a fair level with a mean score of 3.05 (Table 5). The most positive aspect was the preparation of written behavior contracts (4.00) where students were able to develop and agree to clear behavioral commitments. The lowest score was received for the daily monitoring (2.00) indicating that the progress of the students’ behavior was not consistently monitored throughout the intervention. This limitation reduced the power of reinforcement and partly explains the moderate behavioral changes seen in Cycle I. After the intervention, the same questionnaire was used to re-measure the learning motivation of students in the pre-cycle stage. The results showed an increase of motivation scores for the students in comparison with the baseline condition. The total score was 255 and the mean score was 36.4, which places the participants in the moderate motivation group. The majority of students were more willing to participate in counselling, more persistent in completing assigned tasks and more responsive to behavioural reinforcement. However, two students remained in the low motivation category indicating that behavioral change had not yet consistently occurred across all participants.

Table 6. Learning Motivation Scores of Participants in Cycle I

The overall results showed positive progress, but observations made during the counseling sessions indicated that there were still several motivational dimensions that needed improvement. Students still heavily relied on teacher guidance, the participation in group discussions was relatively limited and learning behaviors were not yet fully consistent. Persistence and classroom participation were better, whereas learning independence and behavioral consistency were relatively weaker. These results indicate that students were still adjusting to the behavior contract procedure and needed stronger reinforcement and more systematic behavioral monitoring. The effectiveness of the intervention was determined by comparing the mean motivation score in Cycle I with the pre-cycle condition.

Table 7. Comparison of Learning Motivation Between the Pre-Cycle and Cycle I

Table 7 shows that the average learning motivation of students increased from 34.0 in the pre-cycle to 36.4 in Cycle I. The increase was relatively small, but the results show that group counseling with the behavior contract technique had a positive effect on students' learning motivation. However, the success criteria set in advance had not been fully met yet as learning independence, behavioral consistency and daily monitoring were still below the expected. Therefore, Cycle II was carried out with a series of improvements including more systematic daily monitoring, more diverse reinforcement strategies, and more clearly defined behavioral objectives to promote more significant and lasting changes in students’ motivation for learning.

Cycle II

Cycle II was conducted based on the results of the reflection of Cycle I, which revealed that daily monitoring, behavioral consistency, and learning independence were below the expected level. Thus, a number of changes were made before the second cycle was implemented. These changes included revising the behavior contracts to include more specific and measurable behavioral targets, increasing the variety of reinforcement strategies to match students’ preferences, implementing structured daily monitoring through the use of behavioral checklists, and encouraging students to actively participate in setting both behavioral goals and rewards. These changes were intended to increase students’ commitment to their behavioral contracts and to increase the effectiveness of the counseling intervention. The implementation in Cycle II was much better than the previous cycle. Students were more actively involved in the whole counseling sessions and more responsible in implementing their behavioral commitments. Students’ enthusiasm for achieving their behavioral goals was enhanced by the new reinforcement strategies, which included individualized verbal praise, point-based rewards, and small tangible incentives. Similarly, the use of structured daily monitoring allowed the counselor and students to more consistently evaluate behavioral progress, strengthening the reinforcement process and helping to establish positive learning habits.

Table 8. Implementation Fidelity of Group Counseling Using the Behavior Contract Technique (Cycle II)

The overall implementation fidelity increased to a mean score of 3.8 indicating good level of implementation (Table 8). All aspects of the intervention improved considerably compared with Cycle I (3.05). The greatest gains were made in the explanation of behaviour contracts and in the preparation of written contracts, both of which attained the level of very good. Daily monitoring, which was previously the weakest link of the system during Cycle I, also improved drastically after the implementation of structured behavioral checklists and more systematic follow-up procedures. These findings indicate that the procedural improvements were successful in improving the quality and consistency of the counseling intervention. Students’ motivation to learn was again evaluated at the end of Cycle II using the same questionnaire as in the previous stages. The results showed that learning motivation increased significantly compared to Cycle I. The participants scored a total of 311, with an average score of 44.4, which is considered as high motivation. The result showed that five of the seven participants (71.4%) were in the high motivation category and two students (28.6%) were in the moderate motivation category. Importantly, there were no participants in the low motivation group. In addition to the quantitative improvement, classroom observations showed that students were more persistent in completing academic tasks, more active in counseling discussions, more independent in managing learning activities, and more consistent in carrying out their agreed behavioral commitments .

Table 9. Learning Motivation Scores of Participants in Cycle II

The quantitative findings were supported by the qualitative results from classroom observation and student interviews. Most of the participants stated that the behavior contract helped them to become more disciplined, responsible, and motivated to reach their learning goals. Students also expressed a sense of increased confidence in the counseling sessions and cited peer support, individual reinforcement, and clearly articulated behavioral goals as motivators to maintain positive learning behaviors. In addition, behavioral changes such as timely completion of assignments, reduction in procrastination, following study schedules, and reduction in mobile phone distractions became more evident in the second cycle. The results indicate that the intervention not only improved the students’ motivational scores but also led to significant changes in their behavioral patterns in everyday learning activities. The mean learning motivation scores obtained during each stage of the study were compared to evaluate the overall effectiveness of the intervention.

Table 10. Comparison of Learning Motivation Across the Research Stages

Table 10 shows that students’ motivation to learn increased over the course of the intervention. The mean score increased from 34.0 in the pre-cycle to 36.4 in Cycle I and 44.4 in Cycle II. The greatest improvement occurred after the changes made during Cycle II, namely, the introduction of more systematic monitoring, individualised reinforcement and clearer targets for behaviour. The results show that the group counseling with the behavior contract technique could improve the learning motivation of slow learner students. The action research ended with Cycle II because the predetermined success criteria were met, including no students in the low motivation category and most of the participants in the high motivation category.

Discussion

The results of this study show that the implementation of group counseling with the behavior contract technique was effective in improving the learning motivation of slow learner students through a process of gradual behavioral change. The intervention was carried out in two cycles of action research, which included stages of planning, implementation, observation and reflection. The more specific behavior targets, the structured daily monitoring, and the individualized reinforcement in Cycle II led to better fidelity of implementation than in Cycle I. The score of implementation increased from 3.05 (fair) to 3.80 (good) in Cycle II. It means that the procedures of counseling were more systematic and consistent after the reflection stage. These findings demonstrate that the quality of implementation of interventions is an important factor in determining the effectiveness of behavioral counseling programs. The improvement of implementation quality is in line with Skinner’s Behaviorist Theory that emphasizes behavioral change is strengthened through immediate and consistent reinforcement (Skinner, 1953). The reinforcement in Cycle I was relatively general and the daily monitoring was inconsistent, which limited the development of new learning behavior. Following the changes introduced in Cycle II, reinforcement was more individualized and meaningful and behavioural monitoring was done systematically with daily checklists. These procedural improvements increased student commitment to the agreed upon behavioral contracts and helped form more adaptive learning habits. Thus, results support the proposition that behavior contracts are more effective when reinforcement, behavioral expectations, and monitoring procedures are applied consistently.

The quantitative results also revealed that the use of behavior contract technique significantly improved students’ learning motivation. The average score of learning motivation progressively increased from 34.0 (low) at the pre-cycle stage to 36.4 (moderate) in Cycle I, and 44.4 (high) in Cycle II. In addition, there was a significant change in the distribution of motivation categories, where no students were in the low-motivation category at the end of Cycle II and more than two-thirds of the participants reached the high-motivation category. These results indicate that the intervention succeeded not only in raising average scores of motivation, but also in moving students towards higher levels of motivation. There seem to be several factors that explain this increase in learning motivation. First, students were actively involved in establishing their own behavioral targets, which increased their sense of ownership and responsibility with regard to the agreed commitments. Second, reinforcement was provided immediately after desirable behaviors, which strengthened students’ willingness to engage in positive learning behaviors. Third, daily monitoring provided ongoing feedback that allowed students to assess their own progress and remain accountable throughout the intervention. Finally, the supportive atmosphere created during group counseling helped students to share learning experiences, to give mutual encouragement, and to sustain the commitment to behavioral change. The behavioral contract technique seems to work because of the interaction between behavioral reinforcement and the supportive social milieu provided by the counseling sessions.

The present findings are in line with Bandura’s Social Learning Theory which proposes that motivation is developed through mastery experiences, social reinforcement, and increasing self-efficacy (Bandura, 1986). As students achieved their behavioral targets and received positive reinforcement from the counselor and peers, they became more confident. The interview results showed that the participants felt more responsible for their learning, more motivated to complete the tasks, and more confident in participating during counseling sessions. Thus, the motivation to learn was enhanced not only by external reinforcement, but also by the students’ enhanced confidence in their own ability to manage their learning behavior effectively. Changes in students' observable learning behaviors also support the effectiveness of the intervention. During two cycles of research, all the indicators of motivation (perseverance, activity in the classroom, independence in learning, perseverance, and constancy of behavior) increased. Cycle I identified the least developed Dimensions of independence in learning and behavioral consistency which demonstrated marked improvements. Behavioral consistency, although still the lowest of the five indicators in Cycle II, increased sufficiently to be categorized as “good” and suggested that students were beginning to develop more consistent learning habits. The findings indicate that behavioral change in slow learner students is a result of repeated practice, continuous reinforcement and systematic monitoring and not through immediate transformation.

The observed behavioral improvements are consistent with the proposition by Gage and Berliner (1998) that observable behaviors such as persistence, effort, active participation and sustained engagement in learning activities are indicative of learning motivation. In Cycle II, students were more willing to take on tasks independently, procrastinated less, participated more actively in the counseling discussion, and followed their study schedules more consistently. These changes in behavior show that the intervention had an effect on students’ motivational perceptions, but also on their learning practices. Thus, the behavior contract was a practical tool for self-regulation, converting motivational intentions into measurable behavioral outcomes. The study concluded that group counseling with behavior contract technique is effective intervention to improve learning motivation of slow learner students. The success of the intervention seems to be associated with three interdependent components: clearly defined behavioral goals; consistent reinforcement; and systematic behavioral monitoring. These components are provided in a supportive group counseling environment that enhances students’ motivation, responsibility, and involvement in their learning activities. Therefore, this study provides empirical evidence that behaviour contract techniques could be used as an effective behavioural counselling strategy for the promotion of sustainable improvement of learning motivation among slow learner students especially in the inclusive educational setting.

CONCLUSION

The result of this classroom guidance and counseling action research shows that the implementation of group counseling through behavior contract technique was effective in improving the learning motivation of slow learner students. The quality of implementation of the intervention improved from Cycle I to Cycle II due to more systematic behavioral targets, consistent daily monitoring, and more individualized reinforcement. Following the improvements, the average score of students’ learning motivation gradually increased with the score of 34.0 (low) at the pre-cycle stage, 36.4 (moderate) at Cycle I, and 44.4 (high) at Cycle II. In addition, positive behavioral modifications were observed in all motivational indicators, persistence, active participation, learning independence, perseverance, and behavioral consistency. Behavioral consistency was the lowest of the five indicators, but it too improved to the good category by the end of the intervention. Overall, the results suggest that the behavior contract method provides an effective behavioral counseling strategy for the development of more disciplined, responsible and motivated learning behaviors among slow learner students . Recommendations Based on the findings of this study, it is recommended that school counselors include the behavior contract technique in group counseling services as an alternative technique to improve students’ learning motivation with continuous monitoring and appropriate reinforcement throughout the intervention process. Schools should encourage the efforts of counselors, classroom teachers and parents to work together to promote positive learning behaviors at school and at home and to help implement innovative counseling programs. Students should be encouraged to maintain the positive learning habits they have developed during the intervention and to gradually develop stronger intrinsic motivation beyond external reinforcement. Future researchers are suggested to include larger samples, extend the intervention period, and examine other variables such as self-regulation, learning engagement, or time management to present wider evidence of the efficacy of behavior contract interventions on the improvement of students’ academic motivation and behavioral outcomes.